>> Narrator: theCUBE presents Ignite 22. Brought to you by Palo Alto Networks. >> Hey, welcome back to Las Vegas. Lisa Martin here with Dave Vellante. This is day two of theCUBE's coverage of Palo Alto Ignite 2022. Dave we're just talking about how many times we're in Vegas. And we were here two weeks ago with our guest who's back in Alumni. And it's a blur, right? >> It's true, I lost count. Luckily I'm not flying red eye tonight. So that's good. >> I'm impressed. >> Excited about that. >> Yeah >> I'm actually going to enjoy the, nightlife here for a period of time. And, you know, we were at re-Invent. >> Yeah. >> And what a difference. This is nice and relaxed. You have time. You're not getting bumped in the hallway. >> Right. >> A lot of time for learning. So it's been great show. >> It's been great. And one of the things that we've been talking about is the supply chain. Securing the modern software supply chain is really complicated. We've got an Alumni back with us, to talk about what Palo Alto is doing in that respect. Ankur Shah joins us. The SVP and GM of Cloud Security at Palo Alto Networks. Welcome back. >> Yeah, happy to be back. Good to see you again. Dave and Lisa. >> It's been two long weeks. >> Ankur: I know. It's been two weeks, yeah >> Dave: It's kind of crazy. I mean, ReInvent really was a blur. And it's like you had everything coming at you. And there was obviously a big chunk of security, but you. It was just so much to absorb. >> Yeah. >> Right? >> Yeah, and I couldn't get into any of the sessions versus at Ignite. I mean, you could, you could learn a lot. To your point Dave. And 70,000 people versus 3000 in change. Big difference. >> Dave: Yeah. >> Lisa: Huge difference. >> Yeah. >> Lisa: Huge difference. So we touched on the Cider acquisition. >> Ankur: Yeah. >> Which was announced the intent to acquire last month. Let's dig into a little bit more of that, and then some of the great things that had been announced. >> Ankur: Yeah. >> In the last couple of days. >> Oh, absolutely. So, this is something that we have been marinating for last nine months. Thinking about how best to secure supply chain. And this is software supply chain. The modern application software is fairly complex. You know, back in the days when I was a developer, it was a simple three tier application. Ship the code once a year, et cetera. But now with microservices, new architectures, Kubernetes Public Cloud, we talked about this. It's getting super complicated, and the customers are really worried about securing their entire supply chain. Which is nothing but the software pipeline. And so we started looking at a whole bunch of companies and Cider really stood out. I mean, they had, they were the innovators in this space. Very early days, we've seen supply chain attack. But there hasn't been a really good and strong solution in that space. And Cider just delivered that incredible team. Great technology, super excited about what that integration will look like. in the coming quarters. >> What do we need to know about them? I mean, I'll be honest with you, I wasn't familiar with Cider until I saw you guys made the announcement of the intent to acquire them. What, what should we know about them? Why Cider? What was it that attracted you to them? >> Ankur: Yeah, so, you know, we have a history of technology acquisitions as you know, over the last four years, just in the public cloud. We acquire over half a a dozen companies, small and large. And typically we are always looking for companies who have the next gen technology available. Technology that is more in tune with how application software is going to look like in future. So we're not always going after companies that are making you know, tens of hundreds of millions of dollars in a year and all. We're looking for the right tech. The future. And that's what we found in Cider. Like they have a really strong application security background. And AppSec just broadly speaking, supply chain is part of it. But application security, just broadly speaking, is right for disruption. You've got a lot of vendors, who have been around for like last two decades. Old school stuff, lots and lots of false positives. So we've been bolstering, beefing up our portfolio in the application security space. And Cider really fits right nicely into it. Because it can like I said, secure a lot of technology and tooling, that software developers use as part of their software supply chain. So, great founding team, great technology. It was a perfect fit. >> Talk about integration. We spoke with Nikesh yesterday, with Nir, with a whole bunch of folks. Lee this morning. BJ yesterday as well. And one of the things that seems to stick out at me. With all the shows that we do, is the focus that Palo Alto has on ensuring that it's making the right acquisitions. But that it's the integration, is really seems to be like leading part of the strategy. That seems to be a little bit of a differentiator to me. >> Yeah, it absolutely is. There are two ways to integrate a technology into an existing platform. And Prisma Cloud is a platform as you know. Code-to-cloud, CNAPP platform as we call it. One is just kind of slotted in, put the whole thing in a box. And that's basically making one plus one equal to two. We're looking for high leverage in integrations, whereby once that integration comes along. It makes the rest of the platform even better and superior. It makes that technology look even better. So that's why there's a lot of focus on ensuring that we're delivering the right type of integration, that delivers instant customer value. And that makes the overall platform even superior. So customers don't feel like hey, like there's just one more add-on, on top of the other thing. >> Lisa: Right, not a bolt on. >> So that's why there's a lot of focus on that. Getting the strategy nailed. Because the founding teams generally have a preconceived notion about how the world looks like. Then they understand how Prisma cloud and Palo Alto Networks think about it. And then, we sort of merge the two ideas, and build something that's incredible. So I am, we're spending a lot of time in integration. That honeymoon phase of like, let's high five acquisitions done, that's over. Now it's the grinding work of actually getting this right. And you know, getting hundreds and thousands of customers. >> Well I like how you don't have the private equity mentality. It's not about EBITDA and cashflow. We'll take care of that. >> Ankur: Yeah. >> You know, it's about getting that integration. Getting that flywheel effect, inside the platform. You know, we said one plus one equals, maybe even more than two. Can you explain Prisma Cloud Secrets Security? What is that all about? What do we need to know about that? >> Ankur: Absolutely. So, the developers, you know generally store some stuff in the code repo for their automation work to build application. And that thing, the API keys or as Secrets are stored in code repo. It shouldn't be. Or even if they are, they should be encrypted, or locked down and things of that nature. But, you know, the need for speed trumps everything else. Developers want to go fast. And sometimes they're like, okay well. I guess my application needs this particular, you know API access token or secret. I'm just going to stick it in the code. Now the challenge with that is that, if somebody gets hold of your code repo. Now not only is your code repo, which has all your sensitive data. Your code is the life and blood of a technology company. That's in trouble. But also those secrets and API access keys can be used to log into your cloud accounts. And there you may have sensitive customer data. Everything that you have as a technology company stored in that public cloud accounts. So that's the worry. It's usually the initial access for the kill chain. Because that's where the attacks start. Let me get the secret, let me get the API access key. And let me see what I can do in public cloud. So we are now giving customers the visibility into where the secrets are stored. More importantly, it just right there on developer's face. In the code repo as they're checking in the code. They say why, hey, there's a secret here. Are you sure you want to, you want to keep it like this, no? Okay, well then you can either encrypt it, or just get rid of it. So we're making, we're bringing security where the developers are in their code repo, et cetera. >> So I can see a lot of developers saying, yeah, go ahead, encrypt it. So I don't have to do anything else, you know, extra. It's almost, the analogy is a very small you know, version of this. Its like, use a password manager. You store all your passwords in your contacts on your phone, right? I mean, somebody gets a hold of your contacts, you're screwed. >> Ankur: That's exactly right. >> And so, but I could still see a lot of developers say, check in the box. Say, yeah just encrypt it, leave it there. But you're saying best practice is to not to do that, right? >> Yeah, usually you're not supposed to, you know, store all your secrets, et cetera in code repo to begin with. But if you do, you know, you use a key wall like technology to really encrypt it and store it in a secret manner, yeah. >> Dave: There's an old saying, bad user behavior trump's great security every time. >> Ankur: Every time. >> But this is an example where, we know you're going to have bad behavior. So we're going to protect the bad behavior. >> Yeah, and actually, sorry Lisa, just to that point. The bad user behavior trumps good security. The classic example, this happened three weeks ago. Three, four weeks ago, where Dropbox, one of the file sharing companies there. 120 plus code repos were exposed. And the way their attack started, was a simple social engineering attack. Bad user behavior. There was an email, hey, like your passwords are updated for your, you know, this code plugin. Can you enter the password? And boom, now you have access to the code repo. And now if you have secrets inside of it, now, you know all bets are off. >> Are there hard-coded secrets versus like, I mean, like I think like, like you were saying, Dave. Like usernames and passwords and tokens, versus like soft coded secrets. >> Ankur: It's, I think it, this is more so two forms of it, you know. The most primary one is what we call the API access keys. And this keys are used to access cloud accounts, workloads and things of that nature. But there are actually secret secrets. Could be database login passwords, et cetera. The application is using it to spin up databases. Now, you know, you have access to the data stores. Any other application, there's a login password, all of that stuff. So it's less about the user password, but more the application and databases and things of that nature. >> Dave: So again, and, again, everybody should be using password managers. But when you use a password manager, it's going to give you a long list of passwords, that are either been compromised or are weak. And you just go uh, okay. So can you help? How do you help customers identify what the high risk? You know, API, you know, access are versus those ones that they may not have to worry about. >> Ankur: Yeah, look. You know, secrets aside. Risk prioritization is one of the biggest topics that our customers have across the board, in cloud security. All the security vendors are really, really good at one thing, generating alerts. Everybody does it. They generate an alert. You know, your ring camera, if you've got one. I mean this pop up every day, like every minute rather. Well like can you prioritize it for me? What should I really look at it? So that's a number one thing. What Prisma Cloud does is, you know, contextualize it. What the real risk is? They can tell you like, hey, here's the kill chain. If this thing, you know, goes to public internet. These are the potential exposures that you have. So we provide a prioritized risk of critical alerts that customers have to take care of before they can start taking care of more hygiene type of stuff, right? So that's how we do it. Like we leverage a lot of technology. We apply a lot of context. We tell you like, hey, this code repo is not protected by multifactor authentication. And then there's a secret inside. Are you sure, you know, you don't want to fix it? So that's what we do. But it's a great question. Top of mind for all our customers. And that's how we think about it across the board. Versus generating just alerts all the time. >> Dave: Is the strategy, Because we all know phishing is the sort of most, you know obvious way to. It's the top way in which people get hacked. >> Ankur: Yeah. >> Is your strategy essentially to say. Okay we know that's going to happen, so we're going to try to protect it at the back end. How much of the, maybe it's an industry question. more so than just a Palo Alto specifically, How much emphasis is do you think the industry is taking or should be taking on stopping that, you know that those phishing attacks? Because if that's the number one problem you know, maybe that's where we should be starting. >> Yeah, it's a great question. It's typically the initial vector, for a lot of attacks to your point. But there is one thing that technology and AI cannot solve. Which is the user behavior, to your point. Like we can't get into the heads of the user. I mean, you can train them, you can do everything. You can't prevent somebody from clicking a button. Of course there's technology out there for email security that does that. But your point is, right, it's going to happen. Now what do you do? How do you protect your applications, your crown jewel? You know, whether it's in the cloud or it's in the code repo. So a lot of what we are trying to do in code security, or cloud security, or in general at Palo Alto Networks. is to protect those crown jewel. Because we can't prevent somebody from doing something. User behavior is hard to change. >> Dave: So it's almost like, okay, you left your front door open. Somebody's going to walk in, but oh, they walk into a vault. And they don't know where to go. And there's nowhere they can- >> Ankur: Yeah. >> You know, nothing they can take. They can't get to the silverware or the jewelry. >> I think that's it, yeah. >> What are some of the things, like as we look at, we're wrapping up calendar year '22 heading into '23. That customers can look to Palo Alto Networks to help them achieve? One of the things that we talked about with Nikesh and Niri yesterday, is consolidation. Like, and you guys just did a recent, survey. >> Ankur: Yeah. >> About the state of Cyber, and organizations on average have 366 apps in their environment. 31 security tools, 30 to 50 security tools. >> Ankur: Yeah. >> Consolidation is really key there. What are some of the things that you are excited about to deliver to customers where consolidation is concerned? >> Ankur: Yeah. >> Where software supply chain security is concerned in the next year? >> Yeah, absolutely. Look, there are over 3000 security vendors. And this can be, I mean you talked about average customer having 300. I was talking to a CSO, this was last year for one of the largest financial institution I go, "How many security tools do you have?" He got 120. I said, why? He goes, we have a no vendor left behind policy. >> Wow. >> It's crazy. >> Dave: What? >> Obviously he was joking, but it's crazy, right? Like that's how the CSO's are. >> Dave: I mean, he was kidding. >> Yeah. >> Dave: But recognized that. Wow. >> Yeah, and, this is the state the security industry is in. And our mission has been, and Lee and Nikesh and Niri talked about it. Is just platforms, will platforms take moonshots, things long term. And especially the, macro headwinds that we're seeing. We're hearing more and more from the customers that, look we're not going to buy point product. Then we got to buy another product that stitches it all together. We need platforms, whether it's for zero trust, Prisma SaaS, whether it's cloud. Prisma cloud or for your sock transformation. You know XIM and Cortex line of products. So I think you're going to see more and more of that in 2023. I'm confident in that. >> We heard from Lee today, the world record's 400. >> Yes. >> Yeah. >> That's crazy. >> He's going for it. He's got a ways to go. 120 He's got to... >> Maybe he wasn't, that guy wasn't kidding about his no vendor left behind policy. (laughing) Do you have Ankur, a favorite customer story that really articulates the value of what Palo Alto delivers and continues to. You know, 'cause one of the things that Nikesh said in his keynote was that you know, security's a data problem. Well every company these days, in every industry has to be a data company. But really what they need to be able to be is a secured data company. >> Ankur: Yeah. >> How are you guys enabling that? >> Oh, absolutely. Look, many customer examples come to mind, but speaking of data. You know, one of, some of our largest customers who are protecting their PCI workers where they have sensitive data. They're using for example, Prisma Cloud, to ensure that malicious attacks don't happen. And those workloads are used for credit card processing. They're processing tens of thousands of credit card transactions a second. And make sure that nobody gets hold of that. And that's why they have to make sure that nobody is. No attacker is trying to get hold of the sensitive data, to your point, So we have customers across financial services, media and entertainment technology company. Where we are helping them go as fast as possible in public cloud. Go through digital transformation, by securing their applications. >> Dave: What's the T-shirt say? I see code. >> Oh yeah. >> Dave: Secure from Code to Cloud. >> Lisa: Shift Happens. >> Shift Happens, Secrets from Code to Cloud. >> I love that. I was looking at that, going back to that, what's next in cyber survey? >> Ankur: Yeah. >> It said 74% of respondents, and I believe there was 1300 CIO's, CXO's that were surveyed globally. Where they said security is slowing down DevOps. Can customers look to Palo Alto Networks to help them? >> Ankur: Be enablers? >> Yes. >> Yeah, hundred percent. Look, the conversation over the last few years have changed now. Security used to say like, oh, I don't know about these people who are building applications. The DevOps is like security slowing down. I think there's an opportunity for companies like Palo Alto Networks, to build the bridge between the two. And the way we do it is make the securities easy, simple and not super intrusive. Where developers have to do a natural thing. And one part of it, and I talked about it earlier, is bring security where the developers are. In their code repo, in their IDE. Make it super simple. Don't make them do unnatural things. And it just, this is no different from changing the behavior of our kids. Right? Like you make them do unnatural things, they're not going to do it. But if it is part of their regular, you know, day-to-day operating procedures. I think they're going to be more open to change. Yeah. So I think it's possible. And Palo Alto has a huge responsibility to bridge the divide between the apps team, or the DevOps and the security organization. >> Lisa: Lots of great stuff to come. We thank you so much for coming back, two weeks. Only being on two weeks ago. We appreciate your insights, learning more information. It's great to see you at Palo Alto Ignite. And we'll have to have you back on. 'Cause we know that there's so much more to follow with respect to what you're doing. And shifting left, shift happens. >> Awesome. Lisa, Dave, thank you so much. It's been a pleasure. >> Lisa: Thank you so much. For Ankur Shah and Dave Vellante. I'm Lisa Martin. You're watching theCUBE. The leader in live and emerging tech coverage.

>>Good afternoon from the Venetian Expo, center, hall, whatever you wanna call it, in Las Vegas. Lisa Martin here. It's day four. I'm not sure what this place is called. Wait, >>What? >>Lisa Martin here with Dave Ante. This is the cube. This is day four of a ton of coverage that we've been delivering to you, which, you know, cause you've been watching since Monday night, Dave, we are almost at the end, we're almost at the show wrap. Excited to bring back, we've been talking about security, a lot about security. Excited to bring back a, an alumni to talk about that. But what's your final thoughts? >>Well, so just in, in, in the context of security, we've had just three in a row talking about cyber, which is like the most important topic. And I, and I love that we're having Palo Alto Networks on Palo Alto Networks is the gold standard in security. Talk to CISOs, they wanna work with them. And, and it was, it's interesting because I've been following them for a little bit now, watch them move to the cloud and a couple of little stumbling points. But I said at the time, they're gonna figure it out and, and come rocking back. And they have, and the company's just performing unbelievably well despite, you know, all the macro headwinds that we love to >>Talk about. So. Right. And we're gonna be unpacking all of that with one of our alumni. As I mentioned, Anker Shaw is with us, the SVP and GM of Palo Alto Networks. Anker, welcome back to the Cub. It's great to see you. It's been a while. >>It's good to be here after a couple years. Yeah, >>Yeah. I think three. >>Yeah, yeah, for sure. Yeah. Yeah. It's a bit of a blur after Covid. >>Everyone's saying that. Yeah. Are you surprised that there are still this many people on the show floor? Cuz I am. >>I am. Yeah. Look, I am not, this is my fourth, last year was probably one third or one fourth of this size. Yeah. But pre covid, this is what dream went looked like. And it's energizing, it's exciting. It's just good to be doing the good old things. So many people and yeah. Amazing technology and innovation. It's been incredible. >>Let's talk about innovation. I know you guys, Palo Alto Networks recently acquired cyber security. Talk to us a little bit about that. How is it gonna compliment Prisma? Give us all the scoop on that. >>Yeah, for sure. Look, some of the recent, the cybersecurity attacks that we have seen are related to supply chain, the colonial pipeline, many, many supply chain. And the reason for that is the modern software supply chain, not the physical supply chain, the one that AWS announced, but this is the software supply chain is really incredibly complicated, complicated developers that are building and shipping code faster than ever before. And the, the site acquisition at the center, the heart of that was securing the entire supply chain. White House came with a new initiative on supply chain security and SBO software bill of material. And we needed a technology, a company, and a set of people who can really deliver to that. And that's why we acquired that for supply chain security, otherwise known as cicd, security, c >>IDC security. Yeah. So how will that complement PRIs McCloud? >>Yeah, so look, if you look at our history lease over the last four years, we have been wanting to, our mission mission has been to build a single code to cloud platform. As you may know, there are over 3000 security vendors in the industry. And we said enough is enough. We need a platform player who can really deliver a unified cohesive platform solution for our customers because they're sick and tired of buying PI point product. So our mission has been to deliver that code to cloud platform supply chain security was a missing piece and we acquired them, it fits right really nicely into our portfolio of products and solution that customers have. And they'll have a single pin of glass with this. >>Yeah. So there's a lot going on. You've got, you've got an adversary that is incredibly capable. Yeah. These days and highly motivated and extremely sophisticated mentioned supply chain. It's caused a shift in, in CSO strategies, talking about the pandemic, of course we know work from home that changed things. You've mentioned public policy. Yeah. And, and so, and as well you have the cloud, cloud, you know, relatively new. I mean, it's not that new, but still. Yeah. But you've got the shared responsibility model and not, not only do you have the shared responsibility model, you have the shared responsibility across clouds and OnPrem. So yes, the cloud helps with security, but that the CISO has to worry about all these other things. The, the app dev team is being asked to shift left, you know, secure and they're not security pros. Yeah. And you know, kind audit is like the last line of defense. So I love this event, I love the cloud, but customers need help in making their lives simpler. Yeah. And the cloud in and of itself, because, you know, shared responsibility doesn't do that. Yeah. That's what Palo Alto and firms like yours come in. >>Absolutely. So look, Jim, this is a unable situation for a lot of the Cisco, simply because there are over 26 million developers, less than 3 million security professional. If you just look at all the announcement the AWS made, I bet you there were like probably over 2000 features. Yeah. I mean, they're shipping faster than ever before. Developers are moving really, really fast and just not enough security people to keep up with the velocity and the innovation. So you are right, while AWS will guarantee securing the infrastructure layer, but everything that is built on top of it, the new machine learning stuff, the new application, the new supply chain applications that are developed, that's the responsibility of the ciso. They stay up at night, they don't know what's going on because developers are bringing new services and new technology. And that's why, you know, we've always taken a platform approach where customers and the systems don't have to worry about it. >>What AWS new service they have, it's covered, it's secured. And that's why the adopters, McCloud and Palo Alto Networks, because regardless what developers bring, security is always there by their side. And so security teams need just a simple one click solution. They don't have to worry about it. They can sleep at night, keep the bad actors away. And, and that's, that's where Palo Alto Networks has been innovating in this area. AWS is one of our biggest partners and you know, we've integrated with, with a lot of their services. We launch about three integrations with their services. And we've been doing this historically for more and >>More. Are you still having conversations with the security folks? Or because security is a board level conversation, are your conversations going up a stack because this is a C-suite problem, this is a board level initiative? >>Absolutely. Look, you know, there was a time about four years ago, like the best we could do is director of security. Now it's just so CEO level conversation, board level conversation to your point, simply because I mean, if, if all your financial stuff is going to public cloud, all your healthcare data, all your supply chain data is going to public cloud, the board is asking very simple question, what are you doing to secure that? And to be honest, the question is simple. The answer's not because all the stuff that we talked about, too many applications, lots and lots of different services, different threat vectors and the bad actors, the bad guys are always a step ahead of the curve. And that's why this has become a board level conversation. They wanna make sure that things are secure from the get go before, you know, the enterprises go too deep into public cloud adoption. >>I mean there, there was shift topics a little bit. There was hope or kinda early this year that that cyber was somewhat insulated from the sort of macro press pressures. Nobody's safe. Even the cloud is sort of, you know, facing those, those headwinds people optimizing costs. But one thing when you talk to customers is, I always like to talk about that, that optiv graph. We've all seen it, right? And it's just this eye test of tools and it's a beautiful taxonomy, but there's just too many tools. So we're seeing a shift from point tools to platforms because obviously a platform play, and that's a way. So what are you seeing in the, in the field with customers trying to optimize their infrastructure costs with regard to consolidating to >>Platforms? Yeah. Look, you rightly pointed out one thing, the cybersecurity industry in general and Palo Alto networks, knock on wood, the stocks doing well. The macro headwinds hasn't impacted the security spend so far, right? Like time will tell, we'll, we'll see how things go. And one of the primary reason is that when you know the economy starts to slow down, the customers again want to invest in platforms. It's simple to deploy, simple to operationalize. They want a security partner of choice that knows that they, it's gonna be by them through the entire journey from code to cloud. And so that's why platform, especially times like these are more important than they've ever been before. You know, customers are investing in the, the, the product I lead at Palo Alto network called Prisma Cloud. It's in the cloud network application protection platform seen app space where once again, customers that investing in platform from quote to cloud and avoiding all the point products for sure. >>Yeah. Yeah. And you've seen it in, in Palo Alto's performance. I mean, not every cyber firm has is, is, >>You know, I know. Ouch. CrowdStrike Yeah. >>Was not. Well you saw that. I mean, and it was, and and you know, the large customers were continuing to spend, it was the small and mid-size businesses Yeah. That were, were were a little bit soft. Yeah. You know, it's a really, it's really, I mean, you see Okta now, you know, after they had some troubles announcing that, you know, their, their, their visibility's a little bit better. So it's, it's very hard to predict right now. And of course if TOMA Brava is buying you, then your stock price has been up and steady. That's, >>Yeah. Look, I think the key is to have a diversified portfolio of products. Four years ago before our CEO cash took over the reins of the company, we were a single product X firewall company. Right. And over time we have added XDR with the first one to introduce that recently launched x Im, you know, to, to make sure we build an NextGen team, cloud security is a completely net new investment, zero trust with access as workers started working remotely and they needed to make sure enterprises needed to make sure that they're accessing the applications securely. So we've added a lot of portfolio products over time. So you have to remain incredibly diversified, stay strong, because there will be stuff like remote work that slowed down. But if you've got other portfolio product like cloud security, while those secular tailwinds continue to grow, I mean, look how fast AWS is growing. 35, 40%, like $80 billion run rate. Crazy at that, that scale. So luckily we've got the portfolio of products to ensure that regardless of what the customer's journey is, macro headwinds are, we've got portfolio of solutions to help our customers. >>Talk a little bit about the AWS partnership. You talked about the run rate and I was reading a few days ago. You're right. It's an 82 billion arr, massive run rate. It's crazy. Well, what are, what is a Palo Alto Networks doing with aws and what's the value in it to help your customers on a secure digital transformation journey? >>Well, absolutely. We have been doing business with aws. We've been one of their security partners of choice for many years now. We have a presence in the marketplace where customers can through one click deploy the, the several Palo Alto Networks security solutions. So that's available. Like I said, we had launch partner to many, many new products and innovation that AWS comes up with. But always the day one partner, Adam was talking about some of those announcements and his keynote security data lake was one of those. And they were like a bunch of others related to compute and others. So we have been a partner for a long time, and look, AWS is an incredibly customer obsessed company. They've got their own security products. But if the customer says like, Hey, like I'd like to pick this from yours, but there's three other things from Palo Alto Networks or S MacCloud or whatever else that may be, they're open to it. And that's the great thing about AWS where it doesn't have to be wall garden open ecosystem, let the customer pick the best. >>And, and that's, I mean, there's, there's examples where AWS is directly competitive. I mean, my favorite example is Redshift and Snowflake. I mean those are directly competitive products, but, but Snowflake is an unbelievably great relationship with aws. They do cyber's, I think different, I mean, yeah, you got guard duty and you got some other stuff there. But generally speaking, the, correct me if I'm wrong, the e the ecosystem has more room to play on AWS than it may on some other clouds. >>A hundred percent. Yeah. Once again, you know, guard duty for examples, we've got a lot of customers who use guard duty and Prisma Cloud and other Palo Alto Networks products. And we also ingest the data from guard duty. So if customers want a single pane of glass, they can use the best of AWS in terms of guard duty threat detection, but leverage other technology suite from, you know, a platform provider like Palo Alto Networks. So you know, that that, you know, look, world is a complicated place. Some like blue, some like red, whatever that may be. But we believe in giving customers that choice, just like AWS customers want that. Not a >>Problem. And at least today they're not like directly, you know, in your space. Yeah. You know, and even if they were, you've got such a much mature stack. Absolutely. And my, my frankly Microsoft's different, right? I mean, you see, I mean even the analysts were saying that some of the CrowdStrike's troubles for, cuz Microsoft's got the good enough, right? So >>Yeah. Endpoint security. Yeah. And >>Yeah, for sure. So >>Do you have a favorite example of a customer where Palo Alto Networks has really helped them come in and, and enable that secure business transformation? Anything come to mind that you think really shines a light on Palo Alto Networks and what it's able to do? >>Yeah, look, we have customers across, and I'm gonna speak to public cloud in general, right? Like Palo Alto has over 60,000 customers. So we've been helping with that business transformation for years now. But because it's reinvented aws, the Prisma cloud product has been helping customers across different industry verticals. Some of the largest credit card processing companies, they can process transactions because we are running security on top of the workloads, the biggest financial services, biggest healthcare customers. They're able to put the patient health records in public cloud because Palo Alto Networks is helping them get there. So we are helping accelerated that digital journey. We've been an enabler. Security is often perceived as a blocker, but we have always treated our role as enabler. How can we get developers and enterprises to move as fast as possible? And like, my favorite thing is that, you know, moving fast and going digital is not a monopoly of just a tech company. Every company is gonna be a tech company Oh absolutely. To public cloud. Yes. And we want to help them get there. Yeah. >>So the other thing too, I mean, I'll just give you some data. I love data. I have a, ETR is our survey partner and I'm looking at Data 395. They do a survey every quarter, 1,250 respondents on this survey. 395 were Palo Alto customers, fortune 500 s and P 500, you know, big global 2000 companies as well. Some small companies. Single digit churn. Yeah. Okay. Yeah. Very, very low replacement >>Rates. Absolutely. >>And still high single digit new adoption. Yeah. Right. So you've got that tailwind going for you. Yeah, >>Right. It's, it's sticky because especially our, our main business firewall, once you deploy the firewall, we are inspecting all the network traffic. It's just so hard to rip and replace. Customers are getting value every second, every minute because we are thwarting attacks from public cloud. And look, we, we, we provide solutions not just product, we just don't leave the product and ask the customers to deploy it. We help them with deployment consumption of the product. And we've been really fortunate with that kind of gross dollar and netten rate for our customers. >>Now, before we wrap, I gotta tease, the cube is gonna be at Palo Alto Ignite. Yeah. In two weeks back here. I think we're at D mgm, right? We >>Were at D MGM December 13th and >>14th. So give us a little, show us a little leg if you would. What could we expect? >>Hey, look, I mean, a lot of exciting new things coming. Obviously I can't talk about it right now. The PR Inc is still not dry yet. But lots of, lots of new innovation across our three main businesses. Network security, public cloud, security, as well as XDR X. Im so stay tuned. You know, you'll, you'll see a lot of new exciting things coming up. >>Looking forward to it. >>We are looking forward to it. Last question on curf. You, if you had a billboard to place in New York Times Square. Yeah. You're gonna take over the the the Times Square Nasdaq. What does the billboard say about why organizations should be working with Palo Alto Networks? Yeah. To really embed security into their dna. Yeah. >>You know when Jim said Palo Alto Networks is the gold standard for security, I thought it was gonna steal it. I think it's pretty good gold standard for security. But I'm gonna go with our mission cyber security partner's choice. We want to be known as that and that's who we are. >>Beautifully said. Walker, thank you so much for joining David in the program. We really appreciate your insights, your time. We look forward to seeing you in a couple weeks back here in Vegas. >>Absolutely. Can't have enough of Vegas. Thank you. Lisa. >>Can't have in Vegas, >>I dunno about that. By this time of the year, I think we can have had enough of Vegas, but we're gonna be able to see you on the cubes coverage, which you could catch up. Palo Alto Networks show Ignite December, I believe 13th and 14th on the cube.net. We want to thank Anker Shaw for joining us. For Dave Ante, this is Lisa Martin. You're watching the Cube, the leader in live enterprise and emerging tech coverage.

(gentle music) >> Okay. We're back at AWS re:Invent. You're watching theCUBE's continuous coverage. This is day four. Think it's the first time, at re:Invent, we've done four days. This is our ninth year covering re:Invent. Tom Miller is here. He's the senior vice president of alliances. And he's joined by Ankur Jain, who's the global cloud practice lead at Merkle. Guys, good to see you. Thanks for coming on. >> Good to see you. Thank you. >> Thank you. >> Tom, tell us about Merkel, for those who might not be familiar with you. >> Yeah. So, Merkle is a customer experience management company that is under the dentsu umbrella. Dentsu is a global media agency. We represent one of the pillars, which is customer experience management. And they also have media and creative. And what Merkle does is provide that technology to help bring that creative and media together. >> So you're a tech company? >> Yes. >> Right? Okay. So there's some big tailwinds, changes, trends going on in the market. Obviously, the pandemic, the forced march to digital, there's regulation. What are some of the big waves that you guys are seeing, that you're trying to ride? >> So what we're seeing is, as a start, we've got a lot of existing databases with clients that are on-prem, that we manage today, within a SQL environment or so forth. And they need to move that to a cloud environment. To be more flexible, more agile, provide them with more data, be able to follow that customer experience that they want with their clients, that they're all realizing they need, to be in a digital environment. And so, that's a big push for us working with AWS and helping move our clients into that cloud environment. >> And you're relatively you new to the AWS world, right? Maybe you can talk about that, Ankur. >> Well, actually, as a partner, we may be new. But Merkle has been working with AWS for over five years. >> Dave Vellante: As a customer? >> As a customer. >> Yeah. >> So what we did was, last year, we formalized the relationship with AWS to be an advanced partner now. So we are part of the re:Stack program, basically, which is a pool of very select partners. And Merkel comes in with the specialization of marketing. So, as Tom said, you know, we are part of a dentsu umbrella. Our core focus is on customer experience transformation. And how we do that customer experience transformation is through digital transformation, data transformation. And that's where we see AWS being a very good partner to us, to modernize the solutions that Merkle can take to the market. >> So, I mean, your on-prem databases, there's probably a lot of diversity on-prem. (laughs) A lot of tech... When the cloud, you know, more agility, infinite resources. Do you have a tech stack? Are you more of an integrator? Right tool for the right job? Maybe you could describe your technical philosophy. >> Yeah, I could take that. What Tom just described... So let me give you some perspective on what these databases are. These databases are, essentially, Merkle helping big brands, Fortune 100, Fortune 500 brands to modernize their marketing ecosystem. Especially, MarTech ecosystem. So these databases, they house customer touchpoints, customer data from disparate sources. And they, basically, integrate that data in one central place. And then bolt-on analytics, data science, artificial intelligence, machine learning, on top of it. Helping them with those email campaigns or direct mail campaigns, social campaigns. So that's what these databases are all about. And these databases, currently, sit on-prem, on Merkle's own data center. And we have a huge opportunity to kind of take those databases and modernize them. Give all these AI, ML type of capabilities, advanced analytic capabilities, to our customers by using AWS as the platform to kind of migrate that. >> Dave Vellante: And you do that as a service? >> We do that as a service. >> Yes. >> Yes. >> Strategically, >> Yes. >> you're sort of transforming your business- >> Yes. >> to help your customers transform their business. >> Right. >> Right? Take away, it's classic. I mean, it's happening. This theme of, you know, AWS started with taking away the undifferentiated heavy lifting for infrastructure. Now you're seeing Nasdaq, Goldman Sachs, you guys in the media world, essentially building your own clouds, right? That's the strategy. >> Yes. >> Yes. >> Right? >> Absolutely. >> Superclouds, we call 'em. >> Superclouds, yeah. (Dave laughs) It's about helping our clients understand what is it they're trying to accomplish. And, for the most part, they're trying to understand the customer journey, where that customer is, how they're driving that experience with them, and understanding that experience through the journey. And doing that in the cloud makes it tremendously easier and more economical for 'em. >> Yeah, I was listening to the Snowflake earnings call from last night. And they were talking about, you know, a couple of big verticals, one being media. And all they keep talking about was direct-to-consumer, right? You're hearing that a lot. >> Ankur Jain: Yes. >> Media companies want to interact and build community directly. They don't want to necessarily, I mean, you don't want to go through a third-party anymore, if you don't have to. Technology's enabling that, right? Is that, kind of, the play here? >> Yes. Direct-to-consumer is a huge play. Companies which were traditionally brick-and-mortar-based, or relied on a supply chain of dealers and distributors, are now, basically, transforming themselves to be direct-to-consumer. They want to sell directly to the consumer. Personalization becomes a big theme, especially in D2C type of environment. Because, now, those customers are expecting brands to know what's their like, what's their dislike, which products, which services are they interested in. So that's all kind of advanced analytics, machine learning powered solutions. These are big data problems, that all these brands are kind of trying to solve. That's where Merkle is partnering with AWS, to bring all those technologies, and build those next generation solutions for our customers. >> So what kind of initiatives are you working on with AWS? >> So, there are, like, three, four areas that we are working very closely with AWS. Number one, I would say, think about our marketer's friend. You know, and they have a transformation like direct-to-consumer, omnichannel, e-commerce, these type of capabilities in mind. But they don't know where to start. What tools, what technologies will be part of that ecosystem. So that's where Merkle provides consulting services. To give them a roadmap, give them recommendations on how to structure these big, large strategic initiatives. That's number one, we are doing in partnership with AWS. To reach out to our joint customers and help them transform those ecosystems. Number two, as Tom mentioned, migrations. You know, helping chief data officers, chief technology officers, chief marketing officers modernize their environment, by migrating them to cloud. Number three, Merkle has a solution called Merkury, which is essentially all about customer identity. How do we identify a customer across multiple channels? We are modernizing all that solution, making that available on AWS Marketplace for customers to, actually, easily use that solution. And number four, I would say is, helping them set up data foundation. That's through intelligent marketing data lake. You know, leveraging AWS technologies like Glue, Redshift, and actually modernize their data platforms. And number four is more around clean rooms. Which is, bring on your first-party data, join it with Amazon data, to see how those customers are behaving when they are making a purchase on Amazon.com. Which gives insight to these brands, to reshape their marketing strategy to those customers. So those are, like, four, five focus areas. >> No, it's good. So, I was going to ask you about the data and the data strategy. Like, who owns the data? You're kind of alchemists, that... Your clients have first-party data. >> Ankur Jain: Yes. >> And then you might recommend bringing in other data sources. >> Yes. >> And then you're sort of creating this new cocktail. Who owns the data? >> Well, ultimately, client owns the data, because that's their customer's data. To your point on, we help them enrich that data by bringing in third-party data, which is what we call as... So Merkle has a service called DataSource, which is essentially a collection of data that we acquire about customers. Their likes, their dislikes, their buying power, their interests. So we monetize all that data. And the idea is, to take those data assets and make them available on AWS Data Exchange. So that it becomes very easy for brands to use their first-party data, take this third-party data from Merkle, and then, segment their customers much more intelligently. >> And the CMO is your sort of ideal customer profile? >> Yeah. CMO is our main customer profile. And we'll work with the chief data officer, or we'll work with the chief technology officer. We bridge both sides. We can go technology and marketing, and bring them both together. So you have a CMO who's trying to solve for some type of issue. And you have a chief technology officer who wants to improve their infrastructure. And we know how to bring them together into a conversation and help both parties get what they want. >> And I suppose the chief digital officer fits in there too? >> Tom Miller: Yeah, he fits in there too. >> CGO, chief dig. officer, CMO. Sometimes, they're one in the same. Other times, they're mixed. >> Yep. Yep. >> I've seen CIOs and CDOs together. >> Yes. >> Sure. >> It's all data. >> It's all data. (Dave laughs) >> Yeah. Some of the roles that come into play, as Tom mentioned, and you mentioned, CIO, CTO, chief information officer, chief technology officer, chief data officer, more from the IT side. And then we have the CMOs, chief digital officers, from the marketing side. So the secret sauce that Merkle brings to the table is that we know the language, what IT speaks and what business speaks. So when we talked about the business initiatives, like direct-to-consumer, omnichannel, e-commerce, those are more business-driven initiatives. That's where Merkle comes in, to kind of help them with our expertise over the last 30 years, on how to run these strategic initiatives. And then, at the same time, how do we translate those strategic initiatives into IT transformation? Because it does require a lot of IT transformation to happen underneath. That's where AWS also helps us. So we kind of span across both sides of the horizon. >> So you've got data, you've got tools, you've got software, you've got expertise, that now, you're making that available as a service. Is that right? >> That's right. Yes. >> Yes. >> How far are you into that journey, of saasfying your business? >> Well, the cloud journey started almost, I would say, five to seven years ago at Merkle. >> Yeah. Where you began leveraging the cloud? >> That's right. >> Dave Vellante: And then the light bulb went off and- >> So cloud, again, we use cloud in multiple aspects. From general computing perspective, leveraging, you know, fully managed services that AWS offers. So that's one aspect, which is to bring in data from disparate sources, house it, analyze it, and derive intelligence. The second piece, on the cloud side, is SaaS offering, Software as a Service offerings, like Adobe, Salesforce, and other CDP platforms. So Merkle covers a huge spectrum, when it comes to cloud. >> And you got a combination, you have a consulting business, and also- >> So Merkle has multiple service lines. Consulting business is one of them. Where we can help them on how to approach these transformational initiatives, and give them blueprints and roadmaps and strategy. Then we can also help them understand what the customer strategy should be, so that they can market very intelligently to their end customers. Then we have a technology business, which is all about leveraging cloud and advanced analytics. Then we have a data business, the data assets that I was talking about, that we monetize. We have promotions and loyalty, we have media. So we cover multiple services. >> Dave Vellante: Quite a portfolio. >> Yes. >> You mentioned analytics a couple of times, how do you tie that back to the sales function? I would imagine your clients are increasingly asking for analytics, so they can manage their dashboards and make sure they're above the line. How is that evolving? >> Yeah. So that's a very important line. Because, you know, data is data, right? You bring in the data, but what you do with the data, how you ask questions and how you derive intelligence from it, because that's the actionable part. So, few areas. I'll give you one or two examples on how those analytics kind of come into picture. Let's imagine a brand which is trying to sell a particular product or a particular service to a set of customers. Now, who those set of customers are, you know, where they should target this, who their target customers are, what their demographics are, that's all done through analytics. And what I gave you is a very simple example. There are so many advanced examples, you know, that come into artificial intelligence, machine learning, those type of aspects as well. So analytics definitely play a huge role on how these brands need to sell, and personalize the offerings that they want to offer to the customers. >> Used to be, really, pure art, right? It's really becoming- >> Not any more, it's all data driven companies. (Tom laughs) >> It's "Moneyball." >> Yes. Exactly. (Dave laughs) >> Tom Miller: Exactly. >> There's, maybe, still a little bit of art in there, right? It doesn't hurt to have a little creative flair, still. >> Yes. >> But you got to go with the data. >> And that's where the expertise comes in, right? That's where the experience comes in. And how you take that science and combine it with the art, to present it to a end customer, that's exactly, you know, it's a combination. >> And we also take the time to educate our clients on how we're doing it. So it's not done in a black box, so they can learn and grow themselves. Where they may end up developing their own group to handle it, as opposed to outsourcing with Merkle. >> You got to teach 'em how to fish. Last question. Where do you see this in two to three years? Where do you want to take? >> I think future is cloud, AWS being the market leader. I think AWS has a huge role to play. We are very excited to be partners with AWS, I think it's a match made in heaven. AWS sales in, majority of the sales happen in IT. Our focus is marketing. I think if we can bring both the worlds together, I think that will be a very powerful story for us to tell. >> Yeah, that's good news for AWS. If a little of your DNA could rub off on them, it'd be good. >> Tom Miller: Yeah. >> Guys, thanks so much for coming to theCUBE. >> Thanks, Dave. >> It was great to see you. >> Thank you, Dave. >> Appreciate it. >> All right. Thank you for watching everybody. This is Dave Vellante, for theCUBE. Day four, AWS re:Invent. We're theCUBE, the global leader in high-tech coverage. Be right back. (gentle music)

>>Okay, We're back at AWS Re. Invent. You're watching the >>cubes. Continuous coverage >>coverage. This is Day four. I think it's the first time it reinvent. We've done four days. This is our ninth year covering Reinvent. Tom Miller is here is the senior vice president of Alliances. And he's joined by Anchor Jane. Who's the global cloud? Practically practise lead at Merkel. Guys, good to see you. Thanks for coming on. Thank you, Tom. Tell us about Merkel. For those who might not be familiar with you. >>So Merkel is a customer experience management company. That is, um, under the Dentsu umbrella. Dense. Who is a global media agency? We represent one of the pillars which is global, our customer experience management. And they also have media and creative. And what Merkel does is provide that technology to help bring that creative and media together. They're a tech company. Yes. >>Okay, so there's some big big tail winds, changes, trends going on in the market. Obviously the pandemic. You know, the force marched to digital. Uh, there's regulation. What are some of the big waves that you guys are seeing that you're trying to ride? >>So what we're seeing is, uh we've got, uh, as a start. We've got a lot of existing databases with clients that are on Prem that we manage today within a sequel environment or so forth. And they need to move that to a cloud environment to be more flexible, more agile, provide them with more data to be able to follow that customer experience that they want with their clients, that they're all realising they need to be in a digital environment. And so that's a big push for us working with AWS and helping move our clients into that cloud environments. >>And you're relatively new to the ws world, right? Maybe you can talk >>about that anchor actually, as a partner. We may be new, but Merkel works with AWS has been working with AWS for over five years as a customer as a customer. So what we did was last year we formalise the relationship with us to be, uh, an advanced partner now. So we were part of the restock programme, basically which is a pool of very select partners. And Merkel comes in with the specialisation of marketing. So as Tom said, you know, we're part of, uh Dentsu umbrella are our core focuses on customer experience, transformation and how we do that Customer experience. Transformation is through digital transformation, data transformation. And that's where we see AWS being a very good partner to us to modernise the solutions that Martin can take to the market. >>So your on Prem databases is probably a lot of diversity on a lot of technical that when the cloud more agility, infinite resources do you have a tech stack? Are you more of an integrator? Right tool for the right job? Maybe you could describe >>your I can take that what time just described. So let me give you some perspective on what these databases are. These databases are essentially Markle, helping big brands 1400 Fortune 500 brands to organise their marketing ecosystem, especially Martek ecosystem. So these databases, they house customer touchpoints customer customer data from disparate sources, and they basically integrate that data in one central place and then bolt on analytics, data science, artificial intelligence, machine learning on top of it, helping them with those email campaigns or direct mail campaigns, social campaigns. So that's what these databases are all about, and and these databases currently set on Prem on Merkel's own data centre. And we have a huge opportunity to kind of take those databases and modernise them. Give all these ai ml type of capabilities advanced analytic capabilities to our customers by using AWS is the platform to kind of migrate. And you do that as a service. We do that as a service. >>Strategically, you're sort of transforming your business to help your customers transform their business right? Take away. It's it's classic. I mean, you really it's happening. This theme of, you know a W started with taking away the undifferentiated heavy lifting for infrastructure. Now you're seeing NASDAQ. Goldman Sachs. You guys in the media world essentially building your own clouds, right? That's the strategy. Yes, super clouds. We call >>them Super Cloud. Yeah, it's about helping our clients understand What is it they're trying to accomplish? And for the most part, they're trying to understand the customer journey where the customer is, how they're driving that experience with them and understanding that experience through the journey and doing that in the cloud makes it tremendously easier and more economical form. >>I was listening to the, uh, snowflake earnings call from last night and they were talking about, you know, a couple of big verticals, one being media and all. I keep talking about direct direct to consumer, right? You're hearing that a lot of media companies want to interact and build community directly. They don't want to necessarily. I mean, you don't want to go through a third party anymore if you don't have to, Technology is enabling that is that kind of the play here? >>Yes, Director Consumer is a huge player. Companies which were traditionally brick and mortar based or relied on a supply chain of dealers and distributors are now basically transforming themselves to be direct to consumer. They want to sell directly to the consumer. Personalisation comes becomes a big theme, especially indeed to see type of environment, because now those customers are expecting brands to know what's there like. What's their dislike? Which products which services are they interested in? So that's that's all kind of advanced analytics machine learning powered solutions. These are big data problems that all these brands are kind of trying to solve. That's where Merkel is partnering with AWS to bring all those technologies and and build those next generation solutions for access. So what kind >>of initiatives are you working >>on? So there are, like, 34 areas that we are working very closely with AWS number one. I would say Think about our marketers friend, you know, and they have a transformation like direct to consumer on the channel e commerce, these types of capabilities in mind. But they don't know where to start. What tools? What technologies will be part of that ecosystem. That's where Merkel provides consulting services to to give them a road map, give them recommendations on how to structure these big, large strategic initiatives. That's number one we are doing in partnership with AWS to reach out to our joint customers and help them transform those ecosystems. Number two as Tom mentioned migrations, helping chief data officers, chief technology officers, chief marketing officers modernise their environment by migrating them to cloud number three. Merkel has a solution called mercury, which is essentially all about customer identity. How do we identify a customer across multiple channels? We are Modernising all that solution of making that available on AWS marketplace for customers to actually easily use that solution. And number four, I would say, is helping them set up data foundation. That's through intelligent marketing Data Lake leveraging AWS technologies like blue, red shift and and actually modernise their data platforms. And number four is more around clean rooms, which is bring on your first party data. Join it with Amazon data to see how those customers are behaving when they are making a purchase on amazon dot com, which gives insights to these brands to reshape their marketing strategy to those customers. So those are like four or five focus areas. So I was >>gonna ask you about the data and the data strategy like, who owns the data? You're kind of alchemists that your clients have first party data and you might recommend bringing in other data sources. And you're sort of creating this new cocktail. Who owns the data? >>Well, ultimately, client also data because that that's their customers' data. Uh, to your point on, we helped them enrich that data by bringing in third party data, which is what we call is. So Merkel has a service called data source, which is essentially a collection of data that we acquire about customers. Their likes, their dislikes, their buying power, their interests so we monetise all that data. And the idea is to take those data assets and make them available on AWS data exchange so that it becomes very easy for brands to use their first party data. Take this third party data from Merkel and then, uh, segment their customers much more intelligently. >>And the CMO is your sort of ideal customer profile. >>Yeah, CMO is our main customer profile and we'll work with the chief data officer Will work with the chief technology officer. We kind of we bridge both sides. We can go technology and marketing and bring them both together. So you have a CMO who's trying to solve for some type of issue. And you have a chief technology officer who wants to improve their infrastructure. And we know how to bring them together into a conversation and help both parties get both get what they want. >>And I suppose the chief digital officer fits in there too. Yeah, he fits in their CDOs. Chief Digital officer CMO. Sometimes they're all they're one and the same. Other times they're mixed. I've seen see IOS and and CDOs together. Sure, you sort of. It's all data. It's all >>day. >>Yeah, some of the roles that come into play, as as Tom mentioned. And you mentioned C I o c T. O s chief information officer, chief technology officer, chief data officer, more from the side. And then we have the CMOS chief digital officers from the marketing side. So the secret sauce that Merkel brings to the table is that we know the language, what I t speaks and what business speaks. So when we talk about the business initiatives like direct to consumer Omni Channel E commerce, those are more business driven initiatives. That's where Merkel comes in to kind of help them with our expertise over the last 30 years on on how to run these strategic initiatives. And then at the same time, how do we translate translate those strategic initiatives into it transformation because it does require a lot of idea transformation to happen underneath. That's where AWS also helps us. So we kind of span across both sides of the horizon. >>So you got data. You've got tools, you've got software. You've got expertise that now you're making that available as a as a service. That's right. How far are you into that? journey of satisfying your business. >>Well, the cloud journey started almost, I would say, 5 to 7 years ago at Merkel, >>where you started, where you began leveraging the cloud. That's right. And then the light bulb went off >>the cloud again. We use clouds in multiple aspects, from general computing perspective, leveraging fully managed services that AWS offers. So that's one aspect, which is to bring in data from disparate sources, house it, analyse it and and derive intelligence. The second piece on the cloud side is, uh, SAS, offering software as a service offerings like Adobe Salesforce and other CDP platforms. So Merkel covers a huge spectrum. When it comes to cloud and you got >>a combination, you have a consulting business and also >>so Merkel has multiple service lines. Consulting business is one of them where we can help them on how to approach these transformational initiatives and give them blueprints and roadmaps and strategy. Then we can also help them understand what the customer strategy should be, so that they can market very intelligently to their end customers. Then we have a technology business, which is all about leveraging cloud and advanced analytics. Then we have data business that data assets that I was talking about, that we monetise. We have promotions and loyalty. We have media, so we recover multiple services portfolio. >>How do you mentioned analytics a couple times? How do you tie that? Back to the to the to the sales function. I would imagine your your clients are increasingly asking for analytics so they can manage their dashboards and and make sure they're above the line. How is that evolving? Yes, >>So that's a very important line because, you know, data is data, right? You bring in the data, but what you do with the data, how you know, how you ask questions and how you derive intelligence from it? Because that's the actionable part. So a few areas I'll give you one or two examples on how those analytics kind of come into picture. Let's imagine a brand which is trying to sell a particular product or a particular service to the to a set of customers Now who those set of customers are, You know where they should target this, who their target customers are, what the demographics are that's all done through and analytics and what I gave you is a very simple example. There are so many advanced examples, you know, that come into artificial intelligence machine learning those type of aspects as well. So analytics definitely play a huge role on how these brands need to sell and personalised the offerings that they're going to offer to. The customers >>used to be really pure art, right? It's really >>not anymore. It's all data driven. Moneyball. Moneyball? >>Yes, exactly. Exactly. Maybe still a little bit of hard in there, right? It doesn't hurt. It doesn't hurt to have a little creative flair still, but you've got to go with the data. >>That's where the expertise comes in, right? That's where the experience comes in and how you take that science and combine it with the art to present it to the end customer. That's exactly you know. It's a combination, >>and we also take the time to educate our clients on how we're doing it. So it's not done in a black box, so they can learn and grow themselves where they may end up developing their own group to handle it, as opposed to outsourcing with Merkel, >>teach them how to fish. Last question. Where do you see this in 2 to 3 years. Where do you want to take it? >>I think future is Cloud AWS being the market leader. I think aws has a huge role to play. Um, we are very excited to be partners with AWS. I think it's a match made in heaven. AWS cells in, uh, majority of the sales happen in our focus is marketing. I think if we can bring both the worlds together, I think that would be a very powerful story for us to be >>good news for AWS. They little your DNA can rub off on them would be good, guys. Thanks so much for coming to the Cube. Thank you. All right. Thank you for watching everybody. This is Dave Volonte for the Cube Day four aws re invent. Were the Cube the global leader in high tech coverage? Right back. Mhm. Mhm. Mhm.

>>LA from Las Vegas. It's the cube covering AWS reinvent 2019 brought to you by Amazon web services and along with its ecosystem partners. >>Welcome back to the queue from Las Vegas. We are live at AWS reinvent 19 Lisa Martin with John furrier. We've been having lots of great conversations. John, we're about to have another one cause we always love to talk about customer proof in the putting. Please welcome a couple of guests. We have Rafael, director of analytics and data management from triple a life. Welcome. Thanks for having me. Really appreciate it. Our pleasure. And from Burkle anchor Jane, the SVP of cloud platforms. Welcome. Thank you. Thank you so much. Pleasure to be here. So here we are in this, I can't see of people around us as, as growing exponential a by the hour here, but awkward. Let's start with you give her audience an understanding of Merkel, who you are and what you do. >>Yeah, absolutely. So Marco is a global performance marketing agency. We are part of a dental agent network and a, it's almost about 9,000 to 10,000 people worldwide. It's a global agency. What differentiates Merkel from rest of the other marketing agencies is our deep roots and data driven approach. We embrace technology. It's embedded in all our, all our solutions that we take to market. Um, and that's what we pride ourselves with. So, um, that's basically a high level pitch about Merkel. What differentiates us, my role, uh, I lead the cloud transformation for Merkel. Um, uh, basically think of my team as the think tanks who bring in the new technology, come up with a new way of rolling out solutions product I solutions, uh, disruptive solutions, which helps our clients and big fortune brands such as triple life insurance, uh, to transform their marketing ecosystem. >>So let's go ahead and dig. A lot of folks probably know AAA life, but, but Raphael, give us a little bit of an overview. This is a 50 year old organization. >>So we celebrate our 50th 50 year anniversary this year. Actually, we're founded in 1969. So everybody life insurance, we endeavor to be the provider of choice for a AAA member. Tell them to protect what matters most to them. And we offer a diverse set of insurance products across just about every channel. Um, and um, we engage with Merkel, uh, earlier, the, um, in 2018 actually to, to, uh, to build a nice solution that allows us to even better serve the needs of the members. Uh, my role, I am the, I lead our analytics and data management work. So helping us collect data and manage better and better leverage it to support the needs of members. >>So a trip, I can't even imagine the volumes of data that you're dealing with, but it's also, this is people's data, right? This is about insurance, life insurance, the volume of it. How have you, what were some of the things that you said? All right guys, we need to change how we're managing the data because we know there's probably a lot more business value, maybe new services that we can get our on it or eyes >>on it. >>So, so that was, that was it. So as an organization, uh, I want to underscore what you said. We make no compromises when it comes to the safety of our, of our members data. And we take every step possible to ensure that it is managed in a responsible and safe way. But we knew that on, on the platform that we had prior to this, we weren't, we weren't as italics. We wanted to be. We would find that threaten processes would take spans of weeks in order to operate or to run. And that just didn't allow us to provide the member experience that we wanted. So we built this new solution and this solution updates every day, right? There's no longer multi-week cycle times and tumbler processes happen in real time, which allows us to go to market with more accurate and more responsive programs to our members. >>Can you guys talk about the Amazon and AWS solution? How you guys using Amazon's at red shift? Can he says, you guys losing multiple databases, give us a peek into the Amazon services that you guys are taking advantage of that anchor. >>Yeah, please. Um, so basically when we were approached by AAA life to kind of come in and you know, present ourselves our credentials, one thing that differentiated there in that solution page was uh, bringing Amazon to the forefront because cloud, you know, one of the issue that Ravel and his team were facing were scalability aspect. You know, the performance was, was not up to the par, I believe you guys were um, on a two week cycle. That data was a definition every two weeks. And how can we turn that around and know can only be possible to, in our disruptive technologies that Amazon brings to the forefront. So what we built was basically it's a complete Amazon based cloud native architecture. Uh, we leveraged AWS with our chip as the data warehouse platform to integrate basically billions and billions of rows from a hundred plus sources that we are bringing in on a daily basis. >>In fact, actually some of the sources are the fresh on a real time basis. We are catching real time interactions of users on the website and then letting Kimberly the life make real time decisions on how we actually personalize their experience. So AWS, Redshift, you know, definitely the center's centerpiece. Then we are also leveraging a cloud native ELT technology extract load and transform technology called. It's a third party tool, but again, a very cloud native technology. So the whole solution leverage is Python to some extent. And then our veil can talk about AI and machine learning that how they are leveraging AWS ecosystem there. >>Yeah. So that was um, so, uh, I anchor said it right. One thing that differentiated Merkel was that cloud first approach, right? Uh, we looked at it what a, all of the analysts were saying. We went to all the key vendors in this space. We saw the, we saw the architecture is, and when Merkel walked in and presented that, um, that AWS architecture, it was great for me because if nausea immediately made sense, there was no wizardry around, I hope this database scales. I was confident that Redshift and Lambda and dynamo would this go to our use cases. So it became a lot more about are we solving the right business problem and less about do we have the right technologies. So in addition to what Ankur mentioned, we're leveraging our sort of living RNR studio, um, in AWS as well as top low frat for our machine learning models and for business intelligence. >>And more recently we've started transition from R to a Python as a practitioner on the keynote today. Slew a new thing, Sage maker studio, an IDE for machine learning framework. I mean this is like a common set. Like finally, I couldn't have been more excited right? That, that was my Superbowl moment. Um, I was, I was as I was, we were actually at dinner yesterday and I was mentioning Tonker, this is my wishlist, right? I want AWS to make a greater investment in that end user data scientists experience in auto ML and they knocked it out of the park. Everything they announced today, I was just, I was texting frat. Wow, this is amazing. I can't wait to go home. There's a lot of nuances to, and a lot of these announcements, auto ML for instance. Yeah. Really big deal the way they did it. >>And again, the ID who would've thought, I mean this is duh, why didn't we think about this sooner? Yeah. With auto ML that that focus on transparency. Right. And then I think about a year ago we went to market and we ended up not choosing any solutions because they hadn't solved for once you've got a model built, how do you effectively migrated from let's say an analyst who might not have the, the ML expertise to a data science team and the fact that AWS understood out of the gate that you need that transparent all for it. I'm really excited for that. What do you think the impacts are going to be more uptake on the data science side? What do you think the impact of this and the, so I think for, I think we're going to see, um, that a lot of our use cases are going to part a lot less effort to spin up. >>So we're going to see much more, much faster pilots. We're going to have a much clearer sense of is this worth it? Is this something we should continue to invest in and to me we should drive and I expect that a lot, much larger percentage of my team, the analysts are going to be involved in data and data science and machine learning. So I'm really excited about that. And also the ability to inquire, to integrate best practices into what we're doing out of the gate. Right? So software engineers figured out profiling, they figured out the bugging and these are things that machine learners are picking up. Now the fact that you're front and center is really excited. Superbowl moment. You can be like the new England Patriots, 17 straight AFC championship games. Boston. Gosh, I could resist. Uh, they're all Seattle. They're all Seattle here and Amazon. I don't even bring Seattle Patriots up here and Amazon, >>we are the ESPN of tech news that we have to get in as far as conversation. But I want to kind of talk a little bit, Raphael about the transformation because presumably in, in every industry, especially in insurance, there are so many born in the cloud companies that are a lot, they're a lot more agile and they are chasing what AAA life and your competitors and your peers are doing. What your S establishing with the help of anchor and Merkel, how does this allow you to actually take the data that you had, expand it, but also extract insights from maybe competitive advantages that you couldn't think about before? >>Yeah, so I think, uh, so as an organization, even though we're 50 years old, one of the things that drew me to the company and it's really exciting is it's unrelated to thrusting on its laurels, right? I think there's tremendous hunger and appetite within our executive group to better serve our members and to serve more members. And what this technology is allowed is the technology is not a limiting factor. It's an enabling factors. We're able to produce more models, more performant models, process more of IO data, build more features. Um, we've managed to do away with a lot of the, you know, if you take it and you look at it this way and squeeze it and maybe it'll work and systematize more aspects of our reporting and our campaign development and our model development and the observability, the visibility of just the ability to be agile and have our data be a partner to what we're trying to accomplish. That's been really great. >>You talked about the significant reduction in cycle times. If we go back up to the executive suite from a business differentiation perspective, is the senior leadership at AAA understanding what this cloud infrastructure is going to enable their business to achieve? >>Absolutely. So, so our successes here I think have been instrumental in encouraging our organization to continue to invest in cloud. And uh, we're an active, we're actively considering and discussing additional cloud initiatives, especially around the areas of machine learning and AI. >>And the auger question for you in terms of, of your expertise, in your experience as we look at how cloud is changing, John, you know, educate us on cloud cloud, Tuto, AI machine learning. What are, as, as these, as businesses, as industries have the opportunity to for next gen cloud, what are some of the next industries that you think are really prime to be completely transformed? >>Um, I'm in that are so many different business models. If you look around, one thing I would like to actually touch upon what we are seeing from Merkel standpoint is the digital transformation and how customers in today's world they are, you know, how brands are engaging with their customers and how customers are engaging with the brands. Especially that expectations customer is at the center stage here they are the ones who are driving the whole customer engagement journey, right? How all I am browsing a catalog of a particular brand on my cell phone and then I actually purchased right then and there and if I have an issue I can call them or I can go to social media and log a complaint. So that's whole multi channel, you know, aspect of this marketing ecosystem these days. I think cloud is the platform which is enabling that, right? >>This cannot happen without cloud. I'm going to look at, Raphael was just describing, you know, real time interaction, real time understanding the behavior of the customer in real time and engaging with them based on their need at that point of time. If you have technologies like Sage maker, if you have technologies like AWS Redship you have technologies like glue, Kinesis, which lets you bring in data from all these disparate sources and give you the ability to derive some insights from that data in that particular moment and then interact with the customer right then and there. That's exactly what we are talking about. And this can only happen through cloud so, so that's my 2 cents are where they are, what we from Merkel standpoint, we are looking into the market. That's what we are helping our brands through to >>client. I completely agree. I think that the change from capital and operation, right to no longer house to know these are all the sources and all the use cases and everything that needs to happen before you start the project and the ability to say, Hey, let's get going. Let's deliver value in the way that we've had and continue to have conversations and deliver new features, new stores, a new functionality, and at the same time, having AWS as a partner who's, who's building an incremental value. I think just last week I was really excited with the changes they've made to integrate Sage maker with their databases so you can score from the directly from the database. So it feels like all these things were coming together to allow us as a company to better off on push our aims and exciting time. >>It is exciting. Well guys, I wish we had more time, but we are out of time. Thank you Raphael and anchor for sharing with Merkel and AAA. Pleasure. All right. Take care. Or John furrier. I am Lisa Martin and you're watching the cube from Vegas re-invent 19 we'll be right back.

>> From New York City, it's theCUBE. Covering Automation Anywhere Imagine. Brought to you by Automation Anywhere. >> We're in midtown Manhattan at Automation Anywhere Imagine 2019. It's about 1,500 people talking about RPA which is part of the story but it's really a much broader story than RPA. It's about the ecosystem, it's about new ways to work, and really, RPA is an enabler but that's not the story in and of itself. It's really about helping people do their jobs better like a whole bunch of other tools that've come out over the years to help us out. We're excited to have a return guest who was here with us last year. He's Ankur Kothari, co-founder, another co-founder and chief revenue officer of Automation Anywhere. Great to see you again. >> Always good to see you, Jeff. >> So, it's been a year since last we spoke in June. >> We've been way less on ground, a lot on the flight. >> Yeah. >> Yeah. >> And, you brought in a bunch of money. You got a lot of resources really to support you now. So, how has that kind of changed? You know, you guys have grown a lot. You've put $500 million in the bank. How's that changing what you're working on now? >> Well, we are deploying that capital in three major ways. One is global expansion. We have now grown into, we have offices now in more than 30, 35 countries, 30 plus countries. So we are getting closer to all our customers worldwide in all top 30 economies and major business hubs where we are now we have opened offices, so, that's one. We are using this capital to build our ecosystem with our partners and all the developers. And, obviously we have invested a lot in our product. Taking the product stack more and more broader which allows us to automate any process that can be automated. >> Yeah, I mean, it's a great resource that you have at your disposal now. And Mihir talked about a lot of kind of higher level topics which I found really good in the keynote, really reframing RPA and personal digital assistance, if you will, around it's just another tool to help people get their job better. And he had some ridiculously sad stats about how much time that people are being asked to do robotic tasks which they really shouldn't be doing those tasks. >> Yes. >> There's much higher value stuff. It's not really rip-and-replace, it's really augment and help people do better. >> Augmenting, yes, yes, absolutely, generally most of these journeys start with this goal of productivity and rightly so. There's nothing wrong with that but as you scale in this journey and you start working, as you onboard more digital workers, digital colleagues as we like to call it, you find that the conversation in your organization changes from productivity to progress because that's what any technological transformation is about. It's not just about productivity, it's truly about progressing your team, your company, your industry, your customers forward. >> Right. >> So, that's what you face. And the second big prize on that front is it allows you to make work human. The moment you start automating every process that can be automated, we start using computers what they were designed for, to process things and not just to be used as a system of records. >> Right. >> So, we can do what we are good at. Solving complex problems using our creativity and empathy. >> Right, one of the things I thought was really interesting was the launch of the community addition, which is free. Free for small businesses, free for developers. I can't remember if there's an academic component-- >> Yes. >> Or not, but, you know, you're the guy who's puttin' money in the cash register. I'm sure there were some interesting conversations about having a free community edition. I wonder if you can share some insight 'cause, you know, that's taking money out of the bank, but obviously there's a much larger strategic goal. >> There's a strategic goal. The problem that we are falling in love with is that what would it take for us to accelerate the journey of every company to become a digital enterprise? How do we share in this new bot economy? And, in order to do that, we have to have every person participate in this whole phenomenon. An idea as big as this can not be one company or a few individuals' ideas. So, we have opened up that whole thing for everyone to participate. The community edition allows students, developers, small businesses, everyone to download. They go to our Automation Anywhere University and they can get freely trained and certified. And they can work with a bot. And they can build a bot and form their own opinion. >> Right. >> And have their own point of view. And the belief behind that is that a good idea can come from anywhere or anyone. And those ideas, once they use our product, they can monetize it in our marketplace which is the Bot Store. >> Right. >> So, that it allows everyone to form an opinion, and contribute to this new bot economy. >> It's pretty interesting. One of the topics Mihir touched on in the keynote was that we often think of, you know, kind of applying new technology to today's world, but we often miss, you know, as he said, that now is not the station, it's the train, and it's moving. And by opening it up to developers now, as you said, you're expanding the width, the breadth, and the potential applications of your technology to problems that you guys have never even thought about before. >> Exactly, that's the real thing. We are automating processes that we are doing now but generally it's about automating what we have not even seen. >> Right. >> These processes were designed for people to do. How would a process look when bots are performing there? I live in Silicon Valley and pretty much a computer science guy working on cutting edge. If you asked me 10 years ago would I let any of my family member live in a stranger's house? I would say, no way. Airbnb is one of the largest hotel chains in the world right now. >> Right, right. >> What that tells you is that human brain mind thinks linearly unless you give them something that allows humans to think exponentially. >> Right >> And that's the whole idea of beauty of technology. It allows us to think exponentially, and once our brain stretch there, then it's not possible to go back. >> Well, the other thing I think is really smart on your play is the competition for developers' attention, right? The developers these days have a lot of power and they can choose of a myriad of technologies in which to apply themselves. So, by having this community edition and opening it up is one part, but the other piece that I think is interesting is the whole bot economy. And I think you opened up the store last time we were here last year. >> Yes. >> Now you're putting money behind it so people can sell. In fact, we had a customer on earlier who's developing some stuff but they can augment that investment by actually selling those bots into this store. >> On the Bot Store, yeah. >> So, I wonder if you can talk a little bit more about how that is evolving? Is it kind of matching your vision? Has it accelerated past your vision? >> It is accelerating much faster than what we imagined first. When we one year ago we launched our marketplace, that is Bot Store. We opened up our University for everyone to get freely trained online. Then we started our community online, which is eight people. And with this community edition, everyone is now participating in it. What that is doing is we believe that more, the one thing that all developers want, is to contribute. Their work to be used by others. >> Right. >> And then, in a Bot Store, it allows them to even monetize it. It allows them to productize it so that personal satisfaction of solving a problem is what the developers get. And such new, creative ideas we are getting once we did that. Yesterday we had Bot Games and more than 250 to 300 developers participated in different games. And they were building these bots on fly, and they were competing. And we believe that when we bring all these people together and we give them a problem, genius comes out. >> Right. >> And it has been true. >> (laughs) So the ecosystem is huge and that's part of why you have your own show. And we go to a lot of shows. We were at Google Cloud a couple weeks ago. So, there's really two components of the ecosystem, traditional ecosystem. You've got the devs we talked about. There's the system integrators and you've got them all here in force. And they don't come out unless they really see a big opportunity. >> Yes. >> And the other part is the ISVs, right? To add all these different components. So, how is that evolving? Where do you see it going over the next year or two? >> It's interesting, you saw today that there was IBM, Microsoft, and Oracle all went on stage with software partnerships, you know Workday. So, we are forming large partnerships with software and how our product works with theirs, and the digital workers are part of that whole equation. And all our service providers and SIs and advisories that've been on this journey with us for the last five to six years and they are ramping up their entire practices to get their customers to become a digital enterprise. So, you see these two different worlds coming together and all the three worlds are working together for the customer to become a digital enterprise. >> Right. >> And, that's the best part. The digital native companies like Amazon, Airbnb, they have got this right. But what about the companies who have been there for 50 years, 100 years? How do they become digital? >> Right. >> And that's a more interesting problem. If you look at the software, and all the service partners and we are working together to solve that problem. So, it's a very interesting mix, an interesting time. And add to that this whole bot economy of developers bringing all these new digital workers. We are seeing the consumption of bot, growing in an exponential way. We are growing multi-force in few months. It's been a great, great ride. >> Right, well, I want to close on that in the last question 'cause you are one of the co-founders. I think there was four founders, if I'm correct. >> Yes. >> And you guys did it a very different way. You basically funded it the best way to fund a company, which is with revenue. >> Yes. >> And customer funded and you didn't go out and get outside money and now you've got this huge round which is actually an A round. >> Yes, it's a... >> So, how does that change the game? I mean, it puts you in a very good spot 'cause you don't have to take that money 'cause you were operating fine. But how does it, from a co-founder point of view, change the trajectory of your journey? >> There is obviously a value that that kind of capital brings because you can grow asymmetrically as well. >> Right, right. >> But the real value, for me, is the five investors who are such tier A, top-tier investors, who are the right partners we have got on this journey. If you think about Goldman Sachs, and NEA, and SoftBank, and General Atlantic which is one of larger growth-- >> Pretty good roster. >> Right. So you get that expertise and you get those partnerships that allows you to think exponentially and grow very fast. So, that's the real value for me in addition to the capital. >> Well, Ankur, thanks for sharing your journey with us. It's really been fun to watch and we're just at another inflection point I think. >> Always great to see you, and again next year. We ought to do this every year. >> All right, very good. >> Bigger and bigger. >> Absolutely, thanks again. >> Thanks a lot. >> He's Ankur, I'm Jeff, you're watching theCUBE. We're at Automation Anywhere in midtown Manhattan. Thanks for watching, we'll see you next time. (upbeat electronic music)

>> Live, from Las Vegas, it's theCUBE, covering AWS re:Invent, 2018 brought to you by Amazon Web Services, Intel, and their ecosystem partners. >> Well, good morning. Welcome back, or good afternoon for that matter, if you're watching out on the East Coast. Good to have you have here on theCUBE as we continue our coverage here in Las Vegas. We're at the Sands Expo, Hall D to be exact, one of seven sites that are hosting the AWS re:Invent John Wallace here with Justin Warren. We're now joined by Ankur Shah, who is the vice president of Products, a public cloud security, Palo Alto Networks, and, Ankur, good to see you this morning. >> Yeah, happy to be here. >> Thank you for being with us. And Richard Wise, who is the cloud security engineer, or a cloud security engineer at Robert Half. Good morning to you, Richard. >> Good morning. >> Well, first off, let's tell us about Robert Half. So, you're a recruiting firm in a partnership with Palo Alto, but fill in a few more blanks for folks at home who might not know exactly what you do. >> Sure, we're a staffing and recruiting firm. We have offices worldwide. We have roughly 15,000 full-time employees. We also have many, many temporary employees, and, of course, we do recruiting. Many people I've met here at the conference, in fact, got their first job or one job in the past through Robert Half. And we also-- >> That's makes you a really popular guy-- >> Yes. when the show closes. >> And we also have Protiviti, our prestigious consulting arm. >> Okay, so now, about your partnership. How did you find Palo Alto, or how did Palo Alto find you? And talk about maybe that relationship, how it's developed and where it stands today. What are they doing for you? >> Sure, well, we found Palo Alto about two years ago. We're about seven years into our cloud journey, but it became very clear at a point in time that we needed to get a better handle on how we were managing and securing it. We were doing all the right things but we didn't have the visibility we needed, so we brought in Evident to do that. Also, compliance is very important to us, and the tools allowed us to ensure that we were conforming to all of the compliance standards that we needed to. >> So, maybe Ankur, you can get us in here. Explain how did this partnership get started? >> Yeah, so Robert Half is kind of prototypical customer for us at Palo Alto Networks. Customers moving to cloud. AWS is obviously one of the biggest clouds, so all our customers are migrating, a lot of their, you know, shutting down their data centers, and moving the work loads and applications to the cloud, but as they move to the cloud, they want to make sure that they have the visibility and the security controls to make sure that they are not in the news. So, that's how the partnership started. A lot of customers, just like Robert Half, starts with kind of, you know, I'd like to get a visibility into what's happening in my cloud environment, detect advance data breeches, like cryptojacking, stolen access keys, things of that nature, so that's how we kind of started this partnership. We've been kind of helping them kind of move more and more applications and more and more workloads in their AWS environments, and it's been a really amazing partnership. We've gotten some amazing feedback from them that has helped mature the product over the years. >> What's one of the more surprising things that you've noticed as part of this journey. What's something that you didn't realize that this was going to be a benefit to this partnership, and then, once you actually had Palo Alto come in there, it's like, oh wow, this is amazing. >> Well, there were a couple of things. First off, their RQL, the RedLock Query Language, is very powerful and flexible, and let's us take our compliance and security to the next level, but was really impressed when we first started talking to RedLock and Palo Alto, even before we had purchased the product, we saw some opportunities for product improvements, suggested them, and before we purchased it, within a couple of weeks, they were there. >> Wow. >> Yeah. >> That's pretty fast of all those cycles. I mean, that's what we're here for is rapid innovation. They're trying to change things at the speed of cloud. So, how do you do that safely and securely? Maybe you can tell us how does Palo Alto help do this rapid innovation but still keep everything really secure. >> Yeah, so our DNAs, obviously, network security is where the company started. Over a year now, the company has doubled down on public cloud security, and a lot of emphasis on, sort of, securing customers' cloud environment, helping a lot of customers migrate their applications into the cloud, and from a security standpoint, we look at it from different angles. One is kind of the basic configuration management aspects, making sure that customers don't leave open s3 buckets, permissive security groups, things of that nature. Above and beyond that, we also perform network analytics, so things like triple jacking, data exploration attempts. The platform is able to detect those kinds of advanced threats. Privileged activity monitoring, and anomaly detection is another thing we do, and last but not the least, host monitoring and host security aspects. That's something we do really, really well in the cloud as well, so when you combine all of that stuff, gives customers 360 visibility, as well as security for all things in the cloud. >> I'm sorry. Richard, how hard is your job these days? (laughing) And I mean that with all due respect. We've talked a lot about complexity. We've talked a lot about speed. We've talked a lot about versatility, and high demand, and all these things. Corner office is making demands on you, right? I mean, how tough is it to be in your shoes? >> If it was easy, it wouldn't be fun. I've been working in cloud about as long as Robert Half has, about seven years, and moving into the security role, it's been an incredibly interesting challenge. Yes, it's hard. I do stay up at night on occasion worrying about, did I check this, did I check that? I'm fortunate that our management has a really good understanding of the importance of security and of cloud, and I've gotten a lot of support in my role there so, in that respect, it hasn't been too hard. >> And where is it that security, in terms of a deployment? So, you think about function, right, right? >> Yeah. >> What are we going to get done here? But is it a close second, is it a tie? Because, especially in your business, I mean, you have a lot of personal information with which you're working that you've got to protect. >> Absolutely, so, people trust us with their data. We have personal information for many, many people, and we take very seriously our responsibility to manage and protect that. One of the things that we've done with Palo Alto's tools is ensuring that we're compliant with all of the various standards like ISO 27001, and compliance is kind of like brushing your teeth, right. Everybody needs to do it, and somebody doesn't want to be friends with somebody who doesn't brush their teeth. So, we ensure that we brush our teeth using tools like Palo Alto's. We can demonstrate to people that we're brushing our teeth. >> Right. >> With the innovation of RedLock now, we're able to take that to the next level, so we're not only brushing our teeth now, but we're also grooming our hair. >> You're technologically flossing as well, I'm sure. >> We are, we are. >> So, Ankur, I think that makes you the dentist of cloud security. (laughing) >> So, you've got people brushing their teeth, they're flossing. What comes next? What should they be looking at? Should they be going beyond just hygiene factors, and is there something they can do that's more than just brushing their teeth? >> Yeah, so I touched upon some of those areas. So, I think it all starts with the basic hygiene that we've talked about it, right. So, you got to do it. That's the, kind of, the fundamental, but the next-gen attacks are not going to be very simple, right, because the cloud fundamentally increases the attack factor, right, so the malicious actor, they're smarter, right. So, like I mentioned, things like cryptojacking, stolen access keys, a lot of the next-gen breeches are going to happen in the cloud, so customers have to constantly understand the kind of AWS services that they're adopting, understand the security implications, make sure they have the security guard rails, and like I mentioned, that once they understand that, look at it more holistically, both from, sort of, the basic hygiene perspective, as well as from network security, user activity, as well host monitoring perspective. Once they cover all of that stuff, you know, hopefully they'll have good teeth forever. (laughing) >> Strong cloud teeth. I don't think that's a phrase I wouldn't have thought I'd say until today. >> You know, we hear a lot about the cat and mouse game in security, right? You're trying to stay one step ahead of bad actors who are spending a lot of time, and a lot of resources, and a lot of energy to stay a step ahead of you. So, in today's world, how do you really win that battle? How do you predict where the next wrong turn is going to come, if you will, or where that invasion's going to try to occur, and prevent that, or are you in a prophylactic state all the time where it's about seeing where that action's going, and then trying to stop it once you've learned of it? See what I mean? It's a conundrum that I think you find yourself in. >> You know, I think 90% of the problems that happen where bad actors get hold of your sensitive data is because of common, silly mistakes. So, making sure that there is a user training across the board, not just security teams. Now, DevOps teams have to be part of the equation as well. They need to be trained, and coached, and understanding the security implications of their day-to-day operations. Once you train the users, you'll find that a lot of these problems will go away because most of these actors are using simple techniques to get into the customer's cloud environment because those mistakes are being made. So, start with the user training. Obviously, you need third party tooling and technologies like Palo Alto Networks to make sure you have that security guard rails all the time. Beyond that, you know, you just have to hire a lot of smart people like Richard just to insure that you're ahead of the game, thinking two steps in advance, yeah. >> It's about locking the door. >> Yeah. >> Yeah, and I want to touch on a couple of the things that Ankur said. He talked about building security into DevOps. So, there's this concept we call shifting left where you're trying to build security more upfront into the development and deployment process before you even get into the wild, and that's something Palo Alto is helping us with. The other thing is, we cannot hire enough people to keep up with the pace at which we're scaling our cloud environments, so we need tooling and automation like RedLock in order to ensure that we can get visibility and control on this vast set of resources with just a small number of people. >> Yeah. >> So necessity driving invention in that case, right? >> Yes. >> You need it. Well, gentlemen, thanks for the time. We appreciate the conversation. I feel like I need to go brush or floss. (laughing) >> Yeah, thanks for having us. >> Very self-conscious all of a sudden, but thank you both. >> Thanks for having us. >> Brilliant discussion. Back with more from AWS re:Invent. You're watching theCUBE here in Las Vegas. (energetic electronic music)

>> From Times Square in the heart of New York City, it's theCUBE, covering Imagine 2018. Brought to you by Automation Anywhere. >> Hey welcome back everybody. Jeff Frick here with theCUBE. We're in downtown Manhattan, actually midtown Manhattan, at Automation Anywhere Imagine 2018, 1100 people talkin' about bots, talkin' about Robotics Process Automation, or RPA. And we're excited to have the guy that counts the money at the end of the day; it's important part of any business. He's a co-founder, Ankur Kothari, Chief Revenue Officer and Co-Founder, Automation Anywhere. Ankur, great to see you. >> Great to be here, Jeff, thanks for having me. >> So, first off, as a co-founder, I think you're the third or fourth co-founder we've had on today. A little bit of reflection since you guys started this like 14 years ago. >> Yeah. Here we are, there's 1100 people, the room is packed. They had the overflow, they're actually all over us out here with the overflow for the keynote. Take a minute and kinda tell us how you feel about how this thing has evolved over time. >> It feels like a great party to be part of. Always, you're always happy. >> Right. >> One of the traits that you'll find a lot of co-founders is that they are always happy, never satisfied. They're always looking for the next big one. >> Right. >> But it's amazing to be part of Imagine because we learn so much from our customers and our partner as well. It's not just that we bring them together and we're talking. We're learning every time. It's becoming a big ecosystem. >> Right. >> And, an idea as big as a bot or a future of work is too big an idea for one company to continue. You want as many people to come. >> Right. >> So, our idea of Imagine was a little bit like Field of Dreams, you build and they'll come and they'll collaborate and it'll become bigger and bigger. >> And look all around us. I mean, we're surrounded by people and really, the ecosystem. >> And the bots as well, there are bots on the walls and everything else. >> Bots on the walls, partners everywhere. So let's dive into it a little bit. I mean, one of the ways that you guys participate in the ecosystem, and the ecosystem participates, is the Bot Store. >> Yes. >> So it's just like any other kind of an app store. >> Exactly. >> You've got people contributing. I assume you guys have contributed stuff. But we saw earlier in the keynote by Accenture, and EY, and Deloitte. And all types of companies are contributing bots into this ecosystem for lots of different functions or applications. So really, an interesting thing. How's that workin' out? Where'd you come up with the idea? And why's that so important? >> At Automation Anywhere we like to ask ourselves hard questions, as the leaders in this space. And we asked ourselves this question, "What can we now do to further accelerate our journey of all our customers to become a digital enterprise?" The answer came that we are to share in the new bot economy. Now once that answer was clear, every economy requires a marketplace. >> Right. >> And that's where the Bot Store came. It's a marketplace where producers meet the consumers, and you connect them. All we do is, we curate and make sure that the right things go up. But other than that, it's just like any other marketplace. And we thought that if we'll build the right marketplace where the producers meet consumers, we have thousands of customers and large companies looking at it. It will allow perfect place where all the right ideas get converted into product. >> Right. >> We have tons of partners who have domain expertise, functional expertise, vertical expertise; they can prioritize their expertise, they can convert it into IP. >> Right. >> They can do it for free, they can monetize it. So there's lots to gain for producers of all these bots. And if I am a consumer, now suddenly my time clock to make further shrinks, because instead of creating these bots all from scratch, I can download them from this Bot Store and snap them together like a Lego block. >> Right. >> So that's how the whole idea came. We launched it just two months ago and we have hundreds-- >> You just launched it two months ago? >> Yeah! And we have hundreds of bots in it. More than 80-100 partners have participated. We are getting at least 20-30 more submissions coming every day, and we have few hundred submissions coming every week. So, just like any free marketplace, it has an exponential nature. And that's the thing we are counting on. >> That's amazing, that you've got that much traction in such a short period of time. >> Thousands of downloads on a daily basis. Thousands of users just in two month's time. >> You know, we go to a ton of shows. We do over a hundred shows a year. And once shows get to a certain size, it starts to change a little bit. But when they're small like this, it's a very intimate affair on a couple floors here at the Sheraton, everyone is still really involved. They're really sharing. >> Yes. >> There's so much sharing of information. Not so much, you know ... Because they're not really competitors. Within their own companies, they're all part of this same team that are trying to implement this new thing. >> Exactly. >> And you really feel it. >> Exactly. >> So, the store's cool, but the bot economy. When you talk about the bot economy, we talk about API economy a lot. >> Yes. >> How do you see the bot economy? What are the factors that drive the bot economy, and how's it gonna evolve over time? >> We look at it as a few elements. The current version, we think that bot economy, like any economy, has a marketplace, which is our Bot Store. We have a program which we call Bot Games, because any good economy, any new economy, one of the trait is that the good idea can come from anyone. >> Right. >> It can come from anyplace. Like, any customers, any partner, anyone can bring. A good economy, what it does is it brings that idea from anyone, and it gives these vehicles for good ideas to take flight. If the idea is good, it becomes viral, and it has vehicles where those ideas can go to market. What we did was, we created a program called Bot Games. Yesterday on May 29th, we had the 1st Inaugural Bot Games. We invited developers, people who are part of these programs and their companies. And we gamified and created different games. And we thought that if we bring all these champions and pioneers and like-minded people in the same room, give them certain same problem, and then gamify it, put a clock on it, a lot of great ideas will come out of it. >> Right. >> And that came. And some of those ideas will make it to the marketplace, like a Bot Store, like an Imagine. >> Right. >> So that's where all the ideas connect to the customers. And the people who bring those ideas, they also come up. So that's the other aspect. So the Bot Games is where the ideas, you can crowdsource from places. Bot Store is where they go to the market. In between there is a gap. And we are trying to remove that gap by creating a stimulus package for this new bot economy. Like any economy time and again requires a stimulus pack, and we have created one. What we have done is that if you want to learn Automation Anywhere, right? If you want to understand, because that gap is you're to understand Automation Anywhere. We have created Automation Anywhere University a year ago. And now anyone can take courses for free to learn how to create bots. Whether they are customers or partners. And then, if you purchase these bots through one of our certified partners, the first three bots in year one are free. So we are removing the friction in between. If you have not started on this journey, your learning is free, you get ideas from different places, we can get these prebuilt bots, and the first three bots, if you purchase it through our partners, they are free. So we are removing that friction. And then, we are supporting that whole economy with the industry's largest customer success program. >> Right. So I'm curious if you know, maybe you don't know, of the bots in the bots store, how many are free and how many are paid, as a percentage? >> Interestingly, I don't have that stat because we don't actually worry about that. We let all our partners and people who are contributing to this Bot Store decide that. >> Right. >> Some bots they may decide to monetize, some they may not. It's listed on the Bot Store. Offhand, I would say-- >> Take a guess. Is it 50/50? A third? Two-thirds? >> The nature of it looks like 50/50. >> That's a good guess. Full caveat, it's a guess. We didn't do the analysis. >> Exactly. But here is the unique aspect. Yesterday we had a Bot Game, and the winner had an amazing idea that none of us had ever think of. He created this bot that automates the COE of all these programs. Now, we are talking. He is thinking of putting that on Bot Store. That's the power of bringing multiple people together. >> Right. >> That's the power of free economy, where the exponential nature of it is what we are counting on. And we are getting on a daily basis these new bot ideas, these new bots that are making it to the Bot Store. Just like your App Store. I go to App Store to get ideas what I can do on my phone. >> Right, right. >> Just like that, now we are finding our customers are going to Bot Store to figure out what else can they automate. >> Right, right. >> And that's been another amazing part of it. >> You know, it's so consistent. All these shows we go to, right? How do you unlock innovation? There's some really simple ways. One is, give more people the power, give more people the tools, and give more people the data. >> Exactly. >> And you'll get stuff out of it that the small subset of people that used to have access to those three things, they never found. They just didn't think of it that way, right? >> Exactly. And then we firmly believe that any technology, anything, once you democratize it, you give it in hands of everyone-- >> Right, right. >> You can't have a thriving economy unless everyone forms their own point of view. Unless everyone creates their own perspective. And that's our vision of this bot economy. We are bringing everyone and giving them these vehicles to try it out. Look, the technology has reached a stage where it's cheaper to try it out than talk about it. >> Yes. >> And we are doing that so that everyone forms their own unique point of view, and then they express that point of view and we connect those points of view to these thousands of customers worldwide. >> Right. >> Good ideas take flight, and all we have to do is create vehicles for those good ideas to take flight. >> Alright. So, Ankur, I gave you the last word before we wrap up here. If we come back next year, a year from now, inspired 2019, what are we gonna be talking about? What's on your roadmap? What're some of the priorities that you guys are workin' on over the next 12 months? >> We are talking about ... The next 12 months, we are looking at how to further accelerate this journey. Because what people are in this, the real problem people are trying to achieve is how to become a digital enterprise. Not just to automate, but how do you create a digital enterprise? You cannot become a digital enterprise unless your operations are digital. You cannot make your operations digital unless your processes are digital. And you cannot do that unless your workforce is digital. So we are trying to create technologies, vehicles, platforms, so that everyone can scale their program. Where pretty much everyone should have a digital colleague. Everyone should be able to create a bot. Everyone should be able to work with a bot. Every process, every department, every system should have a digital workforce working in it and that can allow you to create a digital enterprise that can scale up and scale down with the demand and supply. >> Alright-- >> That's what we are trying to start. >> Well, we look forward to gettin' the update next year. >> Exactly. >> Alright, Ankur, thanks for taking a few minutes out of your busy day with us. >> Thanks for having me here, and I appreciate and enjoy the conversation. >> Alright, he's Ankur, I'm Jeff. We're at Automation Anywhere Imagine 2018. Thanks for watching theCUBE. See you next time.

(mellow music) >> Hello everyone, welcome to theCUBE's coverage of AWS Startup Showcase. This is the closing panel session on AI machine learning, the top startups generating generative AI on AWS. It's a great panel. This is going to be the experts talking about riding the wave in generative AI. We got Ankur Mehrotra, who's the director and general manager of AI and machine learning at AWS, and Clem Delangue, co-founder and CEO of Hugging Face, and Ori Goshen, who's the co-founder and CEO of AI21 Labs. Ori from Tel Aviv dialing in, and rest coming in here on theCUBE. Appreciate you coming on for this closing session for the Startup Showcase. >> Thanks for having us. >> Thank you for having us. >> Thank you. >> I'm super excited to have you all on. Hugging Face was recently in the news with the AWS relationship, so congratulations. Open source, open science, really driving the machine learning. And we got the AI21 Labs access to the LLMs, generating huge scale live applications, commercial applications, coming to the market, all powered by AWS. So everyone, congratulations on all your success, and thank you for headlining this panel. Let's get right into it. AWS is powering this wave here. We're seeing a lot of push here from applications. Ankur, set the table for us on the AI machine learning. It's not new, it's been goin' on for a while. Past three years have been significant advancements, but there's been a lot of work done in AI machine learning. Now it's released to the public. Everybody's super excited and now says, "Oh, the future's here!" It's kind of been going on for a while and baking. Now it's kind of coming out. What's your view here? Let's get it started. >> Yes, thank you. So, yeah, as you may be aware, Amazon has been in investing in machine learning research and development since quite some time now. And we've used machine learning to innovate and improve user experiences across different Amazon products, whether it's Alexa or Amazon.com. But we've also brought in our expertise to extend what we are doing in the space and add more generative AI technology to our AWS products and services, starting with CodeWhisperer, which is an AWS service that we announced a few months ago, which is, you can think of it as a coding companion as a service, which uses generative AI models underneath. And so this is a service that customers who have no machine learning expertise can just use. And we also are talking to customers, and we see a lot of excitement about generative AI, and customers who want to build these models themselves, who have the talent and the expertise and resources. For them, AWS has a number of different options and capabilities they can leverage, such as our custom silicon, such as Trainium and Inferentia, as well as distributed machine learning capabilities that we offer as part of SageMaker, which is an end-to-end machine learning development service. At the same time, many of our customers tell us that they're interested in not training and building these generative AI models from scratch, given they can be expensive and can require specialized talent and skills to build. And so for those customers, we are also making it super easy to bring in existing generative AI models into their machine learning development environment within SageMaker for them to use. So we recently announced our partnership with Hugging Face, where we are making it super easy for customers to bring in those models into their SageMaker development environment for fine tuning and deployment. And then we are also partnering with other proprietary model providers such as AI21 and others, where we making these generative AI models available within SageMaker for our customers to use. So our approach here is to really provide customers options and choices and help them accelerate their generative AI journey. >> Ankur, thank you for setting the table there. Clem and Ori, I want to get your take, because the riding the waves, the theme of this session, and to me being in California, I imagine the big surf, the big waves, the big talent out there. This is like alpha geeks, alpha coders, developers are really leaning into this. You're seeing massive uptake from the smartest people. Whether they're young or around, they're coming in with their kind of surfboards, (chuckles) if you will. These early adopters, they've been on this for a while; Now the waves are hitting. This is a big wave, everyone sees it. What are some of those early adopter devs doing? What are some of the use cases you're seeing right out of the gate? And what does this mean for the folks that are going to come in and get on this wave? Can you guys share your perspective on this? Because you're seeing the best talent now leaning into this. >> Yeah, absolutely. I mean, from Hugging Face vantage points, it's not even a a wave, it's a tidal wave, or maybe even the tide itself. Because actually what we are seeing is that AI and machine learning is not something that you add to your products. It's very much a new paradigm to do all technology. It's this idea that we had in the past 15, 20 years, one way to build software and to build technology, which was writing a million lines of code, very rule-based, and then you get your product. Now what we are seeing is that every single product, every single feature, every single company is starting to adopt AI to build the next generation of technology. And that works both to make the existing use cases better, if you think of search, if you think of social network, if you think of SaaS, but also it's creating completely new capabilities that weren't possible with the previous paradigm. Now AI can generate text, it can generate image, it can describe your image, it can do so many new things that weren't possible before. >> It's going to really make the developers really productive, right? I mean, you're seeing the developer uptake strong, right? >> Yes, we have over 15,000 companies using Hugging Face now, and it keeps accelerating. I really think that maybe in like three, five years, there's not going to be any company not using AI. It's going to be really kind of the default to build all technology. >> Ori, weigh in on this. APIs, the cloud. Now I'm a developer, I want to have live applications, I want the commercial applications on this. What's your take? Weigh in here. >> Yeah, first, I absolutely agree. I mean, we're in the midst of a technology shift here. I think not a lot of people realize how big this is going to be. Just the number of possibilities is endless, and I think hard to imagine. And I don't think it's just the use cases. I think we can think of it as two separate categories. We'll see companies and products enhancing their offerings with these new AI capabilities, but we'll also see new companies that are AI first, that kind of reimagine certain experiences. They build something that wasn't possible before. And that's why I think it's actually extremely exciting times. And maybe more philosophically, I think now these large language models and large transformer based models are helping us people to express our thoughts and kind of making the bridge from our thinking to a creative digital asset in a speed we've never imagined before. I can write something down and get a piece of text, or an image, or a code. So I'll start by saying it's hard to imagine all the possibilities right now, but it's certainly big. And if I had to bet, I would say it's probably at least as big as the mobile revolution we've seen in the last 20 years. >> Yeah, this is the biggest. I mean, it's been compared to the Enlightenment Age. I saw the Wall Street Journal had a recent story on this. We've been saying that this is probably going to be bigger than all inflection points combined in the tech industry, given what transformation is coming. I guess I want to ask you guys, on the early adopters, we've been hearing on these interviews and throughout the industry that there's already a set of big companies, a set of companies out there that have a lot of data and they're already there, they're kind of tinkering. Kind of reminds me of the old hyper scaler days where they were building their own scale, and they're eatin' glass, spittin' nails out, you know, they're hardcore. Then you got everybody else kind of saying board level, "Hey team, how do I leverage this?" How do you see those two things coming together? You got the fast followers coming in behind the early adopters. What's it like for the second wave coming in? What are those conversations for those developers like? >> I mean, I think for me, the important switch for companies is to change their mindset from being kind of like a traditional software company to being an AI or machine learning company. And that means investing, hiring machine learning engineers, machine learning scientists, infrastructure in members who are working on how to put these models in production, team members who are able to optimize models, specialized models, customized models for the company's specific use cases. So it's really changing this mindset of how you build technology and optimize your company building around that. Things are moving so fast that I think now it's kind of like too late for low hanging fruits or small, small adjustments. I think it's important to realize that if you want to be good at that, and if you really want to surf this wave, you need massive investments. If there are like some surfers listening with this analogy of the wave, right, when there are waves, it's not enough just to stand and make a little bit of adjustments. You need to position yourself aggressively, paddle like crazy, and that's how you get into the waves. So that's what companies, in my opinion, need to do right now. >> Ori, what's your take on the generative models out there? We hear a lot about foundation models. What's your experience running end-to-end applications for large foundation models? Any insights you can share with the app developers out there who are looking to get in? >> Yeah, I think first of all, it's start create an economy, where it probably doesn't make sense for every company to create their own foundation models. You can basically start by using an existing foundation model, either open source or a proprietary one, and start deploying it for your needs. And then comes the second round when you are starting the optimization process. You bootstrap, whether it's a demo, or a small feature, or introducing new capability within your product, and then start collecting data. That data, and particularly the human feedback data, helps you to constantly improve the model, so you create this data flywheel. And I think we're now entering an era where customers have a lot of different choice of how they want to start their generative AI endeavor. And it's a good thing that there's a variety of choices. And the really amazing thing here is that every industry, any company you speak with, it could be something very traditional like industrial or financial, medical, really any company. I think peoples now start to imagine what are the possibilities, and seriously think what's their strategy for adopting this generative AI technology. And I think in that sense, the foundation model actually enabled this to become scalable. So the barrier to entry became lower; Now the adoption could actually accelerate. >> There's a lot of integration aspects here in this new wave that's a little bit different. Before it was like very monolithic, hardcore, very brittle. A lot more integration, you see a lot more data coming together. I have to ask you guys, as developers come in and grow, I mean, when I went to college and you were a software engineer, I mean, I got a degree in computer science, and software engineering, that's all you did was code, (chuckles) you coded. Now, isn't it like everyone's a machine learning engineer at this point? Because that will be ultimately the science. So, (chuckles) you got open source, you got open software, you got the communities. Swami called you guys the GitHub of machine learning, Hugging Face is the GitHub of machine learning, mainly because that's where people are going to code. So this is essentially, machine learning is computer science. What's your reaction to that? >> Yes, my co-founder Julien at Hugging Face have been having this thing for quite a while now, for over three years, which was saying that actually software engineering as we know it today is a subset of machine learning, instead of the other way around. People would call us crazy a few years ago when we're seeing that. But now we are realizing that you can actually code with machine learning. So machine learning is generating code. And we are starting to see that every software engineer can leverage machine learning through open models, through APIs, through different technology stack. So yeah, it's not crazy anymore to think that maybe in a few years, there's going to be more people doing AI and machine learning. However you call it, right? Maybe you'll still call them software engineers, maybe you'll call them machine learning engineers. But there might be more of these people in a couple of years than there is software engineers today. >> I bring this up as more tongue in cheek as well, because Ankur, infrastructure's co is what made Cloud great, right? That's kind of the DevOps movement. But here the shift is so massive, there will be a game-changing philosophy around coding. Machine learning as code, you're starting to see CodeWhisperer, you guys have had coding companions for a while on AWS. So this is a paradigm shift. How is the cloud playing into this for you guys? Because to me, I've been riffing on some interviews where it's like, okay, you got the cloud going next level. This is an example of that, where there is a DevOps-like moment happening with machine learning, whether you call it coding or whatever. It's writing code on its own. Can you guys comment on what this means on top of the cloud? What comes out of the scale? What comes out of the benefit here? >> Absolutely, so- >> Well first- >> Oh, go ahead. >> Yeah, so I think as far as scale is concerned, I think customers are really relying on cloud to make sure that the applications that they build can scale along with the needs of their business. But there's another aspect to it, which is that until a few years ago, John, what we saw was that machine learning was a data scientist heavy activity. They were data scientists who were taking the data and training models. And then as machine learning found its way more and more into production and actual usage, we saw the MLOps become a thing, and MLOps engineers become more involved into the process. And then we now are seeing, as machine learning is being used to solve more business critical problems, we're seeing even legal and compliance teams get involved. We are seeing business stakeholders more engaged. So, more and more machine learning is becoming an activity that's not just performed by data scientists, but is performed by a team and a group of people with different skills. And for them, we as AWS are focused on providing the best tools and services for these different personas to be able to do their job and really complete that end-to-end machine learning story. So that's where, whether it's tools related to MLOps or even for folks who cannot code or don't know any machine learning. For example, we launched SageMaker Canvas as a tool last year, which is a UI-based tool which data analysts and business analysts can use to build machine learning models. So overall, the spectrum in terms of persona and who can get involved in the machine learning process is expanding, and the cloud is playing a big role in that process. >> Ori, Clem, can you guys weigh in too? 'Cause this is just another abstraction layer of scale. What's it mean for you guys as you look forward to your customers and the use cases that you're enabling? >> Yes, I think what's important is that the AI companies and providers and the cloud kind of work together. That's how you make a seamless experience and you actually reduce the barrier to entry for this technology. So that's what we've been super happy to do with AWS for the past few years. We actually announced not too long ago that we are doubling down on our partnership with AWS. We're excited to have many, many customers on our shared product, the Hugging Face deep learning container on SageMaker. And we are working really closely with the Inferentia team and the Trainium team to release some more exciting stuff in the coming weeks and coming months. So I think when you have an ecosystem and a system where the AWS and the AI providers, AI startups can work hand in hand, it's to the benefit of the customers and the companies, because it makes it orders of magnitude easier for them to adopt this new paradigm to build technology AI. >> Ori, this is a scale on reasoning too. The data's out there and making sense out of it, making it reason, getting comprehension, having it make decisions is next, isn't it? And you need scale for that. >> Yes. Just a comment about the infrastructure side. So I think really the purpose is to streamline and make these technologies much more accessible. And I think we'll see, I predict that we'll see in the next few years more and more tooling that make this technology much more simple to consume. And I think it plays a very important role. There's so many aspects, like the monitoring the models and their kind of outputs they produce, and kind of containing and running them in a production environment. There's so much there to build on, the infrastructure side will play a very significant role. >> All right, that's awesome stuff. I'd love to change gears a little bit and get a little philosophy here around AI and how it's going to transform, if you guys don't mind. There's been a lot of conversations around, on theCUBE here as well as in some industry areas, where it's like, okay, all the heavy lifting is automated away with machine learning and AI, the complexity, there's some efficiencies, it's horizontal and scalable across all industries. Ankur, good point there. Everyone's going to use it for something. And a lot of stuff gets brought to the table with large language models and other things. But the key ingredient will be proprietary data or human input, or some sort of AI whisperer kind of role, or prompt engineering, people are saying. So with that being said, some are saying it's automating intelligence. And that creativity will be unleashed from this. If the heavy lifting goes away and AI can fill the void, that shifts the value to the intellect or the input. And so that means data's got to come together, interact, fuse, and understand each other. This is kind of new. I mean, old school AI was, okay, got a big model, I provisioned it long time, very expensive. Now it's all free flowing. Can you guys comment on where you see this going with this freeform, data flowing everywhere, heavy lifting, and then specialization? >> Yeah, I think- >> Go ahead. >> Yeah, I think, so what we are seeing with these large language models or generative models is that they're really good at creating stuff. But I think it's also important to recognize their limitations. They're not as good at reasoning and logic. And I think now we're seeing great enthusiasm, I think, which is justified. And the next phase would be how to make these systems more reliable. How to inject more reasoning capabilities into these models, or augment with other mechanisms that actually perform more reasoning so we can achieve more reliable results. And we can count on these models to perform for critical tasks, whether it's medical tasks, legal tasks. We really want to kind of offload a lot of the intelligence to these systems. And then we'll have to get back, we'll have to make sure these are reliable, we'll have to make sure we get some sort of explainability that we can understand the process behind the generated results that we received. So I think this is kind of the next phase of systems that are based on these generated models. >> Clem, what's your view on this? Obviously you're at open community, open source has been around, it's been a great track record, proven model. I'm assuming creativity's going to come out of the woodwork, and if we can automate open source contribution, and relationships, and onboarding more developers, there's going to be unleashing of creativity. >> Yes, it's been so exciting on the open source front. We all know Bert, Bloom, GPT-J, T5, Stable Diffusion, that work up. The previous or the current generation of open source models that are on Hugging Face. It has been accelerating in the past few months. So I'm super excited about ControlNet right now that is really having a lot of impact, which is kind of like a way to control the generation of images. Super excited about Flan UL2, which is like a new model that has been recently released and is open source. So yeah, it's really fun to see the ecosystem coming together. Open source has been the basis for traditional software, with like open source programming languages, of course, but also all the great open source that we've gotten over the years. So we're happy to see that the same thing is happening for machine learning and AI, and hopefully can help a lot of companies reduce a little bit the barrier to entry. So yeah, it's going to be exciting to see how it evolves in the next few years in that respect. >> I think the developer productivity angle that's been talked about a lot in the industry will be accelerated significantly. I think security will be enhanced by this. I think in general, applications are going to transform at a radical rate, accelerated, incredible rate. So I think it's not a big wave, it's the water, right? I mean, (chuckles) it's the new thing. My final question for you guys, if you don't mind, I'd love to get each of you to answer the question I'm going to ask you, which is, a lot of conversations around data. Data infrastructure's obviously involved in this. And the common thread that I'm hearing is that every company that looks at this is asking themselves, if we don't rebuild our company, start thinking about rebuilding our business model around AI, we might be dinosaurs, we might be extinct. And it reminds me that scene in Moneyball when, at the end, it's like, if we're not building the model around your model, every company will be out of business. What's your advice to companies out there that are having those kind of moments where it's like, okay, this is real, this is next gen, this is happening. I better start thinking and putting into motion plans to refactor my business, 'cause it's happening, business transformation is happening on the cloud. This kind of puts an exclamation point on, with the AI, as a next step function. Big increase in value. So it's an opportunity for leaders. Ankur, we'll start with you. What's your advice for folks out there thinking about this? Do they put their toe in the water? Do they jump right into the deep end? What's your advice? >> Yeah, John, so we talk to a lot of customers, and customers are excited about what's happening in the space, but they often ask us like, "Hey, where do we start?" So we always advise our customers to do a lot of proof of concepts, understand where they can drive the biggest ROI. And then also leverage existing tools and services to move fast and scale, and try and not reinvent the wheel where it doesn't need to be. That's basically our advice to customers. >> Get it. Ori, what's your advice to folks who are scratching their head going, "I better jump in here. "How do I get started?" What's your advice? >> So I actually think that need to think about it really economically. Both on the opportunity side and the challenges. So there's a lot of opportunities for many companies to actually gain revenue upside by building these new generative features and capabilities. On the other hand, of course, this would probably affect the cogs, and incorporating these capabilities could probably affect the cogs. So I think we really need to think carefully about both of these sides, and also understand clearly if this is a project or an F word towards cost reduction, then the ROI is pretty clear, or revenue amplifier, where there's, again, a lot of different opportunities. So I think once you think about this in a structured way, I think, and map the different initiatives, then it's probably a good way to start and a good way to start thinking about these endeavors. >> Awesome. Clem, what's your take on this? What's your advice, folks out there? >> Yes, all of these are very good advice already. Something that you said before, John, that I disagreed a little bit, a lot of people are talking about the data mode and proprietary data. Actually, when you look at some of the organizations that have been building the best models, they don't have specialized or unique access to data. So I'm not sure that's so important today. I think what's important for companies, and it's been the same for the previous generation of technology, is their ability to build better technology faster than others. And in this new paradigm, that means being able to build machine learning faster than others, and better. So that's how, in my opinion, you should approach this. And kind of like how can you evolve your company, your teams, your products, so that you are able in the long run to build machine learning better and faster than your competitors. And if you manage to put yourself in that situation, then that's when you'll be able to differentiate yourself to really kind of be impactful and get results. That's really hard to do. It's something really different, because machine learning and AI is a different paradigm than traditional software. So this is going to be challenging, but I think if you manage to nail that, then the future is going to be very interesting for your company. >> That's a great point. Thanks for calling that out. I think this all reminds me of the cloud days early on. If you went to the cloud early, you took advantage of it when the pandemic hit. If you weren't native in the cloud, you got hamstrung by that, you were flatfooted. So just get in there. (laughs) Get in the cloud, get into AI, you're going to be good. Thanks for for calling that. Final parting comments, what's your most exciting thing going on right now for you guys? Ori, Clem, what's the most exciting thing on your plate right now that you'd like to share with folks? >> I mean, for me it's just the diversity of use cases and really creative ways of companies leveraging this technology. Every day I speak with about two, three customers, and I'm continuously being surprised by the creative ideas. And the future is really exciting of what can be achieved here. And also I'm amazed by the pace that things move in this industry. It's just, there's not at dull moment. So, definitely exciting times. >> Clem, what are you most excited about right now? >> For me, it's all the new open source models that have been released in the past few weeks, and that they'll keep being released in the next few weeks. I'm also super excited about more and more companies getting into this capability of chaining different models and different APIs. I think that's a very, very interesting development, because it creates new capabilities, new possibilities, new functionalities that weren't possible before. You can plug an API with an open source embedding model, with like a no-geo transcription model. So that's also very exciting. This capability of having more interoperable machine learning will also, I think, open a lot of interesting things in the future. >> Clem, congratulations on your success at Hugging Face. Please pass that on to your team. Ori, congratulations on your success, and continue to, just day one. I mean, it's just the beginning. It's not even scratching the service. Ankur, I'll give you the last word. What are you excited for at AWS? More cloud goodness coming here with AI. Give you the final word. >> Yeah, so as both Clem and Ori said, I think the research in the space is moving really, really fast, so we are excited about that. But we are also excited to see the speed at which enterprises and other AWS customers are applying machine learning to solve real business problems, and the kind of results they're seeing. So when they come back to us and tell us the kind of improvement in their business metrics and overall customer experience that they're driving and they're seeing real business results, that's what keeps us going and inspires us to continue inventing on their behalf. >> Gentlemen, thank you so much for this awesome high impact panel. Ankur, Clem, Ori, congratulations on all your success. We'll see you around. Thanks for coming on. Generative AI, riding the wave, it's a tidal wave, it's the water, it's all happening. All great stuff. This is season three, episode one of AWS Startup Showcase closing panel. This is the AI ML episode, the top startups building generative AI on AWS. I'm John Furrier, your host. Thanks for watching. (mellow music)