(bright upbeat music) >> Hello everyone, and welcome to this exclusive Cube Conversation. We have the pleasure today to welcome, Wim Coekaerts, senior vice president of software development at Oracle. Wim, it's good to see you. How you been, sir? >> Good, it's been a while since we last talked but I'm excited to be here, as always. >> It was during COVID though and so I hope to see you face to face soon. But so Wim, since the Barron's Article declared Oracle a Cloud giant, we've really been sort of paying attention and amping up our coverage of Oracle and asking a lot of questions like, is Oracle really a Cloud giant? And I'll say this, we've always stressed that Oracle invests in R&D and of course there's a lot of D in that equation. And over the past year, we've seen, of course the autonomous database is ramping up, especially notable on Exadata Cloud@Customer, we've covered that extensively. We covered the autonomous data warehouse announcement, the blockchain piece, which of course got me excited 'cause I get to talk about crypto with Juan. Roving Edge, which for everybody who might not be familiar with that, it's an edge cloud service, dedicated regions that you guys announced, which is a managed cloud region. And so it's clear, you guys are serious about cloud. These are all cloud first services using second gen OCI. So, Oracle's making some moves but the question is, what are customers doing? Are they buying this stuff? Are they leaning into these new deployment models for the databases? What can you tell us? >> You know, definitely. And I think, you know, the reason that we have so many different services is that not every customer is the same, right? One of the things that people don't necessarily realize, I guess, is in the early days of cloud lots of startups went there because they had no local infrastructure. It was easy for them to get started in something completely new. Our customers are mostly enterprise customers that have huge data centers in many cases, they have lots of real estate local. And when they think about cloud they're wondering how can we create an environment that doesn't cause us to have two ops teams and two ways of managing things. And so, they're trying to figure out exactly what it means to take their real estate and either move it wholesale to the cloud over a period of years, or they say, "Hey, some of these things need to be local maybe even for regulatory purposes." Or just because they want to keep some data locally within their own data centers but then they have to move other things remotely. And so, there's many different ways of solving the problem. And you can't just say, "Here's one cloud, this is where you go and that's it." So, we basically say, if you're on prem, we provide you with cloud services on-premises, like dedicated regions or Oracle Exadata Cloud@Customer and so forth so that you get the benefits of what we built for cloud and spend a lot of time on, but you can run them in your own data center or people say, "No, no, no. I want to get rid of my data centers, I do it remotely." Okay, then you do it in Oracle cloud directly. Or you have a hybrid model where you say, "Some stays local, some is remote." The nice thing is you get the exact same API, the exact same way of managing things, no matter how you deploy it. And that's a big differentiator. >> So, is it fair to say that you guys have, I think of it as a purpose built club, 'cause I talk to a lot of customers. I mean, take an insurance app like Claims, and customers tell me, "I'm not putting that into the public cloud." But you're making a case that it actually might make sense in your cloud because you can support those mission critical applications with the exact same experience, same API, same... I can get, you know, take Rack for instance, I can't get, you know, real application clusters in an Amazon cloud but presumably I can get them in your cloud. So, is it fair to say you have a purpose built cloud specifically for the most demanding applications? Is that a right way to look at it or not necessarily? >> Well, it's interesting. I think the thing to be careful of is, I guess, purpose built cloud might for some people mean, "Oh, you can only do things if it's Oracle centric." Right, and so I think that fundamentally, Oracle cloud provides a generic cloud. You can run anything you want, any application, any deployment model that you have. Whether you're an Oracle customer or not, we provide you with a full cloud service, right? However, given that we know and have known, obviously for a long time, how our products run best, when we designed OCI gen two, when we designed the networking stack, the storage layer and all that stuff, we made sure that it would be capable of running our more complex environments because our advantage is, Oracle customers have a place where they can run Oracle the best. Right, and so obviously the context of purpose-built fits that model, where yes, we've made some design choices that allow us to run Rack inside OCI and allow us to deploy Exadatas inside OCI which you cannot do in other clouds. So yes, it's purpose built in that sense but I would caution on the side of that it sometimes might imply that it's unique to Oracle products and I guess one way to look at it is if you can run Oracle, you can run everything else, right? Because it's such a complex suite of products that if you can run that then it it'll support any other (mumbling). >> Right. Right, it's like New York city. You make it there, you can make it anywhere. If I can run the most demanding mission critical applications, well, then I can run a web app for instance, okay. I got a question on tooling 'cause there's a lot of tooling, like sometimes it makes my eyes bleed when I look at all this stuff and doesn't... Square the circle for me, doesn't autonomous, an autonomous database like Autonomous Linux, for instance, doesn't it eliminate the need for all these management tools? >> You know, it does. It eliminates the need for the management at the lower level, right. So, with the autonomous Linux, what we offer and what we do is, we automatically patch the operating system for you and make sure it's secure from a security patching point of view. We eliminate the downtime, so when we do it then you don't have to restart applications. However, we don't know necessarily what the app is that is installed on top of it. You know, people can deploy their own applications, they can run third party applications, they can use it for development environments and so forth. So, there's sort of the core operating system layer and on the database side, you know, we take care of database patching and upgrades and storage management and all that stuff. So the same thing, if you run your own application inside the database, we can manage the database portion but we don't manage the application portion just like on the operating system. And so, there's still a management level that's required, no matter what, a level above that. And the other thing and I think this is what a lot of the stuff we're doing is based on is, you still have tons of stuff on-premises that needs full management. You have applications that you migrate that are not running Autonomous Linux, could be a Windows application that's running or it could be something on a different Linux distribution or you could still have some databases installed that you manage yourself, you don't want to use the autonomous or you're on a third-party. And so we want to make sure that we can address all of them with a single set of tools, right. >> Okay, so I wonder, can you give us just an overview, just briefly of the products that comprise into the cloud services, your management solution, what's in that portfolio? How should we think about it? >> Yeah, so it basically starts with Enterprise Manager on-premises, right? Which has been the tool that our Oracle database customers in particular have been using for many years and is widely used by our customer base. And so you have those customers, most of their real estate is on-premises and they can use enterprise management with local. They have it running and they don't want to change. They can keep doing that and we keep enhancing as you know, with newer versions of Enterprise Manager getting better. So, then there's the transition to cloud and so what we've been doing over the last several years is basically, looking at the things, well, one aspect is looking at things people, likes of Enterprise Manager and make sure that we provide similar functionality in Oracle cloud. So, we have Performance Hub for looking at how the database performance is working. We have APM for Application Performance Monitoring, we have Logging Analytics that looks at all the different log files and helps make sense of it for you. We have Database Management. So, a lot of the functionality that people like in Enterprise Manager mentioned the database that we've built into Oracle cloud, and, you know, a number of other things that are coming Operations Insights, to look at how databases are performing and how we can potentially do consolidation and stuff. So we've basically looked at what people have been using on-premises, how we can replicate that in Oracle cloud and then also, when you're in a cloud, how you can make make use of all the base services that a cloud vendor provides, telemetry, logging and so forth. And so, it's a broad portfolio and what it allows us to do with our customers is say, "Look, if you're predominantly on-prem, you want to stay there, keep using Enterprise Manager. If you're starting to move to Oracle cloud, you can first use EM, look at what's happening in the cloud and then switch over, start using all the management products we have in the cloud and let go of the Enterprise Manager instance on-premise. So you can gradually shift, you can start using more and more. Maybe you start with analytics first and then you start with insights and then you switch to database management. So there's a whole suite of possibilities. >> (indistinct) you mentioned APM, I've been watching that space, it's really evolved. I mean, you saw, you know, years ago, Splunk came out with sort of log analytics, maybe simplified that a little bit, now you're seeing some open source stuff come out. You're seeing a lot of startups come out, you saw Cisco made an acquisition with AppD and that whole space is transforming it seems that the future is all about that end to end visibility, simplifying the ability to remediate problems. And I'm thinking, okay, you just mentioned, you guys have a lot of these capabilities, you got Autonomous, is that sort of where you're headed with your capabilities? >> It definitely is and in fact, one of the... So, you know, APM allows you to say, "Hey, here's my web browser and it's making a connection to the database, to a middle tier" and it's hard for operations people in companies to say, hey, the end user calls and says, "You know, my order entry system is slow. Is it the browser? Is it the middle tier that they connect to? Is it the database that's overloaded in the backend?" And so, APM helps you with tracing, you know, what happens from where to where, where the delays are. Now, once you know where the delay is, you need to drill down on it. And then you need to go look at log files. And that's where the logging piece comes in. And what happens very often is that these log files are very difficult to read. You have networking log files and you have database log files and you have reslog files and you almost have to be an expert in all of these things. And so, then with Logging Analytics, we basically provide sort of an expert dashboard system on top of that, that allows us to say, "Hey! When you look at logging for the network stack, here are the most important errors that we could find." So you don't have to go and learn all the details of these things. And so, the real advantages of saying, "Hey, we have APM, we have Logging Analytics, we can tie the two together." Right, and so we can provide a solution that actually helps solve the problem, rather than, you need to use APM for one vendor, you need to use Logging Analytics from another vendor and you know, that doesn't necessarily work very well. >> Yeah and that's why you're seeing with like the ELK Stack it's cool, you're an open source guy, it's cool as an open source, but it's complicated to set up all that that brings. So, that's kind of a cool approach that you guys are taking. You mentioned Enterprise Manager, you just made a recent announcement, a new release. What's new in that new release? >> So Enterprise Manager 13.5 just got released. And so EM keeps improving, right? We've made a lot of changes over over the years and one of the things we've done in recent years is do more frequent updates sort of the cloud model frequent updates that are not just bug fixes but also introduce new functionality so people get more stuff more frequently rather than you know, once a year. And that's certainly been very attractive because it shows that it's a lively evolving product. And one of the main focus areas of course is cloud. And so a lot of work that happens in Enterprise Manager is hybrid cloud, which basically means I run Enterprise Manager and I have some stuff in Oracle cloud, I might have some other stuff in another cloud vendors environment and so we can actually see which databases are where and provide you with one consolidated view and one tool, right? And of course it supports Autonomous Database and Exadata in cloud servers and so forth. So you can from EM see both your databases on-premises and also how it's doing in in Oracle cloud as you potentially migrate things over. So that's one aspect. And then the other one is in terms of operations and automation. One of the things that we started doing again with Enterprise Manager in the last few years is making sure that everything has a REST API. So we try to make the experience with Enterprise Manager be very similar to how people work with a cloud service. Most folks now writing automation tools are used to calling REST APIs. EM in the early days didn't have REST APIs, now we're making sure everything works that way. And one of the advantages is that we can do extensibility without having to rewrite the product, that we just add the API clause in the agent and it makes it a lot easier to become part of the modern system. Another thing that we introduced last year but that we're evolving with more dashboards and so forth is the Grafana plugin. So even though Enterprise Manager provides lots of cool tools, a lot of cloud operations folks use a tool called Grafana. And so we provide a plugin that allows customers to have Grafana dashboards but the data actually comes out of Enterprise Manager. So that allows us to integrate EM into a more cloudy world in a cloud environment. I think the other important part is making sure that again, Enterprise Manager has sort of a cloud feel to it. So when you do patching and upgrades, it's near zero downtime which basically means that we do all the upgrades for you without having to bring EM down. Because even though it's a management tool, it's used for operations. So if there were downtime for patching Enterprise Manager for an hour, then for that hour, it's a blackout window for all the monitoring we do. And so we want to avoid that from happening, so now EM is upgrading, even though all the events are still happening and being processed, and then we do a very short switch. So that help our operations people to be more available. >> Yes. I mean, I've been talking about Automated Operations since, you know, lights out data centers since the eighties back in (laughs). I remember (indistinct) data center one-time lights out there were storage tech libraries in there and so... But there were a lot of unintended consequences around, you know, automated ops, and so people were sort of scared to go there, at least lean in too much but now with all this machine intelligence... So you're talking about ops automation, you mentioned the REST APIs, the Grafana plugins, the Cloud feel, is that what you're bringing to the table that's unique, is that unique to Oracle? >> Well, the integration with Oracle in that sense is unique. So one example is you mentioned the word migration, right? And so database migration tends to be something, you know, customers obviously take very serious. We go from one place, you have to move all your data to another place that runs in a slightly different environment. And so how do you know whether that migration is going to work? And you can't migrate a thousand databases manually, right? So automation, again, it's not just... Automation is not just to say, "Hey, I can do an upgrade of a system or I can make sure that nothing is done by hand when you patch something." It's more about having a huge fleet of servers and a huge fleet of databases. How can you move something from one place to another and automate that? And so with EM, you know, we start with sort of the prerequisite phase. So we're looking at the existing environment, how much memory does it need? How much storage does it use? Which version of the database does it have? How much data is there to move? Then on the target side, we see whether the target can actually run in that environment. Then we go and look at, you know, how do you want to migrate? Do you want to migrate everything from a sort of a physical model or do you want to migrate it from a logical model? Do you want to do it while your environment is still running so that you start backing up the data to the target database while your existing production system is still running? Then we do a short switch afterwards, or you say, "No, I want to bring my database down. I want to do the migrate and then bring it back up." So there's different deployment models that we can let our customers pick. And then when the migration is done, we have a ton of health checks that can validate whether the target database will run through basically the exact same way. And then you can say, "I want to migrate 10 databases or 50 databases" and it'll work, It's all automated out of the box. >> So you're saying, I mean, you've looked at the prevailing way you've done migrations, historically you'd have to freeze the code and then migrate, and it would take forever, it was a function of the number of lines of code you had. And then a lot of times, you know, people would say, "We're not going to freeze the code" and then they would almost go out of business trying to merge the two. You're saying in 2021, you can give customers the choice, you can migrate, you could change the, you know, refuel the plane while you're in midair? Is that essentially what you're saying? >> That's a good way of describing it, yeah. So your existing database is running and we can do a logical backup and restore. So while transactions are happening we're still migrating it over and then you can do a cutoff. It makes the transition a lot easier. But the other thing is that in the past, migrations would typically be two things. One is one database version to the next, more upgrades than migration. Then the second one is that old hardware or a different CPU architecture are moving to newer hardware in a new CPU architecture. Those were sort of the typical migrations that you had prior to Cloud. And from a CIS admin point of view or a DBA it was all something you could touch, that you could physically touch the boxes. When you move to cloud, it's this nebulous thing somewhere in a data center that you have no access to. And that by itself creates a barrier to a lot of admins and DBA's from saying, "Oh, it'll be okay." There's a lot of concern. And so by baking in all these tests and the prerequisites and all the dashboards to say, you know, "This is what you use. These are the features you use. We know that they're available on the other side so you can do the migration." It helps solve some of these problems and remove the barriers. >> Well that was just kind of same same vision when you guys came up with it. I don't know, quite a while ago now. And it took a while to get there with, you know, you had gen one and then gen two but that is, I think, unique to Oracle. I know maybe some others that are trying to do that as well, but you were really the first to do that and so... I want to switch topics to talk about security. It's hot topic. You guys, you know, like many companies really focused on security. Does Enterprise Manager bring any of that over? I mean, the prevailing way to do security often times is to do scripts and write, you know, custom security policy scripts are fragile, they break, what can you tell us about security? >> Yeah. So there's really two things, you know. One is, we obviously have our own best security practices. How we run a database inside Oracle for our own world, we've learned about that over the years. And so we sort of baked that knowledge into Enterprise Manager. So we can say, "Hey, if you install this way, we do the install and the configuration based on our best practice." That's one thing. The other one is there's STIG, there's PCI and they're ShipBob, those are the main ones. And so customers can do their own way. They can download the documentation and do it manually. But what we've done is, and we've done this for a long time, is basically bake those policies into Enterprise Manager. So you can say, "Here's my database this needs to be PCI compliant or it needs to be HIPAA compliant and you push a button and then we validate the policies in those documents or in those prescript described files. And we make sure that the database is combined to that. And so we take that manual work and all that stuff basically out of the picture, we say, "Push this button and we'll take care of it." >> Now, Wim, but just quick sidebar here, last time we talked, it was under a year ago. It was definitely during COVID and it's still during COVID. We talked about the state of the penguin. So I'm wondering, you know, what's the latest update for Linux, any Linux developments that we should be aware of? >> Linux, we're still working very hard on Autonomous Linux and that's something where we can really differentiate and solve a problem. Of course, one of the things to mention is that Enterprise Manager can can do HIPAA compliance on Oracle Linux as well. So the security practices are not just for the database it can also go down to the operating system. Anyway, so on the Autonomous Linux side, you know, management in an Oracle Cloud's OS management is evolving. We're spending a lot of time on integrating log capturing, and if something were to go wrong that we can analyze a log file on the fly and send you a notification saying, "Hey, you know there was this bug and here's the cause." And it was potentially a fix for it to Autonomous Linux and we're putting a lot of effort into that. And then also sort of IT/operation management where we can look at the different applications that are running. So you're running a web server on a Linux environment or you're running some Java processes, we can see what's running. We can say, "Hey, here's the CPU utilization over the past week or the past year." And then how is this evolving? Say, if something suddenly spikes we can say, "Well, that's normal, because every Monday morning at 10 o'clock there's a spike or this is abnormal." And then you can start drilling this down. And this comes back to overtime integration with whether it's APM or Logging Analytics, we can tie the dots, right? We can connect them, we can say, "Push this thing, then click on that link." We give you the information. So it's that integration with the entire cloud platform that's really happening now >> Integration, there's that theme again. I want to come back to migration and I think you did a good job of explaining how you sort of make that non-disruptive and you know, your customers, I think, you know, generally you're pushing you know, that experience which makes people more comfortable. But my question is, why do people want to migrate if it works and it's on prem, are they doing it just because they want to get out of the data center business? Or is it a better experience in the cloud? What can you tell us there? >> You know, it's a little bit of everything. You know, one is, of course the idea that data center maintenance costs are very high. The other one is that when you run your own data center, you know, we obviously have this problem but when you're a cloud vendor, you have these problems but we're in this business. But if you buy a server, then in three years that server basically is depreciated by new versions and they have to do migration stuff. And so one of the advantages with cloud is you push a button, you have a new version of the hardware, basically, right? So the refreshes happen on a regular basis. You don't have to go and recycle that yourself. Then the other part is the subscription model. It's a lot easier to pay for what you use rather than you have a data center whether it's used or not, you pay for it. So there's the cost advantages and predictability of what you need, you pay for, you can say, "Oh next year we need to get x more of EMs." And it's easier to scale that, right? We take care of dealing with capacity planning. You don't have to deal with capacity planning of hardware, we do that as the cloud vendor. So there's all these practical advantages you get from doing it remotely and that's really what the appeal is. >> Right. So, as it relates to Enterprise Manager, did you guys have to like tear down the code and rebuild it? Was it entire like redo? How did you achieve that? >> No, no, no. So, Enterprise Manager keeps evolving and you know, we changed the underlying technologies here and there, piecemeal, not sort of a wholesale replacement. And so in talking about five, there's a lot of new stuff but it's built on the existing EM core. And so we're just, you know, improving certain areas. One of the things is, stability is important for our customers, obviously. And so by picking things piecemeal, we replace one engine rather than the whole thing. It allows us to introduce change more slowly, right. And then it's well-tested as a unit and then when we go on to the next thing. And then the other one is I mentioned earlier, a lot of the automation and extensibility comes from REST APIs. And so instead of basically re-writing everything we just provide a REST endpoint and we make all the new features that we built automatically be REST enabled. So that makes it a lot easier for us to introduce new stuff. >> Got it. So if I want to poke around with this new version of Enterprise Manager, can I do that? Is there a place I can go, do I have to call a rep? How does that work? >> Yeah, so for information you can just go to oracle.com/enterprise manager. That's the website that has all the data. The other thing is if you're already playing with Oracle Cloud or you use Oracle Cloud, we have Enterprise Manager images in the marketplace. So if you have never used EM, you can go to Oracle Cloud, push a button in the marketplace and you get a full Enterprise Manager installation in a matter of minutes. And then you can just start using that as well. >> Awesome. Hey, I wanted to ask you about, you know, people forget that you guys are the stewards of MySQL and we've been looking at MySQL Database Cloud service with HeatWave Did you name that? And so I wonder if you could talk about what you're doing with regard to managing HeatWave environments? >> So, HeatWave is the MySQL option that helps with analytics, right? And it really accelerates MySQL usage by 100 x and in some cases more and it's transparent to the customer. So as a MySQL user, you connect with standard MySQL applications and APIs and SQL and everything. And the HeatWave part is all done within the MySQL server. The engine itself says, "Oh, this SQL query, we can offload to the backend HeatWave cluster," which then goes in memory operations and blazingly fast returns it to you. And so the nice thing is that it turns every single MySQL database into also a data warehouse without any change whatsoever in your application. So it's been widely popular and it's quite exciting. I didn't personally name it, HeatWave, that was not my decision, but it sounds very cool. >> That's very cool. >> Yeah, It's a very cool name. >> We love MySQL, we started our company on the lamp stack, so like many >> Oh? >> Yeah, yeah. >> Yeah, yeah. That's great. So, yeah. And so with HeatWave or MySQL in general we're basically doing the same thing as we have done for the Oracle Database. So we're going to add more functionality in our database management tools to also look at HeatWave. So whether it's doing things like performance hub or generic database management and monitoring tools, we'll expand that in, you know, in the near future, in the future. >> That's great. Well, Wim, it's always a pleasure. Thank you so much for coming back in "The Cube" and letting me ask all my Colombo questions. It was really a pleasure having you. (mumbling) >> It's good be here. Thank you so much. >> You're welcome. And thank you for watching, everybody, this is Dave Vellante. We'll see you next time. (bright music)

(upbeat music) >> Hi, and welcome to theCUBE, the leading source for insights into the world of technology and innovation. I'm your host Donald Klein, and today's topic is the market for autonomous vehicles and the ecosystem suppliers looking to tap into this brave new world of autonomous capabilities in our daily commute. To have this conversation I'm joined by Rudy Burger, managing partner at Woodside Capital. Rudy, welcome to the show. >> Thanks Don, it's great to be here. >> Great, so look, why don't we start off Rudy, why don't you tell us a little bit about Woodside Capital and your role there? >> Great, so I founded Woodside Capital about 20 years ago having started five different companies of my own, one of which I took public. We are a specialist M&A advisor. We work with so-called growth stage often venture-backed companies and help them find buyers that are usually much larger public companies. Our clients are usually US or European companies and we find buyers in the US, Europe, or Asia. >> Excellent, excellent, okay. And why don't you talk a little bit about your kind of specialty areas? >> So I focused my career, and certainly the work at Woodside Capital, on imaging technologies and as an enabling technology, and the products and markets that are enabled by imaging and increasingly computer vision. So nowadays that is autonomous vehicles, consumer technology, security surveillance, and digital health. So enabling technologies, the computer vision is the theme that binds those together. >> Okay, well, the thing that's on everybody's mind these days is autonomous vehicles, when are we going to get them? Very high profile for sure. Before the show we talking about the kind of two key ingredients to making this happen, the AI software which is kind of the brains of the operation and then also the sensors which enable all of the AI. So why don't we talk about the sensor world first, okay? Lot of discussion about there, so sort of does the brave new world of vehicles need lidar? Does it not need lidar? Are there other types of sensors coming along? What's your sense of that market and how it's looking for all of the different players in it? >> So, Don, I look at it from a sort of fairly basic standpoint. Humans have two very capable image sensors and a very powerful processor, and the degree to which the automotive manufacturers and so-called Robo-Taxi developers have decided it's necessary to sprinkle every sensor known to man, and I'm talking lidar, radar, ultrasound, thermal, and of course cameras, is to some extent a degree to which, you know, image sensors are not as good as our eyes today. Now, there are some areas in which we will probably always have technology as a help. For example, humans are not very good at seeing in the dark whereas a thermal technology can do that very well. But my overall belief is that it's never a good idea to bet against an incumbent technology, and in this case I'm talking about so-called CMOS image sensors which are the sensor that goes into pretty much every camera in the world now. It's never a good idea to bet against the incumbent technology being able to scale into a new market. Every time people have done that, they've been wrong. Back in the early days the debate was whether CMOS image sensors would ever be good enough to replace CCDs as the sensor technology, and of course now, you know, everything uses CMOS image sensors. In other markets there was a long period of time in which people were thinking that LCD panels would never be large enough to replace, you know, for television, for example, 50 inch and so forth. It was never going to happen, so we needed plasma TVs, we needed rear-projection TVs. But slowly but surely the incumbent technology, LCDs, expanded to that market. So my belief is that CMOS image sensors will evolve to a point at which they will replace the need for lidar in most applications. >> Interesting, so that's a very controversial statement, right? Because you've certainly seen a lot of emphasis on the development of new generation lidar capability. >> Over 100 lidar companies started over the last three, four years, and of course many of them will not be happy to hear me say that. There are two distinct markets and one is the so-called Robo-Taxi market, and the other is more of the consumer vehicle ADAS market, and I think we need to think about those separately because the economics behind both are very different. If you look at the Robo-Taxi market, those vehicles tend to be much more expensive and are relatively price-insensitive. So if they can improve safety a little bit by putting a lidar on there, you know, great, let's do it, multiple lidars because these vehicles will be in operation 24 by seven, and if each vehicle costs 200,000, $250,000, fine. When we talk about the mass market for automobiles, type of car that you and I might go down and buy, very different thing. And, you know, auto makers sweat the pennies, and so putting a one or $200 lidar in a vehicle, big decision. And to the extent that they can replace the need for that lidar with a much less expensive camera system, that's what they'll do. Bear in mind that Mobileye, which has been the biggest success story, acquired by Intel for $13.5 billion, second largest acquisition Intel ever made, they for the most part still run on one camera, forward-looking camera. That's it, no radar, no lidar, no thermal, one camera. So the clever use of image processing, computer vision, and one image sensor can do a great deal. >> Interesting, okay. Well, so I want to talk about the software in just a second, but just to kind of finish this point, so if you were advising a sensor company that's developing some next gen capabilities, whether lidar or other related technologies, is the point you're making here that there are certain segments of this industry which are going to be more attractive to your technology than others? >> Absolutely, yes. I mean, the first thing to recognize is that the automotive industry has never really been a particularly comfortable fit with the economics and timeline of venture capital. VCs need to invest and recoup and redeploy back to their LPs on an eight-year cycle. But the automotive industry moves quite slowly, perhaps Tesla are excepted, and what the first piece of advice I would give these companies is it's probably going to be three, four, five years before, even if you have the right technology, before that technology really starts generating any significant volume and revenue. So for many venture-backed companies, that's too long. So the first piece of advice is find pockets of revenue, right, beachheads if you will, where you can land your technology and start generating revenue before you get to the automotive market. And many of these lidar companies we just talked about are not going to last long enough to get to the automotive market because not only does the automotive market move slowly but the autonomous vehicle market keeps on getting pushed out to the right as the industry realizes that this is a big, hairy problem. And so I would say, what is it that your technology can do an order of magnitude better than any other technology? Focus on that and find some opportunities for revenue outside the automotive industry that will sustain the company on its way to the holy grail. >> Interesting, yeah, so find that alternative revenue source to get you to base camp, and then when the market's ready, climb that Everest to-- >> I've seen so many companies basically go out of business because they've set their sights on either the automotive market, and it's go for broke. We're not interested in, all these other things are distractions. You know, entrepreneurs don't have a plan B. Or this. We're going to get our technology into a smartphone, that's it. And there are possibly some other opportunities but it takes so long and it's so difficult to get your technology into a smartphone that they go out of business before they ever get to that point. >> Interesting, okay. So good advice for people looking to kind of apply their technology in this kind of a very difficult market, right, very complicated market. All right, well, then let's switch to the other side of it. So we were kind of talking about the key ingredients, right? Sensors but also AI and the software around that, okay, and there are some very big players developing the software. Tesla's had their Autonomy Day where they've showcased their technology. You've obviously got Google with their capabilities developing software. How do you make sense of this overall landscape because we do see a lot of smaller providers also trying to develop software here. >> So the first thing that I find fascinating about the automotive industry is that for the most part there is no software market. There's perhaps one exception of any scale, that's BlackBerry that sells the QNX software. They found a point within the entertainment console where they can license their software. But for all of the development and capital invested into automotive software, nobody is actually generating revenue, making a living, by licensing software. And one of the main reasons for that is that, you know, the automotive market, really since inception, has been a hardware business. This is a business of bending sheet metal, internal combustion engines, and software has really not played that big a role up until relatively recently. So even those companies that do have software technology have ended up selling it into the automotive supply chain as a piece of silicon, embedded on a piece of silicon, not as, you know, here's my software on a USB stick, right? I think that the whole software licensing model hasn't so far fit well, fit comfortably, with the automotive industry. And the other reason is that there's no standard platform. If I were to develop a piece of software, I can, in the PC industry, I can develop for Windows, I can develop for Mac, I can develop for an iPhone. There's no such thing in the automotive industry, and particularly in this new world of autonomous vehicles there is no standard platform. There are many different processors, Nvidia has staked an early claim there. And the reason that most of the companies developing autonomous vehicle technology have developed the so-called full-stack solution, everything from code running on the processor, integrated through the sensors and so forth, is for that reason, there is no standard platform. So each company has developed the whole solution for themselves, and there are many of them around here that have raised hundreds of millions of dollars, some cases billions of dollars, for that purpose. So there is, today, no software market for automotive in the same way that we think about it in other industries. >> Understood, understood. But in terms of the companies that are actually pushing the envelope on these kind of capabilities, right, so we're taking the best of AI, we're applying it to big data sets, and then hopefully being able to extract that to create capabilities for these vehicles, right? What's your sense of how far that's come along in-- >> Well, it's come a long way but, here I'm going to push the boat out a little bit. I don't believe that the so-called deep learning technology, which is the current state of the art for AI, it's the technology that has allowed computers to beat humans at chess, at Go, I don't think that that flavor of AI, that approach to AI, is ever going to get us to safe enough autonomous vehicles. And that's because it works extremely well in fairly well-bounded rules, rule-bounded games or any scenario like that, but can you imagine trying to teach your 16-year-old how to drive by showing them images of every situation that they might encounter, right? Impossible. It's an infinite, it's not a well-bounded set. And that's so difficult because we really haven't developed the technology to allow computers to learn, to have things like common sense, to infer, you know, well, this happened, so this is likely to happen. So I think we are going to need a whole new breakthrough in AI before we get to what is generally considered safe enough vehicles. >> Interesting, well then, maybe if we kind of apply your previous thought about sort of Robo-Taxis as maybe being the segment where you're going to see the most use of these newer sensor technologies. >> Rudy: Near term, yes. >> Exactly, what about maybe, is that sort of the same rules apply there for maybe the AI providers, that they're-- >> I think so and that's why they're all focused on that. I mean, from Uber to Waymo, they've all made the same calculation which is if you're running a fleet of vehicles, and so for example in Uber's case, the driver takes 80% of the fare and only 20% goes back to Uber, but if you can replace the driver with a computer, you can keep that vehicle on the road 24 by seven and you can keep 100% of the revenue. You don't need to pay the computer. So that's the calculus that they're all going through. But I think that many of them are making a fundamental mistake and I predicted recently that I think Uber, my prediction for 2020 is that Uber is going to divest its autonomous vehicle business and get back to the business that it should be focused on. Uber generates about $14 billion a year in gross revenue, so 20% of that, which is the piece that Uber keeps after the drivers take their 80, is what, 2.8 billion. Uber should be able to be an extremely profitable business on 2.8 billion of net revenue, but they're spending a huge chunk of money every year on R&D. Now, I would argue that Hertz and Avis have successful businesses. They're in the service, they're in the transportation business, but they didn't decide that they had to build their own cars in order to be in that business. My view, personal view, is that what Uber should be doing is saying, that's not our business, right? We are the world's best at managing this sort of peer-to-peer network crowdsourced transportation, if you will. And when some company, some Silicon Valley startup, comes out with safe enough technology, great, we'll use it, but we don't have to develop that ourselves. >> Well then, maybe just to play devil's advocate here for a second, what about it's a Robo-Taxi-type technologies being applied in bounded areas within metropolitan areas where the rules-- >> That's where it will start. >> Could be more-- >> I think that's where it will start, but I think part of the problem is that we have, perhaps in part due to all of the media hype around autonomous vehicles, we've been misdirected to thinking about autonomous vehicles as a replacement for the car we drive to work every day and I think that's the wrong way to think about it. I think that autonomous vehicles are going to show up in the market as an extension of public transportation. Right, you know, I get off the train and there's an autonomous vehicle waiting to take me for the last couple of miles to my office. >> And those last couple of miles would be sort of a regulated space. >> Rudy: May well be. >> Where the AI is more than capable of functioning. >> Right, and that, you know, yes. And so it's better to think about autonomous vehicles as not being a revolutionary technology but much more of an evolutionary technology. And in fact, most of these technologies are showing up in so-called ADAS technologies which are designed to make driving your regular car safer, lane assist, keeping you a safe distance. >> Donald: Maybe just explain that word, ADAS, and what that means. >> So ADAS stands for automated driver-assistance systems. So one of the first was cruise control, right, everybody's familiar with cruise control. And so to some extent ADAS is just building on cruise control. In addition to maintaining a constant speed, you can now stay in the lane. In addition to maintaining a constant speed, it will now automatically slow down if you get too close to the car in front. And so you can see ADAS as, you know, collision avoidance and so forth, not full autonomy, still have to have a driver in the driver's seat, but evolving year by year until one year we wake up and, yep, my car will actually drive me all the way from home to work without me intervening. Right, it's going to happen in that way. >> So incremental improvements. >> Incremental improvement. >> To ADAS as opposed to kind of revolution of autonomy. >> An overnight sensation. >> Yeah, right, coming from nowhere. Okay, understood. Well then, let's pivot from that then, okay. So let's talk about the automotive industry as a whole and sort of your thoughts on how this is all going to play out. >> Yeah, so there are some very interesting dynamics playing out in the automotive industry. Firstly, as good news, as a result of all of this money and innovation in the automotive industry, Detroit's actually coming back. I go there once or twice a year and you can feel the economy coming back in Detroit, but it's not going to come back around, you know, bending sheet metal. And the challenge that the automotive companies have is so much of their infrastructure and expertise has been built on construction, building a car, production lines to bend the metal, install the engine, and the internal combustion engine itself. And by complete coincidence, to some extent, we've got this confluence of all of these autonomous technologies and electric vehicles happening at the same time. Electric vehicles are much easier to make than internal combustion engines. Far fewer parts. It's one of the reasons that China has spun up about 20 different electric vehicle companies recently. So I think that long term, my prediction is that the automobile industry will go the same way that the personal computer industry went. When the PC first, you know, it was born by IBM, or Apple in some sense before that. There were dozens of companies producing different PCs and it was very much, they were expensive products, and, you know, relatively unusual. As the industry matured, the supply chains matured, and it became apparent there were really only two companies that were making a lot of money out of the PC industry. The companies that developed the software, operating system, and the companies that developed the processor, and all of the manufacturing went over to, in the PC's case, in Taiwan, right? And I think that exactly the same thing is going to happen with the automotive industry. Tesla today still actually makes cars, but I don't see them long term being in the car business because they're really a technology company. It's the reason I don't think Apple is ever going to get into the car industry. They make fantastic margins selling computer products. The gross margin selling a car, it's miserable. It can be single digits or teens. That would completely tank Apple's blended gross margin. So my prediction for the industry is there will be a few small pockets of very profitable businesses, particularly around the operating system, by which I mean the intelligence or the AI intelligence, and then the processor, whether it's a Qualcomm processor or a Nvidia processor or an Intel processor. And as with the PC industry, most of the profit will go there and most of the manufacturing will end up getting outsourced because that's not the value-add, you know, bending metal and so forth. >> Interesting, well, so in the kind of compute market today, right, we have this notion of sort of cloud-native, right, okay, and that many of the companies that are developing apps as relying on cloud-native infrastructure have a kind of technology lead that's going to be hard for some of the legacy providers to actually catch up on. Now, other people say that that's not necessarily the case and et cetera, right? Can you make the same argument for the electric car market, that some of the electric-natives might have a kind of sustainable advantage here? >> I should've added, today the cloud infrastructure companies, cloud services, SaaS companies, in the PC world, you know, very profitable, and I can see a similar cloud services model developing for the automotive industry. However, other than Tesla, it's very difficult to change the automotive channel to support that. I'll give you one example. Everyone that owns a Tesla is very used to the idea that, sometimes on a daily basis, a new bunch of software, operating system software, is downloaded overnight to your vehicle. You wake up in the morning and some new feature's been turned on, right? Tesla can do that because they bypass the entire dealership channel that has a complete lock on the rest of the industry. So for example, if GM wants to do the same thing as Tesla and do sort of what's called over-the-air, OTA, updates, software updates, they can't do that because their contract with the dealership network states that if there is service to be done on the vehicle, the vehicle has to be brought back to the dealership, and the dealerships consider updating the software on the vehicle as service. So their contract with the dealers actually prevent them from doing something that basic. So it's not just a technology issue. The whole channel and way vehicles get sold is going to have to change. >> Interesting, so that's the advantage that some of the new generation of vehicle manufacturers-- >> I would say that Tesla has a five year lead, technology lead, because they, like Apple, are vertically integrated. They're doing everything from user interface, fit and function, all the way down to the semiconductor. They're developing their own semiconductors now. So they have become a fearsome competitor in the electronic vehicle space because they've been doing it for longer than the other major auto companies. They've figured out a lot of the, you know, tricks and techniques of how to extend mileage and so forth. And so they have a substantial lead in the industry at this point, despite the fact that over the next 12, 18 months, every automotive company is going to be coming out with their own flavor of electronic vehicle. >> So then it's more than just about having electric drivetrains, et cetera, right? It's about the whole suite of capabilities. >> It's a systems engineering challenge. >> Interesting, okay. All right, well Rudy, we're going to have to leave it there, okay, but I think everything you've told us is, it sounds like some good news for some of the Tesla stock holders at the moment. >> I think so. >> Okay, well. (laughs) We'll pass on making an opinion about that, but great conversation, thank you for your insights. Okay, this is Donald Klein, host of theCUBE, here with Rudy Burger, managing partner at Woodside Capital. >> Rudy: Great, thank you, Don. (upbeat music)

(upbeat music) >> Hi, and welcome to theCUBE, the leading source for insights into the world of technology and innovation. I'm your host Donald Klein, and today's topic is the market for autonomous vehicles and the ecosystem suppliers looking to tap into this brave new world of autonomous capabilities in our daily commute. To have this conversation I'm joined by Rudy Burger, managing partner at Woodside Capital. Rudy, welcome to the show. >> Thanks Don, it's great to be here. >> Great, so look, why don't we start off Rudy, why don't you tell us a little bit about Woodside Capital and your role there? >> Great, so I founded Woodside Capital about 20 years ago having started five different companies of my own, one of which I took public. We are a specialist M&A advisor. We work with so-called growth stage often venture-backed companies and help them find buyers that are usually much larger public companies. Our clients are usually US or European companies and we find buyers in the US, Europe, or Asia. >> Excellent, excellent, okay. And why don't you talk a little bit about your kind of specialty areas? >> So I focused my career, and certainly the work at Woodside Capital, on imaging technologies and as an enabling technology, and the products and markets that are enabled by imaging and increasingly computer vision. So nowadays that is autonomous vehicles, consumer technology, security surveillance, and digital health. So enabling technologies, the computer vision is the theme that binds those together. >> Okay, well, the thing that's on everybody's mind these days is autonomous vehicles, when are we going to get them? Very high profile for sure. Before the show we talking about the kind of two key ingredients to making this happen, the AI software which is kind of the brains of the operation and then also the sensors which enable all of the AI. So why don't we talk about the sensor world first, okay? Lot of discussion about there, so sort of does the brave new world of vehicles need lidar? Does it not need lidar? Are there other types of sensors coming along? What's your sense of that market and how it's looking for all of the different players in it? >> So, Don, I look at it from a sort of fairly basic standpoint. Humans have two very capable image sensors and a very powerful processor, and the degree to which the automotive manufacturers and so-called Robo-Taxi developers have decided it's necessary to sprinkle every sensor known to man, and I'm talking lidar, radar, ultrasound, thermal, and of course cameras, is to some extent a degree to which, you know, image sensors are not as good as our eyes today. Now, there are some areas in which we will probably always have technology as a help. For example, humans are not very good at seeing in the dark whereas a thermal technology can do that very well. But my overall belief is that it's never a good idea to bet against an incumbent technology, and in this case I'm talking about so-called CMOS image sensors which are the sensor that goes into pretty much every camera in the world now. It's never a good idea to bet against the incumbent technology being able to scale into a new market. Every time people have done that, they've been wrong. Back in the early days the debate was whether CMOS image sensors would ever be good enough to replace CCDs as the sensor technology, and of course now, you know, everything uses CMOS image sensors. In other markets there was a long period of time in which people were thinking that LCD panels would never be large enough to replace, you know, for television, for example, 50 inch and so forth. It was never going to happen, so we needed plasma TVs, we needed rear-projection TVs. But slowly but surely the incumbent technology, LCDs, expanded to that market. So my belief is that CMOS image sensors will evolve to a point at which they will replace the need for lidar in most applications. >> Interesting, so that's a very controversial statement, right? Because you've certainly seen a lot of emphasis on the development of new generation lidar capability. >> Over 100 lidar companies started over the last three, four years, and of course many of them will not be happy to hear me say that. There are two distinct markets and one is the so-called Robo-Taxi market, and the other is more of the consumer vehicle ADAS market, and I think we need to think about those separately because the economics behind both are very different. If you look at the Robo-Taxi market, those vehicles tend to be much more expensive and are relatively price-insensitive. So if they can improve safety a little bit by putting a lidar on there, you know, great, let's do it, multiple lidars because these vehicles will be in operation 24 by seven, and if each vehicle costs 200,000, $250,000, fine. When we talk about the mass market for automobiles, type of car that you and I might go down and buy, very different thing. And, you know, auto makers sweat the pennies, and so putting a one or $200 lidar in a vehicle, big decision. And to the extent that they can replace the need for that lidar with a much less expensive camera system, that's what they'll do. Bear in mind that Mobileye, which has been the biggest success story, acquired by Intel for $13.5 billion, second largest acquisition Intel ever made, they for the most part still run on one camera, forward-looking camera. That's it, no radar, no lidar, no thermal, one camera. So the clever use of image processing, computer vision, and one image sensor can do a great deal. >> Interesting, okay. Well, so I want to talk about the software in just a second, but just to kind of finish this point, so if you were advising a sensor company that's developing some next gen capabilities, whether lidar or other related technologies, is the point you're making here that there are certain segments of this industry which are going to be more attractive to your technology than others? >> Absolutely, yes. I mean, the first thing to recognize is that the automotive industry has never really been a particularly comfortable fit with the economics and timeline of venture capital. VCs need to invest and recoup and redeploy back to their LPs on an eight-year cycle. But the automotive industry moves quite slowly, perhaps Tesla are excepted, and what the first piece of advice I would give these companies is it's probably going to be three, four, five years before, even if you have the right technology, before that technology really starts generating any significant volume and revenue. So for many venture-backed companies, that's too long. So the first piece of advice is find pockets of revenue, right, beachheads if you will, where you can land your technology and start generating revenue before you get to the automotive market. And many of these lidar companies we just talked about are not going to last long enough to get to the automotive market because not only does the automotive market move slowly but the autonomous vehicle market keeps on getting pushed out to the right as the industry realizes that this is a big, hairy problem. And so I would say, what is it that your technology can do an order of magnitude better than any other technology? Focus on that and find some opportunities for revenue outside the automotive industry that will sustain the company on its way to the holy grail. >> Interesting, yeah, so find that alternative revenue source to get you to base camp, and then when the market's ready, climb that Everest to-- >> I've seen so many companies basically go out of business because they've set their sights on either the automotive market, and it's go for broke. We're not interested in, all these other things are distractions. You know, entrepreneurs don't have a plan B. Or this. We're going to get our technology into a smartphone, that's it. And there are possibly some other opportunities but it takes so long and it's so difficult to get your technology into a smartphone that they go out of business before they ever get to that point. >> Interesting, okay. So good advice for people looking to kind of apply their technology in this kind of a very difficult market, right, very complicated market. All right, well, then let's switch to the other side of it. So we were kind of talking about the key ingredients, right? Sensors but also AI and the software around that, okay, and there are some very big players developing the software. Tesla's had their Autonomy Day where they've showcased their technology. You've obviously got Google with their capabilities developing software. How do you make sense of this overall landscape because we do see a lot of smaller providers also trying to develop software here. >> So the first thing that I find fascinating about the automotive industry is that for the most part there is no software market. There's perhaps one exception of any scale, that's BlackBerry that sells the QNX software. They found a point within the entertainment console where they can license their software. But for all of the development and capital invested into automotive software, nobody is actually generating revenue, making a living, by licensing software. And one of the main reasons for that is that, you know, the automotive market, really since inception, has been a hardware business. This is a business of bending sheet metal, internal combustion engines, and software has really not played that big a role up until relatively recently. So even those companies that do have software technology have ended up selling it into the automotive supply chain as a piece of silicon, embedded on a piece of silicon, not as, you know, here's my software on a USB stick, right? I think that the whole software licensing model hasn't so far fit well, fit comfortably, with the automotive industry. And the other reason is that there's no standard platform. If I were to develop a piece of software, I can, in the PC industry, I can develop for Windows, I can develop for Mac, I can develop for an iPhone. There's no such thing in the automotive industry, and particularly in this new world of autonomous vehicles there is no standard platform. There are many different processors, Nvidia has staked an early claim there. And the reason that most of the companies developing autonomous vehicle technology have developed the so-called full-stack solution, everything from code running on the processor, integrated through the sensors and so forth, is for that reason, there is no standard platform. So each company has developed the whole solution for themselves, and there are many of them around here that have raised hundreds of millions of dollars, some cases billions of dollars, for that purpose. So there is, today, no software market for automotive in the same way that we think about it in other industries. >> Understood, understood. But in terms of the companies that are actually pushing the envelope on these kind of capabilities, right, so we're taking the best of AI, we're applying it to big data sets, and then hopefully being able to extract that to create capabilities for these vehicles, right? What's your sense of how far that's come along in-- >> Well, it's come a long way but, here I'm going to push the boat out a little bit. I don't believe that the so-called deep learning technology, which is the current state of the art for AI, it's the technology that has allowed computers to beat humans at chess, at Go, I don't think that that flavor of AI, that approach to AI, is ever going to get us to safe enough autonomous vehicles. And that's because it works extremely well in fairly well-bounded rules, rule-bounded games or any scenario like that, but can you imagine trying to teach your 16-year-old how to drive by showing them images of every situation that they might encounter, right? Impossible. It's an infinite, it's not a well-bounded set. And that's so difficult because we really haven't developed the technology to allow computers to learn, to have things like common sense, to infer, you know, well, this happened, so this is likely to happen. So I think we are going to need a whole new breakthrough in AI before we get to what is generally considered safe enough vehicles. >> Interesting, well then, maybe if we kind of apply your previous thought about sort of Robo-Taxis as maybe being the segment where you're going to see the most use of these newer sensor technologies. >> Rudy: Near term, yes. >> Exactly, what about maybe, is that sort of the same rules apply there for maybe the AI providers, that they're-- >> I think so and that's why they're all focused on that. I mean, from Uber to Waymo, they've all made the same calculation which is if you're running a fleet of vehicles, and so for example in Uber's case, the driver takes 80% of the fare and only 20% goes back to Uber, but if you can replace the driver with a computer, you can keep that vehicle on the road 24 by seven and you can keep 100% of the revenue. You don't need to pay the computer. So that's the calculus that they're all going through. But I think that many of them are making a fundamental mistake and I predicted recently that I think Uber, my prediction for 2020 is that Uber is going to divest its autonomous vehicle business and get back to the business that it should be focused on. Uber generates about $14 billion a year in gross revenue, so 20% of that, which is the piece that Uber keeps after the drivers take their 80, is what, 2.8 billion. Uber should be able to be an extremely profitable business on 2.8 billion of net revenue, but they're spending a huge chunk of money every year on R&D. Now, I would argue that Hertz and Avis have successful businesses. They're in the service, they're in the transportation business, but they didn't decide that they had to build their own cars in order to be in that business. My view, personal view, is that what Uber should be doing is saying, that's not our business, right? We are the world's best at managing this sort of peer-to-peer network crowdsourced transportation, if you will. And when some company, some Silicon Valley startup, comes out with safe enough technology, great, we'll use it, but we don't have to develop that ourselves. >> Well then, maybe just to play devil's advocate here for a second, what about it's a Robo-Taxi-type technologies being applied in bounded areas within metropolitan areas where the rules-- >> That's where it will start. >> Could be more-- >> I think that's where it will start, but I think part of the problem is that we have, perhaps in part due to all of the media hype around autonomous vehicles, we've been misdirected to thinking about autonomous vehicles as a replacement for the car we drive to work every day and I think that's the wrong way to think about it. I think that autonomous vehicles are going to show up in the market as an extension of public transportation. Right, you know, I get off the train and there's an autonomous vehicle waiting to take me for the last couple of miles to my office. >> And those last couple of miles would be sort of a regulated space. >> Rudy: May well be. >> Where the AI is more than capable of functioning. >> Right, and that, you know, yes. And so it's better to think about autonomous vehicles as not being a revolutionary technology but much more of an evolutionary technology. And in fact, most of these technologies are showing up in so-called ADAS technologies which are designed to make driving your regular car safer, lane assist, keeping you a safe distance. >> Donald: Maybe just explain that word, ADAS, and what that means. >> So ADAS stands for automated driver-assistance systems. So one of the first was cruise control, right, everybody's familiar with cruise control. And so to some extent ADAS is just building on cruise control. In addition to maintaining a constant speed, you can now stay in the lane. In addition to maintaining a constant speed, it will now automatically slow down if you get too close to the car in front. And so you can see ADAS as, you know, collision avoidance and so forth, not full autonomy, still have to have a driver in the driver's seat, but evolving year by year until one year we wake up and, yep, my car will actually drive me all the way from home to work without me intervening. Right, it's going to happen in that way. >> So incremental improvements. >> Incremental improvement. >> To ADAS as opposed to kind of revolution of autonomy. >> An overnight sensation. >> Yeah, right, coming from nowhere. Okay, understood. Well then, let's pivot from that then, okay. So let's talk about the automotive industry as a whole and sort of your thoughts on how this is all going to play out. >> Yeah, so there are some very interesting dynamics playing out in the automotive industry. Firstly, as good news, as a result of all of this money and innovation in the automotive industry, Detroit's actually coming back. I go there once or twice a year and you can feel the economy coming back in Detroit, but it's not going to come back around, you know, bending sheet metal. And the challenge that the automotive companies have is so much of their infrastructure and expertise has been built on construction, building a car, production lines to bend the metal, install the engine, and the internal combustion engine itself. And by complete coincidence, to some extent, we've got this confluence of all of these autonomous technologies and electric vehicles happening at the same time. Electric vehicles are much easier to make than internal combustion engines. Far fewer parts. It's one of the reasons that China has spun up about 20 different electric vehicle companies recently. So I think that long term, my prediction is that the automobile industry will go the same way that the personal computer industry went. When the PC first, you know, it was born by IBM, or Apple in some sense before that. There were dozens of companies producing different PCs and it was very much, they were expensive products, and, you know, relatively unusual. As the industry matured, the supply chains matured, and it became apparent there were really only two companies that were making a lot of money out of the PC industry. The companies that developed the software, operating system, and the companies that developed the processor, and all of the manufacturing went over to, in the PC's case, in Taiwan, right? And I think that exactly the same thing is going to happen with the automotive industry. Tesla today still actually makes cars, but I don't see them long term being in the car business because they're really a technology company. It's the reason I don't think Apple is ever going to get into the car industry. They make fantastic margins selling computer products. The gross margin selling a car, it's miserable. It can be single digits or teens. That would completely tank Apple's blended gross margin. So my prediction for the industry is there will be a few small pockets of very profitable businesses, particularly around the operating system, by which I mean the intelligence or the AI intelligence, and then the processor, whether it's a Qualcomm processor or a Nvidia processor or an Intel processor. And as with the PC industry, most of the profit will go there and most of the manufacturing will end up getting outsourced because that's not the value-add, you know, bending metal and so forth. >> Interesting, well, so in the kind of compute market today, right, we have this notion of sort of cloud-native, right, okay, and that many of the companies that are developing apps as relying on cloud-native infrastructure have a kind of technology lead that's going to be hard for some of the legacy providers to actually catch up on. Now, other people say that that's not necessarily the case and et cetera, right? Can you make the same argument for the electric car market, that some of the electric-natives might have a kind of sustainable advantage here? >> I should've added, today the cloud infrastructure companies, cloud services, SaaS companies, in the PC world, you know, very profitable, and I can see a similar cloud services model developing for the automotive industry. However, other than Tesla, it's very difficult to change the automotive channel to support that. I'll give you one example. Everyone that owns a Tesla is very used to the idea that, sometimes on a daily basis, a new bunch of software, operating system software, is downloaded overnight to your vehicle. You wake up in the morning and some new feature's been turned on, right? Tesla can do that because they bypass the entire dealership channel that has a complete lock on the rest of the industry. So for example, if GM wants to do the same thing as Tesla and do sort of what's called over-the-air, OTA, updates, software updates, they can't do that because their contract with the dealership network states that if there is service to be done on the vehicle, the vehicle has to be brought back to the dealership, and the dealerships consider updating the software on the vehicle as service. So their contract with the dealers actually prevent them from doing something that basic. So it's not just a technology issue. The whole channel and way vehicles get sold is going to have to change. >> Interesting, so that's the advantage that some of the new generation of vehicle manufacturers-- >> I would say that Tesla has a five year lead, technology lead, because they, like Apple, are vertically integrated. They're doing everything from user interface, fit and function, all the way down to the semiconductor. They're developing their own semiconductors now. So they have become a fearsome competitor in the electronic vehicle space because they've been doing it for longer than the other major auto companies. They've figured out a lot of the, you know, tricks and techniques of how to extend mileage and so forth. And so they have a substantial lead in the industry at this point, despite the fact that over the next 12, 18 months, every automotive company is going to be coming out with their own flavor of electronic vehicle. >> So then it's more than just about having electric drivetrains, et cetera, right? It's about the whole suite of capabilities. >> It's a systems engineering challenge. >> Interesting, okay. All right, well Rudy, we're going to have to leave it there, okay, but I think everything you've told us is, it sounds like some good news for some of the Tesla stock holders at the moment. >> I think so. >> Okay, well. (laughs) We'll pass on making an opinion about that, but great conversation, thank you for your insights. Okay, this is Donald Klein, host of theCUBE, here with Rudy Burger, managing partner at Woodside Capital. >> Rudy: Great, thank you, Don. (upbeat music)

live from Las Vegas it's the queue covering Dell technologies world 2019 brought to you by Dell technologies and it's ecosystem partners welcome back everyone to the cubes live coverage of Dell technologies world here in Sin City I'm your host Rebecca night along with my co-host Stu minimun we have Chadds a catch he is the SVP PKS and Deltek Alliance at pivotal thank you so much for coming back on the cube Rebekah it is my pleasure Stu as always this is a big anniversary actually this isn't he I'm glad you brought it up this is this is Mark's 10 years of the cube at Dell technologies world and you're a cube MVP I want to hear you break it down for us would listen down this milestone when when when you guys started doing this I'm not sure whether anyone knew whether there was gonna be a season two but you know I think at these events distilling down what's happening bring in people with diverse points of view you guys have always made it real shared the perspective of the ecosystem challenged us to keep it a no-spin zone which i think is a great formula yeah Chad thank you so much first of all you know one of the things we do come in opinionated but one of the things we want is we want guests with opinions and luckily you've always brought it we love having you on the program and boy have things changed a lot in the last 10 years so I want to get your view on the keynote so I mean Chad you and I go back way we we were colleagues back at EMC I remember when you were acquired into the company we worked on like I scuzzy stuff which nobody even talks anymore of my scuzzy storage networking the dark art of that stuff but VMware was something that you know it really was a lifter for both of our careers I think it was really interesting to see how central VMware is to the strategy that we saw how it fits into multi cloud I just got a note from Dave Volante said you know Pat Geller drew up on there talking about multi cloud and you know let's not think that Microsoft obviates the need for AWS Atos is the first the big cloud and absolutely VMware's working with them so I'd love to get your take on you know VMware and the multi cloud and VMware with delve as opposed to VMware with EMC there's a lot to unpack in that yeah we've got like an hour so the first thing that I think is interesting is that history and context gives perspective but ditch context and dick ditch history and if you think of the now and the market the customer no longer wants servers network storage they don't want virtualization they don't even want things like RDS and ec2 and we still want the emotion right you know the the reality is is that with every customer that I see they're looking for things that only the Giants in increasingly vertically integrated stacks can do so think about the whole keynote through that context right basically you saw Dell EMC and VMware more aligned than ever and again you and I have the history in the context of years of EMC VMware I remember the first time I did a vien the first time played with ESX 3.0 and virtual Center 100 and 200 and going is gonna change the universe but fast-forward to now people are like I want an easy button for the whole stack Dell EMC says this is the common building block VX rail my former baby is now grown up and it's the standardized way to deploy the VMware stack on Brentt Project I mention is moved out of a hypothetical into beta management of that lifecycle as a cloud service and you'll notice that Michael started it in the keynote kubernetes is central to that vision our efforts between pivotal and VMware in the kubernetes universe is singular the objective is to make that whole stack simple to deploy consume grow etc etc now Chad I needed a comment on one thing so I seem to remember back another project you worked on that was going to start as a managed server and that turned into Acadia which turned into VCE which turned into a product because the customer gave very clear feedback that most of them didn't want it so why is it is it different now what's different now what changed in a decade the customer wants the outcome in the historical like you know that's a Wayback Machine right so circa 2010 the way you built a private cloud was an assemblage of server network computes virtualization in separate components delivering that as an outcome as a managed service even for VCE CPS D etc etc there we did it amazingly for about 3,000 customers but it was held together with services and human that's not software what's adapted is that the software-defined data center is now much more mature and it's possible for us to literally roll in a rack of VX rails manage it via dimension do full lifecycle updates not via NRC em but via button click in a window that is necessary for that degree of simplification now if we had stopped there in the keynote we'd be missing the mark because basically the customers have said I want a common multi cloud hybrid cloud operating model with consistent control consistent infrastructure can consistent kubernetes consistent developer abstractions and I thought it was a pretty big deal to see Microsoft join what VMware's been doing with AWS and you know we were there at the Google announcement at Google next you know just a couple weeks back so I think that we're moving into a face to be a little opinionated here where customers wanting an outcome are going to look at Deltek Microsoft Amazon sometimes Google and go tell us how we bring ourselves to the digital future it's interesting because that means what things that people don't like which is vertically integrated stacks they don't like industry consolidation they don't like optionality being reduced but if you want an outcome frankly increasingly what's happening is consolidation at this layer and a blossoming ecosystem above it so so where where where will that bring us I mean I think I think you're absolutely right in you you started talking about how we're sort of putting aside history and perspective and now let's bring it back into the conversation yeah what does that mean I think I think that for human beings watching the era of doing cool things assembling things that run VMS even things that run kubernetes and containers is increasingly turning into an a realm where you have to let go so that you can do things that matter increasingly the ecosystems are hyper standardizing those stacks and delivering them as a service in a public cloud and on-premises our objective and I think it's something that only Deltek really is in a position to do is to do that in a way which is open multi-cloud and yet also deeply integrated and what I would say is again to anybody watching is if you're deep passion is in building cool things build cool things but on top of that stuff so chat great set up for the question I have kubernetes I've argued for a number of years is something that the average customer shouldn't need to worry about it's something that should be baked into the platform all the public clouds have it VMware has it your babies PKS today help help us reconcile the statement you were just making and what PKS because I know it's really cool tech and there's lots of pieces and lots of smart people work on it but so you know how does that fit so a stew again you and I go back aways do you remember you remember the state of virtualization circa 2006 sure you'd show up to the VM world and it would be filled with people deeply passionate at the time it was like three four thousand people we're gonna change the world with virtualization all of them were doing weird science projects very few of them could say and I'm running this in production to you know do bla and I'm making the hospital run better right but they'd be like look at how cool this is the technology matured a lot and if you look at the time frame 2010 which was vSphere for if my timing is right it was the first year where it was like kind of for reals right and people started to talk about hey I can do cool stuff kubernetes is currently in the 2006 of virtualization so I've been doing this now for a year we as del tech are now the number two contributor to kubernetes right after Google more than RedHat more than RedHat is that combining all the pieces we have basically drove and so hard towards this point because we think it's essential now you've got the help to your team as part of that that's a big that is a big part of the strategy right how do we make contributions for the native upstream community and lead that charge via be a good citizen of that ecosystem one two we will make PKS Enterprise PKS in a central PKS the best simplest curated way to make this work that said kubernetes has three major release over three months PKS 1.4 using one dot 13.5 came out last week 1.5 with beta support for Windows is just arriving and we did a beta last week three months from now there's gonna be another major release I'm doing a session that basically says and I'm the I'm a cheerleader I'm like a superfan this is currently like juggling flaming chainsaws right yeah it's it's like you were like what and I'm like yeah so the CNC F which is the ecosystem around kubernetes kubernetes on its own is just like a base component you need to have this and this and this and this has 647 things on the landscape landing page that means if you take five minutes per you would spend a week without sleep without eating like the Game of Thrones watching last night's no food no sleeping no bathroom breaks today Chad five minutes each today and you would get a chance to learn all of those but to really deeply understand what they do you can't do with that in five minutes that's six months of work people need that market to consolidate mature industrialize and we're doing it having having been part of the VX rail envy san ramp being part of the NSX ramp the vSphere ramp the converged infrastructure ramp what's happening with kubernetes and with peak s exceeds the ramp curves for all of those so if you're a customer and you're thinking about do I need this kubernetes thing the answer is yes we have 50 of the Fortune 500 customers now using peak s people are doing it for real but it's still early days now some people may go that's scary and I'm gonna take a timeout I wouldn't do that I would say that just like virtualization 2006 those people who were there at vmworld got a ton of value leveraged and learning and now it's like an industry standard we are going to make kubernetes part of the VMware software defined data center and you heard Pat and Michael talk about it so it sounds like it's going in the direction that you that you believe thumbs up thumbs up from Chad sockets you heard it here first thumbs up it's been it's been a really exciting year and this year we are gonna take that momentum and accelerate it to the moon and beyond but we can't wait to have you back at this table this time next year for Season eleven thank you so much for returning to the queue Rebecca thank you I'm Rebecca Knight first amendment we will have much more from the cubes live coverage of Dell technologies world here in Las Vegas coming up in just a little bit [Music]

>> From Tavern on the Green in Central Park, New York, it's theCUBE covering Veritas Solution Day. Brought to you by Veritas. >> Welcome to New York City, everybody. We're here in the heart of Central Park at the beautiful location, Tavern on the Green. You're watching theCUBE, the leader in live tech coverage. And this is our special coverage of the Veritas Solutions Day. The hashtag is VtasVision. Veritas Vision last year was a big tent customer event, several thousand customers at that event and Veritas decided this year to go out to the field. 20 of these solution days, very intimate events, couple hundred customers, keynote presentations from Veritas, breakout sessions, getting deep into the product but also talking strategy, and intimate conversations with executives, CxOs, CIOs, backup admins, and of course, New York City is one of those places where you get very advanced customers pushing the envelope, very demanding. I often joke they're as demanding as New York sports fans, and so they have high expectations. But they also have a lot of money, and so the vendor community loves to come to New York, they love to get intimate with these customers in New York, as do we at theCUBE. So we're going to be talking to customers today, we're going to be talking to executives of Veritas, some partners. So I want to talk a little bit about what's going on in the marketplace, in this backup and recovery space. It's transforming quite dramatically. For those of you who follow theCUBE, you know last year at VMworld, last two years, actually, data protection was one of the hottest topics at the event. Of course, multi-cloud, of course there was a lot of AI talk and containers and Kubernetes. But staid old backup, old, reliable data protection was one of the hottest topics. We're seeing VC money pour into this space. We're seeing upstarts like Cohesity and Rubrik trying to take aim at the incumbents like Veritas and Commvault, and IBM, and Dell EMC, so those traditional companies, those enterprise companies that have large install bases are trying to hold onto that install base and migrate their platforms to a modern software-defined platform, API-based, using containers, using microservices, building on top of the code that they've developed, simplifying the UI, and at the same time, allowing for an abstraction layer across clouds and multi-clouds. So what are the big drivers that are really pushing the trends, the megatrends of this space? Well, certainly digital transformation is one of them. The last 10 years of big data, people have gathered all this data, and now that data is in this place and people are now applying machine intelligence to that data. They're doing a lot of this work in the cloud. So digital transformation, data, big data, cloud, multi-cloud, simplification. People want a much simpler experience, so bringing the cloud experience to their data, wherever the data might live. Because of course, you get the three laws of cloud. You've got the law of physics, right? Physics says you can't just shove everything into the cloud. It just takes too long. If I have big bog of data, if I have a petabyte of data, you know how long that's going to take to put into the cloud? So I may not just move it in there unless I stick it on a Chevy truck and it cart it over on a bunch of tapes and nobody really wants to do that. So there's the law of physics. There's also the law of economics. It's very expensive to move that data. You need a lot of network bandwidth, so, you know, you might not necessarily put everything into the cloud, you might keep stuff on-prem. And of course, there's a law of the land. And the law of the land says, well, if I'm in country X, let's say Germany, that data can't leave that country. It's got to be physically proximate inside the boundaries, the borders of the country, by local law. So these three laws are something that was put forth to us by Pat Gelsinger in theCUBE at VMworld this year. We've evolved that thinking, but it's very true when we talk to customers about this. These are trends that are driving their decisions about cloud and multi-cloud and where to put it. We talked in theCUBE about the stat that the average enterprise has eight clouds. Well, we're a small enterprise and we have eight clouds, so I think that number's actually much, much higher, especially when you include SAS. So lots of data, lots of copies of data, so you need a way to abstract all that complexity and have a single place to protect your data. Now, a big part of this, digital transformation is driving more intense requirements on recovery point objectives and recovery time objectives, RPO and RTO, what do those words mean? Recovery point objective, think about... Ask a businessperson, how much data are you willing to lose? And they go, oh, what are you talking about? I don't want to lose any data. But if you think about it and you ask the next question, how much are you willing to spend so that you lose no data, and if they have to spend millions and millions of dollars to do that, they might relax that requirement a little bit. They might say, well, you know, if I lose 15 minutes of data in any given time and have to recreate it, not the end of the world. So that's what RPO is, is essentially the point in time that you go in to recover and how much data loss you're exposed to. And the way this works is you take, let's say, snapshots to simplify the equation, you push those offsite away from any potential disaster, and it's that gap between when you actually capture the data and when that disaster might happen that you're exposed. So to make that as close as zero as possible, that gap as close to zero as possible, is very, very expensive, so a lot of companies don't want to do that. At the same time, digital transformation's pushing them to get as close to zero as possible without breaking the bank. The other part of that equation is recovery time objective, how long it takes to get the application and the data back and running. And because of digital transformation, people want to make that virtually instantaneously. So because of digital transformation, people are re-architecting their data protection strategies to have near-instantaneous recovery. This all fits into the megatrend of cloud. People want it to be simpler, they want it to mimic the cloud-like experience, almost as if I'm on Amazon or I'm on Netflix, so simplifying the recovery process and the backup process is something that we're going to hear a lot more of. Automation is another big theme. People tend to automate through scripts. Well, scripts are fragile, scripts tend to break. When changes are made in software, scripts tend to have to be rewritten and maintained. And so it's a very high maintenance type of activity to do scripts, and over time, they just fade away, or don't, they stop working. So automation through API is very, very important, something that you're hearing much more, is much more thematic in this world of data protection. The other is getting more out of the corpus of data in my data protection infrastructure, because, let's face it, backup and recovery, it's like insurance. I hope I never need it, but if I do need it, it's very valuable at that point in time that I do need it. But it's an expense. It's not driving bottom-line revenue. It's not necessarily cutting cost. It is indirectly in the form of reducing the cost of downtime, but that's harder. That's kind of viewed oftentimes as a soft dollar benefit. So what you're hearing is a lot of the vendor community and the user community are talking about getting more out of the data that they have and out of the backup and recovery infrastructure by bringing analytics, and machine intelligence, or AI and machine learning to the equation. Studying analytics to identify anomalous behavior, maybe identifying security breaches, creating air gaps such that I can potentially thwart ransomware or other malware infections, analyzing the corpus of backup data because it holds all the company's corporate data, it's accessible. If you can analyze that data and look for anomalies, you might be able to thwart an attack. So getting more out of that data through analytics. Predictive maintenance is another example of data analytics that's driving some of these trends beyond just backup and recovery. And also governance. Governance and privacy are kind of, security and privacy are two sides of the same coin, so with GDPR, the General Data Protection Regulation that came out, that went into effect in terms of fines going into effect this past May, very, very onerous and expensive fines, people are using their data protection corpus and the analytics around that to reduce their risk and to better govern their data. So these are some of the big trends that we're seeing. So Veritas is a leader here, we're going to be covering this all day. Veritas and some of its other brethren that have been around for decades are getting attacked by a lot of the upstarts, but they got the advantage that the install vendors have the advantage of a large install base. The incumbent vendors have the advantage of a large install base. The upstarts have the advantage of they're starting with a clean sheet of paper. We're going to talk to customers and find out what are they thinking in terms of their backup approach. Industry data suggest that over half of the customers that you talk to are rethinking their backup strategies because of digital transformation. Well, we're going to talk to some customers. Are they thinking about sticking with Veritas or they thinking about migrating? Why or why not? What are some of the advantages and considerations there? So Veritas, a long, rich story going back to the '80s when the company was founded, was a hot IPO, really super hot company, got sold to Symantec for about 13.5 billion, and then Symantec spun it out to private equity several years ago in an eight billion dollar go-private sale, and subsequently, Veritas got off the 90-day shot clock. We heard this from companies like Dell where they didn't have to report and get abused by the street for either missing a number or having one little metric that was off. So they could write their own narrative. They could invest in R&D, they could have more patient capital. And so you saw this from the Carlisle group that took Veritas private and has been sort of this march toward a new platform, spending money on R&D, and now, really going to market very aggressively. Another thing you're going to hear about is partnerships, partnerships with AWS and some of the other cloud-providers. There's a partnership that's being announced with the flash storage company, Pure, today. So we're going to dig into some of that. So we'll be here all day, Tavern on the Green. You're watching theCUBE and we're here in New York City. Keep it right there, we'll be right back. I'm Dave Vellante, back shortly. (digitalized music)

>> Narrator: Live from Orlando, Florida, it's The Cube covering Grace Hopper's celebration of women in computing. Brought to you by SiliconANGLE Media. >> Welcome back to the Cube's coverage of the Grace Hopper conference here in Orlanda, Florida. I'm your host, Rebecca Knight. We're joined by Aubrey Blanch. She is the Head of Diversity at Atlassian. >> Yeah, thank you so much for having me. >> Well, thank you for coming on the program. >> Absolutely, it's great to be here. >> So, tell me a little bit more about what you do as the Head of Diversity at Atlassian. >> Yeah, so I was always tell people that my job is to make people really happy and to give them an equal opportunity to succeed? But what that actually means day-to-day is that I spend a lot of time looking at the data that tells me are we hiring the right people, are we hiring people equitably, do they love coming to work and are they having an impact? So, I, that means sometimes designing programs, sometimes doing focus groups, but always trying to think about how do we make sure that everyone has the thing that they need to be really successful at Atlassian and sort of fulfill our company mission which is to help unleash the potential of every teams and for us, you know, we, we unleash the potential in every team and we know that every team is diverse and so we know that it's just an imperative for us to look like the customers that we're serving because it means that we understand them and it means that we can help them do better work. And I know that you are really dedicated to the idea of including empirical science-- >> Yes. >> In, in what you do. >> Aubrey: Yes. >> Talk to me about some the, the most powerful studies, the most powerful research that you try to bring to your thought process in terms of hiring. >> Yeah, absolutely, so I'm a recovering social scientist by training so I get really excited about the idea that you can use research to make little tweaks to the way that you do things that changes outcomes in really big ways. So, one example. We know that women, on average, when they have the same contributions as their male colleagues, actually tend to rate themselves lower. Right? Same work and then they say, "No, that's not quite as good." And so, last year we made a change to our performance review process that helps get rid of problems that might be introduced by that. So, if you're a manager and you're reading two people's work and one person has given themselves a three and one's given them a four that might affect your rating. So, we actually changed it so that now managers right the review without seeing their direct reports review. Turns out it removes bias, it shortens the process, and it helps identify whether people have an agreement about what people's work is. And we found that that meant that everyone was getting a more equitable set of ratings and we could say, "Eh, we removed bias "and it made it easier for the business." And it meant that people were getting rewarded for the value that they were creating. >> And you're also, you're also big on data. >> Aubrey: Yes. >> And so you, you first of all have to collect the data. >> So what's kinds of-- >> Yeah. >> How are you collecting data and polling employees about whether or not they are happy? Absolutely, so first, you have to collect data about who people are and how they identify. So, things like gender, race, disability status. We collect that data. And then we survey people, right? Asking them not, are you happy, but have you grown in the last six months? You know, does your manager support you in doing those things? And you can sort of triangulate what a person's experience looks like that way. But you also look at bigger things. You look at things like promotion velocity. Or what is your attrition and retention rates? And those tell you a lot of things. You dig into exit surveys and you say, "What's the number one reason that people are leaving?" Let's fix it. >> Right. >> And the other piece of data that I get really excited about and something that's sort of Atlassian's thing, I guess, is that we actually report on the diversity of our work force at the team level. So, you can check it out. It's atlassian.com/diversity. But in addition to those corporate level statistics, we really think that the diversity on your teams matters because your teams are who you're engaging with day-to-day. And you get the value out of diversity because two different people come together. And so it doesn't actually matter if you have 30% women in your company if all the women are in HR and marketing and all the men are in engineering. What matters is each of those teams is diverse because it helps them build better. And so we think it's important to measure it that way. >> That is such a great point because I think that a lot of companies can bolster their diversity numbers. >> Aubrey: Yeah. >> And with women in the more traditionally female-oriented parts of the company. >> Absolutely. But that cut of data also helps drive bigger impact. So, I'll give you an example. When we cut our data at the team level, what we saw, and this was about a year ago, that about 13.5% of our technical employees were women but when we looked at all of our teams that were developing software, two thirds of them had a woman team member. And so from that insight we were able to say, well those women are probably isolated on their teams. And so they're likely lacking a sense of community and belonging and so instead of just investing in recruiting, we created a variety of programs that helped women collaborate across their teams. So, things as simple as a coffee dates program where women opt in and are assigned to another woman in their office to have coffee with every other week. Or something more structured like a peer-mentoring ring that's cross-functional. And what we found is that that actually helped drive retention for women in those rolls. So, while we're investing in recruiting, we're also making sure that we're keeping and growing the women that are already on our teams. >> So this is, this is incredible. These small tweaks as you started off saying-- >> Yeah. >> That are really changing the way you do business. >> Absolutely. >> What is you're, you're best advice to the rest of the tech industry where Atlassian, feels like you've figured out something here? >> Yeah, I think it's trust the data and know that there are no best practices or silver bullets. So, we've made incredible progress over the last few years so-- >> And you do, and you publish your numbers. >> Yes we do. >> As you said. >> Yeah, every year. We've improved our hiring of women in technical roles by 80% over the last two years and it's, we've honestly just adopted the same approach that our software teams use. Which is we test something, we see whether it works and then we iterate and improve it. >> Agile, right. >> Right. And so it's not about one training or one program, it's about re-thinking about how you engage with your people and how you respond to their experiences. Because they'll tell you what they want and need and it's about providing that. And I always tell people best practices are a starting point but they may or may not work for you. So, you need to be open minded to the idea that the first thing you try just might not work because your culture might be different or something like that. For us, we also like to think about diversity in a really broad way. So, my other piece of advice is think intersectionally, right? So when we say-- >> What does that mean? >> Yeah. >> How do you define that? >> So, it's a big, complicated word but it just means that we all have layers. So, I, for example, identify as a woman but I also identify as American and Hispanic and five feet tall and an HR person and all of us carry all of those identities around and what you, so you need to understand that women is a diverse group. But, when you do that, when you start talking about axes of diversity that are past gender, it turns out it turns what could be an us-versus-them conversation into something that's about we. Because maybe someone says, "Well, I don't identify as female "but this is the unique thing that I bring in." And suddenly you've created it where everyone has an incentive and has skin in the game to create inclusion and you will get greater gender equity out of that. So, it's a little bit counter-intuitive to start backwards in a way, or start complex and work towards simple but that's something that we've found has been incredibly helpful in galvanizing people to get involved and really changing the culture in a way that it's not a top down initiative or a bottom-up initiative, it's everyone moving in the same direction. >> Well, Aubrey, it sounds so common-sensical, of course, yes, yes. >> Yeah. >> But it's only obvious after you say it. >> Right, yeah, yes. >> And after you've tried it and tested and iterated on it. (laughs) >> So that would be my thing is, is whatever diversity matters to you because at Atlassian, for example, we're an Australian company and so international diversity is incredibly important, right? Where you come from. You know we, I always joke, you're more likely to hear three languages walking across the office than anything else and that's a really cool place to be but it means we've already gotten used to working in a diverse environment and now it's how do we just add additional aspects of diversity to our culture and to our teams? >> Right, and let's not fight that. >> Absolutely. >> 'Cause it's working. >> Right, and the other thing that I've found which is really exciting is as I've seen teams start to change their composition, you don't just hear really great things from those folks who come from under-represented groups. People from those majority groups say, "Wow, it's actually improving my experience at work," because they have access to more perspectives and people who have different experiences than them. >> So, it's firing different parts of their brains to-- >> Yeah. >> To-- >> It's just more interesting to do your job that way. >> Have better ideas, yeah. >> So, that's the other thing that's real important is this is a win-win-win solution, it's not a zero-sum game. >> Right. Well Aubrey, thanks so much for joining us. It's been a lot of fun talking to you. >> Absolutely. Thank you so much for having me. >> We will have more from the Cube's coverage of the Grace Hopper Conference just after this.