(bright music) >> Welcome back everyone. theCube's live coverage here. Day two, of two sets, three days of theCube coverage here at VMware Explore. This is our 12th year covering VMware's annual conference, formerly called VM World. I'm John Furrier, with Dave Vellante. We'd love seeing the progress and we've got great security comes Tom Gill, senior vices, president general manager, networking and advanced security business group at VMware. Great to see you. Thanks for coming on. >> Thanks. for having me. >> Yeah, really happy we could have you on. >> I think this is my sixth edition on the theCube. Do I get frequent flyer points or anything? >> Yeah. >> You first get the VIP badge. We'll make that happen. You can start getting credits. >> Okay, there we go. >> We won't interrupt you. Seriously, you got a great story in security here. The security story is kind of embedded everywhere, so it's not called out and blown up and talked specifically about on stage. It's kind of in all the narratives in the VM World for this year. But you guys have an amazing security story. So let's just step back and to set context. Tell us the security story for what's going on here at VMware and what that means to this supercloud, multi-cloud and ongoing innovation with VMware. >> Yeah, sure thing. So probably the first thing I'll point out is that security's not just built in at VMware. It's built differently. So, we're not just taking existing security controls and cut and pasting them into our software. But we can do things because of our platform, because of the virtualization layer that you really can't do with other security tools. And where we're very, very focused is what we call lateral security or East-West movement of an attacker. 'Cause frankly, that's the name of the game these days. Attackers, you've got to assume that they're already in your network. Already assume that they're there. Then how do we make it hard for them to get to the stuff that you really want? Which is the data that they're going after. And that's where we really should. >> All right. So we've been talking a lot, coming into VMware Explore, and here, the event. About two things. Security, as a state. >> Yeah. >> I'm secure right now. >> Yeah. >> Or I think I'm secure right now, even though someone might be in my network or in my environment. To the notion of being defensible. >> Yeah. >> Meaning I have to defend and be ready at a moment's notice to attack, fight, push back, red team, blue team. Whatever you're going to call it. But something's happening. I got to be able to defend. >> Yeah. So what you're talking about is the principle of Zero Trust. When I first started doing security, the model was we have a perimeter. And everything on one side of the perimeter is dirty, ugly, old internet. And everything on this side, known good, trusted. What could possibly go wrong. And I think we've seen that no matter how good you make that perimeter, bad guys find a way in. So Zero Trust says, you know what? Let's just assume they're already in. Let's assume they're there. How do we make it hard for them to move around within the infrastructure and get to the really valuable assets? 'Cause for example, if they bust into your laptop, you click on a link and they get code running on your machine. They might find some interesting things on your machine. But they're not going to find 250 million credit cards. >> Right. >> Or the script of a new movie or the super secret aircraft plans. That lives in a database somewhere. And so it's that movement from your laptop to that database. That's where the damage is done and that's where VMware shines. >> So if they don't have the right to get to that database, they're not in. >> And it's not even just the right. So they're so clever and so sneaky that they'll steal a credential off your machine, go to another machine, steal a credential off of that. So, it's like they have the key to unlock each one of these doors. And we've gotten good enough where we can look at that lateral movement, even though it has a credential and a key, we're like wait a minute. That's not a real CIS Admin making a change. That's ransomware. And that's where you. >> You have to earn your way in. >> That's right. That's right. Yeah. >> And we're all kinds of configuration errors. But also some user problems. I've heard one story where there's so many passwords and username and passwords and systems that the bad guys scour, the dark web for passwords that have been exposed. >> Correct. >> And go test them against different accounts. Oh one hit over here. >> Correct. >> And people don't change their passwords all the time. >> Correct. >> That's a known vector. >> Just the idea that users are going to be perfect and never make a mistake. How long have we been doing this? Humans are the weakest link. So people are going to make mistakes. Attackers are going to be in. Here's another way of thinking about it. Remember log4j? Remember that whole fiasco? Remember that was at Christmas time. That was nine months ago. And whoever came up with that vulnerability, they basically had a skeleton key that could access every network on the planet. I don't know if a single customer that said, "Oh yeah, I wasn't impacted by log4j." So here's some organized entity had access to every network on the planet. What was the big breach? What was that movie script that got stolen? So there wasn't one, right? We haven't heard anything. So the point is, the goal of attackers is to get in and stay in. Imagine someone breaks into your house, steals your laptop and runs. That's a breach. Imagine someone breaks into your house and stays for nine months. It's untenable, in the real world, right? >> Right. >> We don't know in there, hiding in the closet. >> They're still in. >> They're watching everything. >> Hiding in your closet, exactly. >> Moving around, nibbling on your cookies. >> Drinking your beer. >> Yeah. >> So let's talk about how this translates into the new reality of cloud-native. Because now you hear about automated pentesting is a new hot thing right now. You got antivirus on data is hot within APIs, for instance. >> Yeah. >> API security. So all kinds of new hot areas. Cloud-native is very iterative. You know, you can't do a pentest every week. >> Right. >> You got to do it every second. >> So this is where it's going. It's not so much simulation. It's actually real testing. >> Right. Right. >> How do you view that? How does that fit into this? 'cause that seems like a good direction to me. >> Yeah. If it's right in, and you were talking to my buddy, Ahjay, earlier about what VMware can do to help our customers build cloud native applications with Tanzu. My team is focused on how do we secure those applications? So where VMware wants to be the best in the world is securing these applications from within. Looking at the individual piece parts and how they talk to each other and figuring out, wait a minute, that should never happen. By almost having an x-ray machine on the innards of the application. So we do it for both for VMs and for container based applications. So traditional apps are VM based. Modern apps are container based. And we have a slightly different insertion mechanism. It's the same idea. So for VMs, we do it with a hypervisor with NSX. We see all the inner workings. In a container world we have this thing called a service mesh that lets us look at each little snippet of code and how they talk to each other. And once you can see that stuff, then you can actually apply. It's almost like common sense logic of like, wait a minute. This API is giving back credit card numbers and it gives five an hour. All of a sudden, it's now asking for 20,000 or a million credit cards. That doesn't make any sense. The anomalies stick out like a sore thumb. If you can see them. At VMware, our unique focus in the infrastructure is that we can see each one of these little transactions and understand the conversation. That's what makes us so good at that East-West or lateral security. >> You don't belong in this room, get out or that that's some weird call from an in memory database, something over here. >> Exactly. Where other security solutions won't even see that. It's not like there algorithms aren't as good as ours or better or worse. It's the access to the data. We see the inner plumbing of the app and therefore we can protect the app from. >> And there's another dimension that I want to get in the table here. 'Cause to my knowledge only AWS, Google, I believe Microsoft and Alibaba and VMware have this. >> Correct >> It's Nitro. The equivalent of a Nitro. >> Yes. >> Project Monterey. >> Yeah. >> That's unique. It's the future of computing architectures. Everybody needs a Nitro. I've written about this. >> Yeah. >> Right. So explain your version. >> Yeah. >> It's now real. >> Yeah. >> It's now in the market, right? >> Yeah. >> Or soon will be. >> Here's our mission. >> Salient aspects. >> Yeah. Here's our mission of VMware. Is that we want to make every one of our enterprise customers. We want their private cloud to be as nimble, as agile, as efficient as the public cloud. >> And secure. >> And secure. In fact, I'll argue, we can make it actually more secure because we're thinking about putting security everywhere in this infrastructure. Not just on the edges of it. Okay. How do we go on that journey? As you pointed out, the public cloud providers realized five years ago that the right way to build computers was not just a CPU and a graphics process unit, GPU. But there's this third thing that the industry's calling a DPU, data processing unit. And so there's kind of three pieces of a computer. And the DPU is sometimes called a Smartnic. It's the network interface card. It does all that network handling and analytics and it takes it off the CPU. So they've been building and deploying those systems themselves. That's what Nitro is. And so we have been working with the major Silicon vendors to bring that architecture to everybody. So with vSphere 8, we have the ability to take the network processing, that East-West inspection I talked about, take it off of the CPU and put it into this dedicated processing element called the DPU and free up the CPU to run the applications that Ahjay and team are building. >> So no performance degradation at all? >> Correct. To CPU offload. >> So even the opposite, right? I mean you're running it basically Bare Metal speeds. >> Yes, yes and yes. >> And you're also isolating the storage from the security, the management, and. >> There's an isolation angle to this, which is that firewall, that we're putting everywhere. Not just that the perimeter, but we put it in each little piece of the server is running when it runs on one of these DPUs it's a different memory space. So even if an attacker gets to root in the OS, they it's very, very, never say never, but it's very difficult. >> So who has access to that resource? >> Pretty much just the infrastructure layer, the cloud provider. So it's Amazon, Google, Microsoft, and the enterprise. >> Application can't get in. >> Can't get in there. Cause you would've to literally bridge from one memory space to another. Never say never, but it would be very. >> But it hasn't earned the trust to get. >> It's more than barbwire. It's multiple walls. >> Yes. And it's like an air gap. It puts an air gap in the server itself so that if the server is compromised, it's not going to get into the network. Really powerful. >> What's the big thing that you're seeing with this supercloud transition. We're seeing multi-cloud and this new, not just SaaS hosted on the cloud. >> Yeah. >> You're seeing a much different dynamic of, combination of large scale CapEx, cloud-native, and then now cloud-native drills on premises and edge. Kind of changing what a cloud looks like if the cloud's on a cloud. >> Yeah. >> So we're the customer, I'm building on a cloud and I have on premise stuff. So, I'm getting scale CapEx relief from the hyperscalers. >> I think there's an important nuance on what you're talking about. Which is in the early days of the cloud customers. Remember those first skepticism? Oh, it'll never work. Oh, that's consumer grade. Oh, that's not really going to work. Oh some people realize. >> It's not secure. >> Yeah. It's not secure. >> That one's like, no, no, no it's secure. It works. And it's good. So then there was this sort of over rush. Let's put everything on the cloud. And I had a lot of customers that took VM based applications said, I'm going to move those onto the cloud. You got to take them all apart, put them on the cloud and put them all back together again. And little tiny details like changing an IP address. It's actually much harder than it looks. So my argument is, for existing workloads for VM based workloads, we are VMware. We're so good at running VM based workloads. And now we run them on anybody's cloud. So whether it's your east coast data center, your west coast data center, Amazon, Google, Microsoft, Alibaba, IBM keep going. We pretty much every. >> And the benefit of the customer is what. >> You can literally VMotion and just pick it up and move it from private to public, public to private, private to public, Back and forth. >> Remember when we called Vmotion BS, years ago? >> Yeah. Yeah. >> VMotion is powerful. >> We were very skeptical. We're like, that'll never happen. I mean we were. This supposed to be pat ourselves on the back. >> Well because alchemy. It seems like what you can't possibly do that. And now we do it across clouds. So it's not quite VMotion, but it's the same idea. You can just move these things over. I have one customer that had a production data center in the Ukraine. Things got super tense, super fast and they had to go from their private cloud data center in the Ukraine, to a public cloud data center out of harm's way. They did it over a weekend. 48 hours. If you've ever migrated a data center, that's usually six months. Right. And a lot of heartburn and a lot of angst. Boop. They just drag and dropped and moved it on over. That's the power of what we call the cloud operating model. And you can only do this when all your infrastructures defined in software. If you're relying on hardware, load balancers, hardware, firewalls, you can't move those. They're like a boat anchor. You're stuck with them. And by the way, they're really, really expensive. And by the way, they eat a lot of power. So that was an architecture from the 90's. In the cloud operating model your data center. And this comes back to what you were talking about is just racks and racks of X86 with these magic DPUs, or smart nics, to make any individual node go blisteringly fast and do all the functions that you used to do in network appliances. >> We just had Ahjay taking us to school, and everyone else to school on applications, middleware, abstraction layer. And Kit Culbert was also talking about this across cloud. We're talking supercloud, super pass. If this continues to happen, which we would think it will happen. What does the security posture look like? It feels to me, and again, this is your wheelhouse. If supercloud happens with this kind of past layer where there's vMotioning going on. All kinds of spanning applications and data across environments. >> Yeah. Assume there's an operating system working on behind the scenes. >> Right. >> What's the security posture in all this? >> Yeah. So remember my narrative about the bad guys are getting in and they're moving around and they're so sneaky that they're using legitimate pathways. The only way to stop that stuff, is you've got to understand it at what we call Layer 7. At the application layer. Trying to do security to the infrastructure layer. It was interesting 20 years ago, kind of less interesting 10 years ago. And now it's becoming irrelevant because the infrastructure is oftentimes not even visible. It's buried in some cloud provider. So Layer 7 understanding, application awareness, understanding the APIs and reading the content. That's the name of the game in security. That's what we've been focused on. Nothing to do with the infrastructure. >> And where's the progress bar on that paradigm. One to ten. Ten being everyone's doing it. >> Right now. Well, okay. So we as a vendor can do this today. All the stuff I talked about, reading APIs, understanding the individual services looking at, Hey, wait a minute this credit card anomalies, that's all shipping production code. Where is it in customer adoption life cycle? Early days 10%. So there's a whole lot of headroom for people to understand, Hey, I can put these controls in place. They're software based. They don't require appliances. It's Layer 7, so it has contextual awareness and it's works on every single cloud. >> We talked about the pandemic being an accelerator. It really was a catalyst to really rethink. Remember we used to talk about Pat as a security do over. He's like, yes, if it's the last thing I do, I'm going to fix security. Well, he decided to go try to fix Intel instead. >> He's getting some help from the government. >> But it seems like CISOs have totally rethought their security strategy. And at least in part, as a function of the pandemic. >> When I started at VMware four years ago, Pat sat me down in his office and he said to me what he said to you, which is like, "Tom," he said, "I feel like we have fundamentally changed servers. We fundamentally change storage. We fundamentally change networking. The last piece of the puzzle of security. I want you to go fundamentally change it." And I'll argue that the work that we're doing with this horizontal security, understanding the lateral movement. East- West inspection. It fundamentally changes how security works. It's got nothing to do with firewalls. It's got nothing to do with Endpoint. It's a unique capability that VMware is uniquely suited to deliver on. And so Pat, thanks for the mission. We delivered it and it's available now. >> Those WET web applications firewall for instance are around, I mean. But to your point, the perimeter's gone. >> Exactly. >> And so you got to get, there's no perimeter. so it's a surface area problem. >> Correct. And access. And entry. >> Correct. >> They're entering here easy from some manual error, or misconfiguration or bad password that shouldn't be there. They're in. >> Think about it this way. You put the front door of your house, you put a big strong door and a big lock. That's a firewall. Bad guys come in the window. >> And then the windows open. With a ladder. >> Oh my God. Cause it's hot, bad user behavior trumps good security every time. >> And then they move around room to room. We're the room to room people. We see each little piece of the thing. Wait, that shouldn't happen. Right. >> I want to get you a question that we've been seeing and maybe we're early on this or it might be just a false data point. A lot of CSOs and we're talking to are, and people in industry in the customer environment are looking at CISOs and CSOs, two roles. Chief information security officer, and then chief security officer. Amazon, actually Steven Schmidt is now CSO at Reinforce. They actually called that out. And the interesting point that he made, we had some other situations that verified this, is that physical security is now tied to online, to your point about the service area. If I get a password, I still got the keys to the physical goods too. >> Right. So physical security, whether it's warehouse for them or store or retail. Digital is coming in there. >> Yeah. So is there a CISO anymore? Is it just CSO? What's the role? Or are there two roles you see that evolving? Or is that just circumstance. >> I think it's just one. And I think that the stakes are incredibly high in security. Just look at the impact that these security attacks are having on. Companies get taken down. Equifax market cap was cut 80% with a security breach. So security's gone from being sort of a nuisance to being something that can impact your whole kind of business operation. And then there's a whole nother domain where politics get involved. It determines the fate of nations. I know that sounds grand, but it's true. And so companies care so much about it they're looking for one leader, one throat to choke. One person that's going to lead security in the virtual domain, in the physical domain, in the cyber domain, in the actual. >> I mean, you mention that, but I mean, you look at Ukraine. I mean that cyber is a component of that war. I mean, it's very clear. I mean, that's new. We've never seen. this. >> And in my opinion, the stuff that we see happening in the Ukraine is small potatoes compared to what could happen. >> Yeah. >> So the US, we have a policy of strategic deterrence. Where we develop some of the most sophisticated cyber weapons in the world. We don't use them. And we hope never to use them. Because our adversaries, who could do stuff like, I don't know, wipe out every bank account in North America. Or turn off the lights in New York City. They know that if they were to do something like that, we could do something back. >> This is the red line conversation I want to go there. So, I had this discussion with Robert Gates in 2016 and he said, "We have a lot more to lose." Which is really your point. >> So this brand. >> I agree that there's to have freedom and liberty, you got to strike back with divorce. And that's been our way to balance things out. But with cyber, the red line, people are already in banks. So they're are operating below the red line line. Red line meaning before we know you're in there. So do we move the red line down because, hey, Sony got hacked. The movie. Because they don't have their own militia. >> Yeah. >> If their were physical troops on the shores of LA breaking into the file cabinets. The government would've intervened. >> I agree with you that it creates tension for us in the US because our adversaries don't have the clear delineation between public and private sector. Here you're very, very clear if you're working for the government. Or you work for an private entity. There's no ambiguity on that. >> Collaboration, Tom, and the vendor community. I mean, we've seen efforts to try to. >> That's a good question. >> Monetize private data and private reports. >> So at VMware, I'm very proud of the security capabilities we've built. But we also partner with people that I think of as direct competitors. We've got firewall vendors and Endpoint vendors that we work with and integrate. And so coopetition is something that exists. It's hard. Because when you have these kind of competing. So, could we do more? Of course we probably could. But I do think we've done a fair amount of cooperation, data sharing, product integration, et cetera. And as the threats get worse, you'll probably see us continue to do more. >> And the government is going to trying to force that too. >> And the government also drives standards. So let's talk about crypto. Okay. So there's a new form of encryption coming out called processing quantum. >> Quantum. Quantum computers have the potential to crack any crypto cipher we have today. That's bad. Okay. That's not good at all because our whole system is built around these private communications. So the industry is having conversations about crypto agility. How can we put in place the ability to rapidly iterate the ciphers in encryption. So, when the day quantum becomes available, we can change them and stay ahead of these quantum people. >> Well, didn't NIST just put out a quantum proof algo that's being tested right now by the community? >> There's a lot of work around that. Correct. And NIST is taking the lead on this, but Google's working on it. VMware's working on it. We're very, very active in how do we keep ahead of the attackers and the bad guys? Because this quantum thing is a, it's an x-ray machine. It's like a dilithium crystal that can power a whole ship. It's a really, really, really powerful tool. >> Bad things will happen. >> Bad things could happen. >> Well, Tom, great to have you on the theCube. Thanks for coming on. Take the last minute to just give a plug for what's going on for you here at VMWorld this year, just VMware Explore this year. >> Yeah. We announced a bunch of exciting things. We announced enhancements to our NSX family, with our advanced load balancer. With our edge firewall. And they're all in service of one thing, which is helping our customers make their private cloud like the public cloud. So I like to say 0, 0, 0. If you are in the cloud operating model, you have zero proprietary appliances. You have zero tickets to launch a workload. You have zero network taps and Zero Trust built into everything you do. And that's what we're working on. Pushing that further and further. >> Tom Gill, senior vices president, head of the networking at VMware. Thanks for coming on. We do appreciate it. >> Thanks for having us. >> Always getting the security data. That's killer data and security of the two ops that get the most conversations around DevOps and Cloud Native. This is The theCube bringing you all the action here in San Francisco for VMware Explore 2022. I'm John Furrier with Dave Vellante. Thanks for watching. (bright music)

>>Welcome back everyone Cube's live coverage here. Day two, two sets, three days of cube coverage here at VMware Explorer. This is our 12th year covering VMware's annual conference, formally called world I'm Jean Dave ante. We'd love seeing the progress and we've got great security comes Tom Gill, senior rights, president general manager, networking and advanced security business group at VMware. Great to see you. Thanks for coming on. Thanks >>For having me. Yeah, really happy we could have you on, you know, I think, I think this is my sixth edition on the cube. Like, do I get freaking flyer points or anything? >>Yeah, you get first get the VIP badge. We'll make that happen. You can start getting credits. >>Okay. There we go. >>We won't interrupt you. No, seriously, you got a great story in security here. The security story is kind of embedded everywhere, so it's not like called out and, and blown up and talked specifically about on stage. It's kind of in all the narratives in, in the VM world for this year. Yeah. But you guys have an amazing security story. So let's just step back into set context. Tell us the security story for what's going on here at VMware and what that means to this super cloud multi-cloud and ongoing innovation with VMware. Yeah, >>Sure thing. So, so probably the first thing I'll point out is that, that security's not just built in at VMware it's built differently, right? So we're not just taking existing security controls and cut and pasting them into, into our software. But we can do things because of our platform because of the virtualization layer that you really can't do with other security tools and where we're very, very focused is what we call lateral security or east west movement of an attacker. Cuz frankly, that's the name of the game these days. Right? Attackers, you gotta assume that they're already in your network. Okay. Already assume that they're there, then how do we make it hard for them to get to what the, the stuff that you really want, which is the data that they're, they're going after. Right. And that's where we, >>We really should. All right. So we've been talking a lot coming into world VMware Explorer and here the event about two things security as a state. Yeah. I'm secure right now. Yeah. Or I, I think I'm secure right now, even though someone might be in my network or in my environment to the notion of being defensible. Yeah. Meaning I have to defend and be ready at a moment's notice to attack, fight, push back red team, blue team, whatever you're gonna call it, but something's happening. I gotta be a to defend. Yeah. >>So you, what you're talking about is the principle of zero trust. So the, the, when we, when I first started doing security, the model was we have a perimeter and everything on one side of the perimeter is dirty, ugly, old internet and everything on this side known good, trusted what could possibly go wrong. And I think we've seen that no matter how good you make that perimeter, bad guys find a way in. So zero trust says, you know what? Let's just assume they're already in. Let's assume they're there. How do we make it hard for them to move around within the infrastructure and get to the really valuable assets? Cuz for example, if they bust into your laptop, you click on a link and they get code running on your machine. They might find some interesting things on your machine, but they're not gonna find 250 million credit cards. Right. Or the, the script of a new movie or the super secret aircraft plans, right. That lives in a database somewhere. And so it's that movement from your laptop to that database. That's where the damage is done. Yeah. And that's where VMware shines. If they don't >>Have the right to get to that database, they're >>Not >>In and it's not even just the right, like, so they're so clever. And so sneaky that they'll steal a credential off your machine, go to another machine, steal a credential off of that. So it's like they have the key to unlock each one of these doors and we've gotten good enough where we can look at that lateral movement, even though it has a credential and a key where like, wait a minute, that's not a real CIS admin making a change. That's ransomware. Yeah. Right. And that's, that's where we, you have to earn your way in. That's right. That's >>Right. Yeah. And we're all, there's all kinds of configuration errors. But also some, some I'll just user problems. I've heard one story where there's so many passwords and username and passwords and systems that the bad guy's scour, the dark web for passwords that have been exposed. Correct. And go test them against different accounts. Oh one hit over here. Correct. And people don't change their passwords all the time. Correct? Correct. That's a known, known vector. We, >>We just, the idea that users are gonna be perfect and never make mistake. Like how long have we been doing this? Like humans with the weakest link. Right. So, so, so people are gonna make mistakes. Attackers are gonna be in here's another way of thinking about it. Remember log for J. Remember that whole ago, remember that was a Christmas time. That was nine months ago. And whoever came up with that, that vulnerability, they basically had a skeleton key that could access every network on the planet. I don't know if a single customer that was said, oh yeah, I wasn't impacted by log for J. So seers, some organized entity had access to every network on the planet. What was the big breach? What was that movie script that got stolen? So there wasn't one. Right? We haven't heard anything. So the point is the goal of attackers is to get in and stay in. Imagine someone breaks into your house, steals your laptop and runs. That's a breach. Imagine someone breaks into your house and stays for nine months. Like it's untenable, the real world. Right, right. >>We don't even go in there. They're still in there >>Watching your closet. Exactly. Moving around, nibbling on your ni line, your cookies. You know what I mean? Drinking your beer. >>Yeah. So, so let's talk about how this translates into the new reality of cloud native, because now know you hear about, you know, automated pen testing is a, a new hot thing right now you got antivirus on data. Yeah. Is hot is hot within APIs, for instance. Yeah. API security. So all kinds of new hot areas, cloud native is very iterative. You know, you, you can't do a pen test every week. Right. You gotta do it every second. Right. So this is where it's going. It's not so much simulation. It's actually real testing. Right. Right. How do you view that? How does that fit into this? Cuz that seems like a good direction to me. >>Yeah. It, it, it fits right in. And you were talking to my buddy AJ earlier about what VMware can do to help our customers build cloud native applications with, with Zu, my team is focused on how do we secure those applications? So where VMware wants to be the best in the world is securing these applications from within looking at the individual piece parts and how they talk to each other and figuring out, wait a minute. That, that, that, that, that should never happen by like almost having an x-ray machine on the ins of the application. So we do it for both for VMs and for container based applications. So traditional apps are VM based. Modern apps are container based and we, and we have a slightly different insertion mechanism. It's the same idea. So for VMs, we do it with the hypervisor, with NSX, we see all the inner workings in a container world. >>We have this thing called a service me that lets us look at each little snippet of code and how they talk to each other. And once you can see that stuff, then you can actually apply. It's almost like common sense logic of like, wait a minute. You know, this API is giving back credit card numbers and it gives five an hour. All of a sudden, it's now asking for 20,000 or a million credit card that doesn't make any sense. Right? The anomalies stick out like a sore thumb. If you can see them. And VMware, our unique focus in the infrastructure is that we can see each one of these little transactions and understand the conversation. That's what makes us so good at that east west or lateral >>Security. Yeah. You don't belong in this room, get out or that that's right. Some weird call from an in-memory database, something over >>Here. Exactly. Where other, other security solutions won't even see that. Right. It's not like there algorithms aren't as good as ours or, or better or worse. It's that, it's the access to the data. We see the, the, the, the inner plumbing of the app. And therefore we can protect >>The app from, and there's another dimension that I wanna get in the table here, cuz to my knowledge only AWS, Google, I, I believe Microsoft and Alibaba and VMware have this, it nitro the equivalent of a nitro. Yes. Project Monterey. Yeah. That's unique. It's the future of computing architectures. Everybody needs a nitro. I've I've written about this. Yeah. Right. So explain your version. Yeah. Project. It's now real. It's now in the market right. Or soon will be. Yeah. Here. Here's our mission salient aspects. Yeah. >>Here's our mission of VMware is that we wanna make every one of our enterprise customers. We want their private cloud to be as nimble, as agile, as efficient as the public cloud >>And secure >>And secure. In fact, I'll argue, we can make it actually more secure because we're thinking about putting security everywhere in this infrastructure. Right. Not just on the edges of it. So, so, so, okay. How do we go on that journey? As you pointed out, the public cloud providers realized, you know, five years ago that the right way to build computers was not just a CPU and a GPU graphics process, unit GPU, but there's this third thing that the industry's calling a DPU data processing unit. So there's kind of three pieces of a computer. And the DPU is sometimes called a smart Nick it's the network interface card. It does all that network handling and analytics and it takes it off the CPU. So they've been building and deploying those systems themselves. That's what nitro is. And so we have been working with the major Silicon vendors to bring that architecture to everybody. So, so with vSphere eight, we have the ability to take the network processing that east west inspection. I talked about, take it off of the CPU and put it into this dedicated processing element called the DPU and free up the CPU to run the applications that AJ and team are building. >>So no performance degradation at all, correct. >>To CPU >>Offload. So even the opposite, right? I mean you're running it basically bare metal speeds. >>Yes, yes. And yes. >>And, and, and you're also isolating the, the storage right from the, from the, the, the security, the management. And >>There's an isolation angle to this, which is that firewall that we're putting everywhere. Not just that the perimeter, we put it in each little piece of the server is running when it runs on one of these DPU, it's a different memory space. So even if, if an attacker gets to root in the OS, they it's very, very, never say never, but it's very difficult. >>So who has access to that? That, that resource >>Pretty much just the infrastructure layer, the cloud provider. So it's Google Microsoft, you know, and the enterprise, the >>Application can't get in, >>Can't get in there. Cause it, you would've to literally bridge from one memory space to another, never say never, but it would be very, very, >>It hasn't earned the trust >>To get it's more than Bob wire. It's, it's, it's multiple walls and, and >>It's like an air gap. It puts an air gap in the server itself so that if the server's compromised, it's not gonna get into the network really powerful. >>What's the big thing that you're seeing with this super cloud transition we're seeing, we're seeing, you know, multicloud and this new, not just SAS hosted on the cloud. Yeah. You're seeing a much different dynamic of combination of large scale CapEx, cloud native. And then now cloud native develops on premises and edge kind of changing what a cloud looks like if the cloud's on a cloud. So rubber customer, I'm building on a cloud and I have on-prem stuff. So I'm getting scale CapEx relief from the, from the cap, from the hyperscalers. >>I, I think there's an important nuance on what you're talking about, which is, is in the early days of the cloud customers. Remember those first skepticism? Oh, it'll never work. Oh, that's consumer grade. Oh, that's not really gonna work. And some people realize >>It's not secure. Yeah. >>It, it's not secure that one's like, no, no, no, it's secure. It works. And it, and it's good. So then there was this sort of over rush. Like let's put everything on the cloud. And I had a lot of customers that took VM based applications said, I'm gonna move those onto the cloud. You gotta take 'em all apart, put 'em on the cloud and put 'em all back together again. And little tiny details, like changing an IP address. It's actually much harder than it looks. So my argument is for existing workloads for VM based workloads, we are VMware. We're so good at running VM based workloads. And now we run them on anybody's cloud. So whether it's your east coast data center, your west coast data center, Amazon, Google, Microsoft, Alibaba, IBM keep going. Right. We pretty much every, and >>The benefit of the customer is what you >>Can literally vMotion and just pick it up and move it from private to public public, to private, private, to public, public, back and forth. >>Remember when we called VMO BS years ago. Yeah, yeah, yeah. >>We were really, skeptic is >>Powerful. We were very skeptical. We're like, that'll never happen. I mean, we were, I mean, it's supposed to be pat ourselves on the back. We, well, >>Because it's alchemy, it seems like what you can't possibly do that. Right. And so, so, so, and now we do it across clouds, right? So we can, you know, it's not quite VMO, but it's the same idea. You can just move these things over. I have one customer that had a production data center in the Ukraine, things got super tense, super fast, and they had to go from their private cloud data center in the Ukraine to a public cloud data center outta harm's way. They did it over a weekend, 48 hours. If you've ever migrated data, that's usually six months, right? And a lot of heartburn and a lot of angst, boom. They just drag and drop, moved it on over. That's the power of what we call the cloud operating model. And you can only do this when all your infrastructure's defined in software. >>If you're relying on hardware, load, balancers, hardware, firewalls, you can't move those. They're like a boat anchor. You're stuck with them. And by the way, really, really expensive. And by the way, they eat a lot of power, right? So that was an architecture from the nineties in the cloud operating model, your data center. And this goes back to what you were talking about is just racks and racks of X 86 with these magic DPU or smart necks to make any individual node go blisteringly fast and do all the functions that you used to do in network appliances. >>We just said, AJ taking us to school and everyone else to school on applications, middleware abstraction layer. Yeah. And kit Culver was also talking about this across cloud. We're talking super cloud, super pass. If this continues to happen, which we would think it will happen. What does the security posture look like? It has. It feels to me. And again, this is, this is your wheelhouse. If super cloud happens with this kind of past layer where there's B motioning going on, all kinds of yeah. Spanning applications and data. Yeah. Across environments. Yeah. Assume there's an operating system working on behind the scenes. Right. What's the security posture in all this. Yeah. >>So remember my narrative about like VA guys are getting in and they're moving around and they're so sneaky that they're using legitimate pathways. The only way to stop that stuff is you've gotta understand it at what, you know, we call layer seven at the application layer the in, you know, trying to do security, the infrastructure layer. It was interesting 20 years ago, kind of less interesting 10 years ago. And now it's becoming irrelevant because the infrastructure is oftentimes not even visible, right. It's buried in some cloud provider. So layer seven, understanding, application awareness, understanding the APIs and reading the content. That's the name of the game in security. That's what we've been focused on. Right. Nothing to do with >>The infras. And where's the progress bar on that, that paradigm early one at the 10, 10 being everyone's doing it >>Right now. Well, okay. So we, as a vendor can do this today. All the stuff I talked about about reading APIs, understanding the, the individual services looking at, Hey, wait a minute. This credit card anomalies, that's all shipping production code. Where is it in customer adoption life cycle, early days, 10%. So, so there's a whole lot of headroom. We, for people to understand, Hey, I can put these controls in place. There's software based. They don't require appliances. It's layer seven. So it has contextual awareness and it's works on every single cloud. >>You know, we talk about the pandemic. Being an accelerator really was a catalyst to really rethink. Remember we used to talk about pat his security a do over. He's like, yes, if it's the last thing I'm due, I'm gonna fix security. Well, he decided to go try to fix Intel instead, but, >>But, but he's getting some help from the government, >>But it seems like, you know, CISOs have totally rethought, you know, their security strategy. And, and at least in part is a function of the pandemic. >>When I started at VMware four years ago, pat sat me down in his office and he said to me what he said to you, which is like Tom, he said, I feel like we have fundamentally changed servers. We fundamentally changed storage. We fundamentally changed networking. The last piece of the puzzle of security. I want you to go fundamentally change it. And I'll argue that the work that we're doing with this, this horizontal security understanding the lateral movement east west inspection, it fundamentally changes how security works. It's got nothing to do with firewalls. It's got nothing to do with endpoint. It's a unique capability that VMware is uniquely suited to deliver on. And so pat, thanks for the mission. We delivered it and available >>Those, those wet like web applications firewall for instance are, are around. I mean, but to your point, the perimeter's gone. Exactly. And so you gotta get, there's no perimeter. So it's a surface area problem. Correct. And access and entry, correct. They're entering here easy from some manual error or misconfiguration or bad password that shouldn't be there. They're >>In. Think about it this way. You put the front door of your house, you put a big strong door and a big lock. That's a firewall bad guys, come in the window. Right. And >>Then the window's open and the window with a ladder room. Oh my >>God. Cause it's hot, bad user behavior. Trump's good security >>Every time. And then they move around room to room. We're the room to room people. Yeah. We see each little piece of the thing. Wait, that shouldn't happen. Right. >>I wanna get you a question that we've been seeing and maybe we're early on this, or it might be just a, a false data point. A lot of CSOs and we're talking to are, and people in industry in the customer environment are looking at CSOs and CSOs, two roles, chief information security officer, and then chief security officer Amazon, actually, Steven Schmidt is now CSO at reinforced. They actually called that out. Yeah. And the, and the interesting point that he made, we've had some other situations that verified. This is that physical security is now tied to online to your point about the service area. If I get a password, I still at the keys to the physical goods too. Right. Right. So physical security, whether it's warehouse for them is, or store or retail digital is coming in there. Yeah. So is there a CSO anymore? Is it just CSO? What's the role or are there two roles you see that evolving or is that just, >>Well, >>I circumstance, >>I, I think it's just one. And I think that, that, you know, the stakes are incredibly high in security. Just look at the impact that these security attacks are having on it. It, you know, companies get taken down, Equifax market cap was cut, you know, 80% with a security breach. So security's gone from being sort of a nuisance to being something that can impact your whole kind of business operation. And then there's a whole nother domain where politics get involved. Right. It determines the fate of nations. I know that sounds grand, but it's true. Yeah. And so, so, so companies care so much about it. They're looking for one liter, one throat to choke, you know, one person that's gonna lead security in the virtual domain, in the physical domain, in the cyber domain, in, in, you know, in the actual, well, it is, >>I mean, you mentioned that, but I mean, mean you look at Ukraine. I mean the, the, that, that, that cyber is a component of that war. I mean, that's very clear. I mean, that's, that's new, we've never seen >>This. And in my opinion, the stuff that we see happening in the Ukraine is small potatoes compared to what could happen. Yeah, yeah. Right. So the us, we have a policy of, of strategic deterrents where we develop some of the most sophisticated cyber weapons in the world. We don't use them and we hope never to use them because the, the, our adversaries who could do stuff like, oh, I don't know, wipe out every bank account in north America, or turn off the lights in New York city. They know that if they were to do something like that, we could do something back. >>I, this discuss, >>This is the red line conversation I wanna go there. So >>I had this discussion with Robert Gates in 2016 and he said, we have a lot more to lose, which is really >>Your point. So this brand, so I agree that there's the, to have freedom and Liberty, you gotta strike back with divorce and that's been our way to, to balance things out. Yeah. But with cyber, the red line, people are already in banks. So they're addresses are operating below the red line, red line, meaning before we know you're in there. So do we move the red line down because Hey, Sony got hacked the movie because they don't have their own militia. Yeah. If they were physical troops on the shores of LA breaking into the file cabinets. Yeah. The government would've intervened. >>I, I, I agree with you that it creates, it creates tension for us in the us because our, our adversaries don't have the clear delineation between public and private sector here. You're very, very clear if you're working for the government or you work for an private entity, there's no ambiguity on that. And so, so we have different missions in each department. Other countries will use the same cyber capabilities to steal intellectual, you know, a car design as they would to, you know, penetrate a military network. And that creates a huge hazard for us on the us. Cause we don't know how to respond. Yeah. Is that a civil issue? Is that a, a, a military issue? And so, so it creates policy ambiguity. I still love the clarity of separation of, you know, sort of the various branches of government separation of government from, >>But that, but, but bureau on multinational corporation, you then have to, your cyber is a defensible. You have to build the defenses >>A hundred percent. And I will also say that even though there's a clear D mark between government and private sector, there's an awful lot of cooperation. So, so our CSO, Alex toshe is actively involved in the whole intelligence community. He's on boards and standards and we're sharing because we have a common objective, right? We're all working together to fight these bad guys. And that's one of the things I love about cyber is that that even direct competitors, two big banks that are rivals on the street are working together to share security information and, and private, is >>There enough? Is collaboration Tom in the vendor community? I mean, we've seen efforts to try to, that's a good question, monetize private data, you know? Yeah. And private reports and, >>And, you know, like, so at VMware, we, we, I'm very proud of the security capabilities we've built, but we also partner with people that I think of as direct competitors, we've got firewall vendors and endpoint vendors that we work with and integrate. And so cooperation is something that exists. It's hard, you know, because when you have these kind of competing, you know, so could we do more? Of course we probably could, but I do think we've done a fair amount of cooperation, data sharing, product integration, et cetera, you know, and, you know, as the threats get worse, you'll probably see us continue to do more. >>And the governments is gonna trying to force that too. >>And, and the government also drives standards. So let's talk about crypto. Okay. So there's a new form of encryption coming out called quantum processing, calling out. Yeah. Yeah. Quantum, quantum computers have the potential to crack any crypto cipher we have today. That's bad. Okay. Right. That's not good at all because our whole system is built around these private communications. So, so the industry is having conversations about crypto agility. How can we put in place the ability to rapidly iterate the ciphers in encryption? So when the day quantum becomes available, we can change them and stay ahead of these quantum people. Well, >>Didn't this just put out a quantum proof algo that's being tested right now by the, the community. >>There's a lot of work around that. Correct. And, and, and this is taking the lead on this, but you know, Google's working on it, VMware's working on it. We're very, very active in how do we keep ahead of the attackers and the bad guys? Because this quantum thing is like a, it's a, it's a x-ray machine. You know, it's like, it's like a, a, a di lithium crystal that can power a whole ship. Right. It's a really, really, really powerful >>Tool. It's bad. Things will happen. >>Bad things could happen. >>Well, Tom, great to have you on the cube. Thanks for coming. Take the last minute to just give a plug for what's going on for you here at world this year, VMware explore this year. Yeah. >>We announced a bunch of exciting things. We announced enhancements to our, our NSX family, with our advanced load balancer, with our edge firewall. And they're all in service of one thing, which is helping our customers make their private cloud like the public cloud. So I like to say 0, 0, 0. If you are in the cloud operating model, you have zero proprietary appliances. You have zero tickets to launch a workload. You have zero network taps and zero trust built into everything you do. And that's, that's what we're working on and pushing that further and further. >>Tom Gill, senior vices president head of the networking at VMware. Thanks for coming up for you. Appreciate >>It. Yes. Thanks for having guys >>Always getting the security data. That's killer data and security of the two ops that get the most conversations around dev ops and cloud native. This is the queue bringing you all the action here in San Francisco for VMware. Explore 2022. I'm John furrier with Dave, Alan. Thanks for watching.

(upbeat music) >> Hi, I'm Joe Rodriguez, Managing Director of Financial Services at Cloudera. Welcome to the Fight Fraud with Data session. At Cloudera we believe that fighting fraud begins with data. So financial services is Cloudera's largest industry vertical. We have approximately 425 global financial services customers, which consists of 82 out of a hundred of the largest global banks of which we have 27 that are globally systemic banks. Four out of the five top stock exchanges, eight out of the top 10 wealth management firms and all four of the top credit card networks. So as you can see, most financial services institutions utilize Cloudera for data analytics and machine learning. We also have over 20 central banks and a dozen or so financial regulators. So it's an incredible footprint which gives Cloudera lots of insight into the many innovations that our customers are coming up with. Criminals can steal thousands of dollars before a fraudulent transaction is detected. So the cost to purchase your account data is well worth the price to fraudsters. According to Experian, credit and a debit card account information sells on the dark web for a mere $5 with the CVV number and up to $110 if it comes with all the bank information, including your name, social security number, date of birth, complete account numbers, and other personal data. Our customers have several key data and analytics challenges when it comes to fighting financial crime. The volume of data that they need to deal with is huge and growing exponentially. All this data needs to be evaluated in real time. There are new sources of streaming data that need to be integrated with existing legacy data sources. This includes biometrics data and enhanced authentication video surveillance, call center data, and of course all that needs to be integrated with existing legacy data sources. There is an analytics Arms Race between the banks and the criminals, and the criminal networks never stop innovating. They also have to deal with disjointed security and governance. Security and governance policies are often set per data source or application requiring redundant work across workloads. And they have to deal with siloed environments. The specialized nature of platforms and people results in disparate data sources and data management processes. This duplicates efforts and divides the business risk and crime teams, limiting collaboration opportunities between them. CDP enhances financial crime solutions to be holistic by eliminating data gaps between siloed solutions, with an enterprise data approach, advanced data analytics and machine learning. By deploying an enterprise wide data platform, you reduce siloed divisions between business risk and crime teams and enable better collaboration through industrialized machine learning, you tighten up the loop between detection and new fraud patterns. Cloudera provides the data platform on which a best of breed applications can run and leverage integrated machine learning. Cloudera stands rather than replaces your existing fraud modeling applications. So Oracle, SAS, Actimize, to name a few, integrate with an enterprise data hub to scale the data, increase speed and flexibility and improve efficacy of your entire fraud system. It also centralizes the fraud workload on data that can be used for other use cases in applications like Enhanced KYC and Customer 360 for example. I just wanted to highlight a couple of our partners in financial crime prevention, Simudyne and Quantexa. So Simudyne provides fraud simulation using agent-based modeling machine learning techniques to generate synthetic transaction data. This data simulates potential fraud scenarios in a cost-effective GDPR-compliant virtual environment to significantly improve financial crime detection systems. Simudyne identifies future fraud topologies for millions of simulations that can be used to dynamically train new machine learning algorithms for enhanced identification. And Quantexa connects the dots within your data using dynamic entity resolution, and advanced network analytics to create context around your customers. This enables you to see the bigger picture and automatically assesses potential criminal behavior. Now let's go over some of our customers and how they're using Cloudera. First, we'll talk about United Overseas Bank or UOB. UOB is a leading full service bank in Asia with a network of more than 500 offices in 19 countries and territories, in Asia Pacific, Western Europe and North America. UOB built a modern data platform on Cloudera that gives it the flexibility and speed to develop new AI and machine learning solutions and to create a data-driven enterprise. UOB set up it's big data analytics center in 2017. It was Singapore's first centralized big data unit within a bank to deepen the bank's data analytic capabilities and to use data insights to enhance the bank's performance. Essential to this work was implementing a platform that could cost efficiently bring together data from dozens of separate systems and incorporate a range of unstructured data, including voice and text. Using Cloudera CDP and machine learning, UOB gained a richer understanding of its customer preferences to help make their banking experience simpler, safer, and more reliable. Working with Cloudera, UOB has a big data platform that gives business staff and data scientists, faster access to relevant and quality data for self-service analytics, machine learning and emerging artificial intelligence solutions. With new self-service analytics and machine learning driven insights, UOB has realized improvements in digital banking, asset management, compliance, AML, and more. Advanced AML detection capabilities, help analysts detect suspicious transactions either based on hidden relationships of shell companies and high risk individuals with Cloudera and machine learning technologies, UOB was able to enhance AML detection and reduce the time to identify new links from months to three weeks. Next, let's speak about MasterCard. So MasterCard's principle business is to process payments between banks and merchants and the credit issuing banks and credit unions of the purchasers who use the MasterCard brand debit and credit cards to make purchases. MasterCard chose Cloudera Enterprise for fraud detection and to optimize their DW infrastructure, delivering deep insights and best practices and big data security and compliance. Next, let's speak about Bank Rakyat in Indonesia or BRI. BRI is one of the largest and oldest banks in Indonesia and engages in the provision of general banking services. It's headquartered in Jakarta, Indonesia. BRI is well-known for its focus on microfinancing initiatives and serves over 75 million customers through its more than 11,000 offices and rural service outposts. BRI required better insight to understand customer activity and identify fraudulent transactions. The bank needed a solid foundation that allowed it to leverage the power of advanced analytics, artificial intelligence, and machine learning to gain better understanding of customers and the market. BRI used Cloudera Enterprise data platform to build an agile and reliable, predictive augmented intelligence solution to enhance its credit scoring system. And to address the rising concern around data security from regulators and customers, BRI developed a real-time fraud detection service powered by Cloudera and Kafka, BRI's data scientists developed a machine learning model for fraud detection by creating a behavioral scoring model based on customer savings, loan transactions, deposits, payroll and other financial real-time data. This led to improvements in its fraud detection and credit scoring capabilities, as well as the development of a new digital microfinancing product. With the enablement of real-time fraud detection, BRI was able to reduce the rate of fraud by 40%. It improved relationship manager productivity by two and a half fold. It improved the credit scoring system to cut down on micro-financing loan processing times from two weeks to two days to now two minutes. So fraud prevention is a good area to start with data focus if you haven't already. It offers a quick return on investment and it's a focused area that's not too entrenched across the company. To learn more about fraud prevention, go to www.cloudera.com, and you should schedule a meeting with Cloudera to learn even more. And with that, thank you for listening and thank you for your time. (upbeat music)

>>from around the globe. It's the Cube covering space and cybersecurity. Symposium 2020 hosted by Cal Poly. Yeah, Lauren, Welcome to the Space and Cybersecurity Symposium 2020 put on by Cal Poly and hosted with Silicon Angle acute here in Palo Alto, California for a virtual conference. Couldn't happen in person this year. I'm John for a year. Host the intersection of space and cybersecurity. I'll see critical topics, great conversations. We got a great guest here to talk about the addressing the cybersecurity workforce gap, and we have a great guest, a feature speaker. Stewart Knox, the undersecretary with California's Labor and Workforce Development Office. Stewart Thanks for joining us today. >>Thank you so much, John. Appreciate your time today and listening to a little bit of our quandaries with making sure that we have the security that's necessary for the state of California and making sure that we have the work force that is necessary for cybersecurity in space. >>Great, I'd love to get started. I got a couple questions for you, but first take a few minutes for an opening statement to set the stage. >>Sure, realizing that in California we lead the nation in much of cybersecurity based on Department of Defense contractors within the Santa California leading the nation with over $160 billion within the industry just here in California alone and having over 800,000 bus workers. Full time employment in the state of California is paramount for us to make sure that we face, um, defense manufacturers approximate 700,000 jobs that are necessary to be filled. There's over 37,000 vacancies that we know of in California, just alone in cybersecurity. And so we look forward to making sure that California Workforce Development Agency is leading the charge to make sure that we have equity in those jobs and that we are also leading in a way that brings good jobs to California and to the people of California, a good education system that is developed in a way that those skills are necessarily met for the for the employers here in California and the nation, >>One of the exciting things about California is obviously look at Silicon Valley, Hewlett Packard in the garage, storied history space. It's been a space state. Many people recognize California. You mentioned defense contractors. It's well rooted with with history, um, just breakthroughs bases, technology companies in California. And now you've got technology. This is the cybersecurity angle. Um, take >>them into >>Gets more commentary to that because that's really notable. And as the workforce changes, these two worlds are coming together, and sometimes they're in the same place. Sometimes they're not. This is super exciting and a new dynamic that's driving opportunities. Could you share, um, some color commentary on that dynamic? >>Absolutely. And you're so correct. I think in California we lead the nation in the way that we developed programs that are companies lead in the nation in so many ways around, uh, cyberspace cybersecurity, Uh, in so many different areas for which in the Silicon Valley is just, uh, such a leader in those companies are good qualified companies to do so. Obviously, one of the places we play a role is to make sure that those companies have a skilled workforce. Andi, also that the security of those, uh, systems are in place for our defense contractors onda For the theater companies, those those outlying entities that are providing such key resource is to those companies are also leading on the cutting edge for the future. Also again realizing that we need to expand our training on skills to make sure that those California companies continue to lead is just, um, a great initiative. And I think through apprenticeship training programs on By looking at our community college systems, I think that we will continue to lead the nation as we move forward. >>You know, we've had many conversations here in this symposium, virtually certainly around. The everyday life of consumer is impacted by space. You know, we get our car service Uber lyft. We have maps. We have all this technology that was born out of defense contracts and r and D that really changed generations and create a lot of great societal value. Okay, now, with space kind of on the next generation is easier to get stuff into space. The security of the systems is now gonna be not only paramount for quality of life, but defending that and the skills are needed in cybersecurity to defend that. And the gap is there. What >>can we >>do to highlight the opportunities for career paths? It used to be the day when you get a mechanical engineering degree or aerospace and you graduated. You go get a job. Not anymore. There's a variety of of of paths career wise. What can we do to highlight this career path? >>Absolutely correct. And I think it starts, you know, k through 12 system on. I know a lot of the work that you know, with this bow and other entities we're doing currently, uh, this is where we need to bring our youth into an age where they're teaching us right as we become older on the uses of technology. But it's also teaching, um, where the levels of those education can take them k through 12. But it's also looking at how the community college system links to that, and then the university system links above and beyond. But it's also engage in our employers. You know, One of the key components, obviously, is the employers player role for which we can start to develop strategies that best meet their needs quickly. I think that's one of the comments we hear the most labor agency is how we don't provide a change as fast as we should, especially in technology. You know, we buy computers today, and they're outdated. Tomorrow it's the same with the technology that's in those computers is that those students are going to be the leaders within that to really develop how those structures are in place. S O. K. Through 12 is probably primary place to start, but also continuing. That passed the K 12 system and I bring up the employers and I bring them up in a way, because many times when we've had conversations with employers around what their skills needs were and how do we develop those better? One of the pieces that of that that I think is really should be recognized that many times they recognized that they wanted a four year degree, potentially or five year, six year degree. But then, when we really looked at the skill sets, someone coming out of the community college system could meet those skill sets. And I think we need to have those conversations to make sure not that they shouldn't be continue their education. They absolutely should. Uh, but how do we get those skill sets built into this into 12 plus the two year plus the four year person? >>You know, I love the democratization of these new skills because again. There's no pattern matching because they weren't around before, right? So you gotta look at the exposure to your point K through 12 exposure. But then there's an exploration piece of whether it's community, college or whatever progression. And sometimes it's nonlinear, right? I mean, people are learning different ways, combining the exposure and the exploration. That's a big topic. Can you share your view on this because this now opens up mawr doors for people choice. You got new avenues. You got online clock and get a cloud computing degree now from Amazon and walk in and help. I could be, you know, security clearance, possibly in in college. So you know you get exposure. Is there certain things you see? Is it early on middle school? And then I'll see the exploration Those air two important concepts. Can you unpack that a little bit exposure and exploration of skills? >>Absolutely. And I think this takes place, you know, not only in in the K 12 because somebody takes place in our community colleges and universities is that that connection with those employers is such a key component that if there's a way we could build in internships where experiences what we call on the job training programs apprenticeship training pre apprenticeship training programs into a design where those students at all levels are getting an exposure to the opportunities within the Space and Cybersecurity Avenue. I think that right there alone will start to solve a problem of having 37 plus 1000 openings at any one time in California. Also, I get that there's there's a burden on employers. Thio do that, and I think that's a piece that we have to acknowledge. And I think that's where education to play a larger role That's a place we had. Labor, Workforce, Development Agency, player role With our apprenticeship training programs are pre apprenticeship training programs. I could go on all day of all of our training programs that we have within the state of California. Many of the list of your partners on this endeavor are partners with Employment Training Panel, which I used to be the director of the Brown administration of um, That program alone does incumbent worker training on DSO. That also is an exposure place where ah worker, maybe, you know, you know, use the old adage of sweeping the floors one day and potentially, you know, running a large portion of the business, you know, within years. But it's that exposure that that employee gets through training programs on band. Acknowledging those skill sets and where their opportunities are, is what's valid and important. I think that's where our students we need to play a larger role in the K 12. That's a really thio Get that pushed out there. >>It's funny here in California you're the robotics clubs in high school or like a varsity sport. You're seeing kids exposed early on with programming. But you know, this whole topic of cybersecurity in space intersection around workforce and the gaps and skills is not just for the young. Certainly the young generations gotta be exposed to the what the careers could be and what the possible jobs and societal impact and contributions what they could be. But also it's people who are already out there. You know, you have retraining re Skilling is plays an important role. I know you guys do a lot of thinking on this is the under secretary. You have to look at this because you know you don't wanna have a label old and antiquated um systems. And then a lot of them are, and they're evolving and they're being modernized by digital transformation. So what does the role of retraining and skill development these programs play? Can you share what you guys are working on in your vision for that? >>Absolutely. That's a great question. And I think that is where we play a large role, obviously in California and with Kobe, 19 is we're faced with today that we've never seen before, at least in my 27 years of running program. Similar Thio, of course, in economic development, we're having such a large number of people displaced currently that it's unprecedented with unemployment rates to where we are. We're really looking at How do we take? And we're also going to see industries not return to the level for which they stood at one point in time. Uh, you know, entertainment industries, restaurants, all the alike, uh, really looking at how do we move people from those jobs that were middle skill jobs, topper skilled jobs? But the pay points maybe weren't great, potentially, and there's an opportunity for us to skill people into jobs that are there today. It may take training, obviously, but we have dollars to do that generally, especially within our K 12 and are que 14 systems and our universities. But we really wanna look at where those skill sets are are at currently. And we want to take people from that point in time where they said today, and try to give them that exposure to your point. Earlier question is, how do we get them exposed to a system for which there are job means that pay well with benefit packages with companies that care about their employees? Because that's what our goal is. >>You know. You know, I don't know if you have some visibility on this or ah opinion, but one observation that I've had and talking to whether it's a commercial or public sector is that with co vid uh, there have been a lot of awareness of the situation. We're adequately prepared. There's, um, readiness. But as everyone kind of deals with it, they're also starting to think about what to do. Post covert as we come out of it, Ah, growth strategy for a company or someone's career, um, people starting to have that on the top of their minds So I have to ask you, Is there anything that you see that they say? Okay, certain areas, maybe not doubling down on other areas. We're gonna double down on because we've seen some best practices on a trajectory of value for coming out of co vid with, you know, well, armed skills or certain things because you because that's what a lot of people are thinking right now. It's probably cyber is I mean, how many jobs are open? So you got well, that that's kind of maybe not something double down on here are areas we see that are working. Can you share your current visibility to that dynamic? >>Absolutely. Another great question. One of the key components that we look at Labor Workforce Development Agency. And so look at industries and growth modes and ones that are in decline boats. Now Kobe has changed that greatly. We were in a growth rate for last 78 years. We saw almost every industry might miss a few. You know that we're all in growth in one way or enough, obviously, that has changed. Our landscape is completely different than we saw 67 months ago. So today we're looking at cybersecurity, obviously with 30 plus 1000 jobs cos we're looking at Defense Department contractor is obviously with federal government contracts. We were looking at the supply chains within those we're looking at. Health care, which has always been one, obviously are large one of our large entities that has has grown over the years. But it's also changed with covered 19. We're looking at the way protective equipment is manufactured in the way that that will continue to grow over time. We're looking at the service industry. I mean, it will come back, but it won't come back the way we've seen it, probably in the past, but where the opportunities that we develop programs that we're making sure that the skill sets of those folks are transferrable to other industries with one of the issues that we face constant labor and were forced moment programs is understanding that over the period of time, especially in today's world again, with technology that people skill sets way, don't see is my Parents Day that you worked at a job for 45 years and you retired out of one job. Potentially, that is, that's been gone for 25 years, but now, at the pace for which we're seeing systems change. This is going to continue to amp up. I will stay youth of today. My 12 year old nephew is in the room next door to me on a classroom right now online. And so you know, there. It's a totally different atmosphere, and he's, you know, enjoying actually being in helping learning from on all online system. I would not have been able to learn that way, but I think we do see through the K Through 12 system where we're moving, um, people's interest will change, and I think that they will start to see things in a different way than we have in the past. They were forced systems. We are an old system been around since the thirties. Some even will say prior to the thirties came out of the Great Depression in some ways, and that system we have to change the way we develop our programs are should not be constant, and it should be an evolving system. >>It's interesting a lot of the conversation between the private and public partnerships and industry. You're seeing an agile mind set where it's a growth mindset. It's also reality based mindset and certainly space kind of forces. This conversation with cyber security of being faster, faster, more relevant, more modern. You mentioned some of those points, and with co vid impact the workforce development, it's certainly going to put a lot of pressure on faster learning. And then you mentioned online learning. This has become a big thing. It's not just putting education online per se. There's new touch points. You know you got APS, you got digital. This digital transformation is also accelerating. How do you guys view the workforce development? Because it's going to be open. It's gonna be evolving. There's new data coming in, and maybe kids don't want to stare at a video conference. Is there some game aspect to it? Is there how do you integrate thes new things that are coming really fast? And it's happening kind of in real time in front of our eyes. So I love to get your thoughts on how you guys see that, because it will certainly impact their ability to compete for jobs and or to itself learn. >>I think one of the key components of California's our innovation right and So I think one of the things that we pride ourselves in California is around that, um that said, that is the piece that I think the Silicon Valley and there's many areas in California that that have done the same, um, or trying to do the same, at least in their economy, is to build in innovation. And I think that's part of the K through 12 system with our with our our state universities and our UCS is to be able to bridge that. I think that you we see that within universities, um, that really instill an innovative approach to teaching but also instill innovation within their students. I'm not sure there yet with our fully with our K 12 system. And I think that's a place that either our community colleges could be a bridge, too, as well. Eso that's one component of workforce development I think that we look at as being a key. A key piece you brought up something that's really interesting to me is when you talk about agile on day, one of the things that even in state government on this, is gonna be shocking to you. But we have not been an agile system, Aziz. Well, I think one of the things that the Newsome administration Governor Newsom's administration has brought is. And when I talk about agile systems, I actually mean agile systems. We've gone from Kobol Systems, which are old and clunky, still operating. But at the same time, we're looking at upgrading all of our systems in a way that even our technology in the state of California should be matching the technology that our great state has within our our state. So, um, there in lies. It's also challenges of finding the qualified staff that we need in the state of California for all of our systems and servers and everything that we have. Um, currently. So you know, not only are we looking at external users, users of labor, workforce development, but we're looking at internal users that the way we redevelop our systems so that we are more agile in two different ways. >>You just got me. I triggered with COBOL. I programmed in the eighties with COBOL is only one credit lab in college. Never touched it again. Thank God. But this. But this >>is the >>benefit of cloud computing. I think this is at the heart, and this is the undertone of the conference and symposium is cloud computing. You can you can actually leverage existing resource is whether there legacy systems because they are running. They're doing a great job, and they do a certain work load extremely well. Doesn't make sense to replace what does a job, but you can integrate it in this. What cloud does this is Opening up? Can mawr more and more capabilities and workloads? This is kind of the space industry is pointing to when they say we need people that can code. And that could solve data problems. Not just a computer scientist, but a large range of people. Creative, um, data, science, everything. How does California's workforce solve the needs of America's space industry? This is because it's a space state. How do you see that? Let your workforce meeting those needs. >>Yeah, I think I think it's an investment. Obviously, it's an investment on our part. It's an investment with our college partners. It's an investment from our K 12 system to make sure that that we are allocating dollars in a way through meeting the demand of industry Onda, we do look at industry specific around there needs. Obviously, there's a large one. We wanna be very receptive and work with our employers and our employee groups to make sure that we need that demand. I think it's putting our money where our mouth is and and designing and working with employer groups to make sure that the training meets their needs. Um, it's also working with our employer groups to make sure that the employees are taken care of. That equity is built within the systems, Um, that we keep people employed in California on their able to afford a home, and they're able to afford a life here in California. But it's also again, and I brought up the innovation component. I think it's building an innovation within systems for which they are employers but are also our incoming employees are incumbent workers. And you brought this up earlier. People that already employed and people that are unemployed currently with the skill set that might match up, is how do we bridge those folks into employment that they maybe have not thought about. We have a whole career network of systems out throughout the city, California with the Americans job Centers of California on day will be working, and they already are working with a lot of dislocated workers on day. One of the key components of that is to really look at how do we, um, take what their current skills that might be and then expose them to a system for which we have 37 plus 1000 job openings to Andi? How do we actually get those books employed? It's paying for potentially through those that local Workforce Innovation Opportunity Act, funding for Americans job centers, um, to pay for some on the job, training it Z to be able to pay for work experiences. It's to be able to pay for internships for students, um, to get that opportunity with our employers and also partner with our employers that they're paying obviously a percentage of that, too. >>You know, one of the things I've observed over my, um, career 54 times around the sun is you know, in the old days when I was in college in school, you had career people have longer jobs, as you mentioned. Not like that anymore. But also I knew someone I'm gonna be in line to get that job, maybe nepotism or things of that nature. Now the jobs have no historical thing or someone worked longer in a job and has more seniority. Ah, >>lot of these >>jobs. Stewart don't HAVA requirements like no one's done them before. So the ability for someone who, um, is jumping in either from any college, there's no riel. It's all level set. It's like complete upside down script here. It's not like, Oh, I went to school. Therefore I get the job you could be Anyone could walk into these careers because the jobs air so new. So it's not where you came from or what school you went to or your nationality or gender. The jobs have been democratized. They're not discriminating against people with skills. So this opens up mawr. How >>do you >>see that? Because this really is an opportunity for this next generation to be more diverse and to be mawr contributed because diversity brings expertise and different perspectives. Your thoughts on that? >>Absolutely. And that was one of the things we welcome. Obviously we want to make sure that that everybody is treated equally and that the employers view everyone as employer employer of choice but an employee of choices. Well, we've also been looking at, as I mentioned before on the COVITZ situation, looking at ways that books that are maybe any stuck in jobs that are don't have a huge career pathway or they don't have a pathway out of poverty. I mean, we have a lot of working for people in the state of California, Um, that may now do to cope and lost their employment. Uh, this, you know, Let's let's turn back to the old, you know? Let's try, eliminate, eliminate, eliminate. How do we take those folks and get them employed into jobs that do have a good career pathway? And it's not about just who you knew or who you might have an in with to get that job. It is based on skills, I think, though that said there we need to have a better way to actually match those jobs up with those employers. And I think those are the long, ongoing conversations with those employer groups to make sure that one that they see those skill sets is valid and important. Um, they're helping design this crew sets with us, eh? So that they do match up and that were quickly matching up those close skills. That so that we're not training people for yesterday skills. >>I think the employer angles super important, but also the educators as well. One of the things that was asked in another question by the gas they they said. She said The real question to ask is, how early do you start exposing the next generation? You mentioned K through 12. Do you have any data or insight into or intuition or best practice of where that insertion point is without exposure? Point is, is that middle school is a elementary, obviously high school. Once you're in high school, you got your training. Wheels are off, you're off to the races. But is there a best practice? What's your thoughts? Stewart On exposure level to these kinds of new cyber and technical careers? >>Sure, absolutely. I I would say kindergarten. We San Bernardino has a program that they've been running for a little bit of time, and they're exposing students K through 12 but really starting in kindergarten. One is the exposure Thio. What a job Looks like Andi actually have. I've gone down to that local area and I've had three opportunity to see you know, second graders in a health care facility, Basically that they have on campus, built in on dear going from one workstation as a second grader, Uh, looking at what those skills would be and what that job would entail from a nurse to a Dr Teoh physician's assistant in really looking at what that is. Um you know, obviously they're not getting the training that the doctor gets, but they are getting the exposure of what that would be. Andi, I think that is amazing. And I think it's the right place to start. Um, it was really interesting because I left. This was pre covet, but I jumped on the plane to come back up north. I was thinking to myself, How do we get this to all school district in California, where we see that opportunity, um, to expose jobs and skill sets to kids throughout the system and develop the skill set so that they do understand that they have an opportunity. >>We're here at Cal Poly Space and Cybersecurity Symposium. We have educators. We have, um, students. We have industry and employers and government together. What's your advice to them all watching and listening about the future of work. Let's work force. What can people do? What do you think you're enabling? What can maybe the private sector help with And what are you trying to do? Can you share your thoughts on that? Because we have a range from the dorm room to the boardroom here at this event. Love to get your thoughts on the workforce development view of this. >>Yeah, absolutely. I think that's the mix. I mean, I think it's going to take industry to lead A in a lot of ways, in terms of understanding what their needs are and what their needs are today and what they will be tomorrow. I think it takes education, toe listen, and to understand and labor and workforce development also listen and understand what those needs will look like. And then how do we move systems? How do we move systems quickly? How do we move systems in a way that meets those needs? How do we, uh, put money into systems where the most need is, but also looking at trends? What is that trend going to look like in two years? What does that train gonna look like in five years. But that's again listening to those employers. Um, it's also the music community based organizations. I think, obviously some of our best students are also linked to CBS. And one way or another, it may be for services. It maybe for, uh, faith based. It may be anything, but I think we also need to bring in the CBS is Well, ah, lot of outreach goes through those systems in conjunction with, but I think that's the key component is to make sure that our employers are heard on. But they sit at the table like you said to the boardroom of understanding, and I think bringing students into that so that they get a true understanding of what that looks like a well, um, is a key piece of this. >>So one of the things I want to bring up with you is maybe a bit more about the research side of it. But, um, John Markoff, who was a former New York Times reporter with author of the book What the Dormouse, said It was a book about the counter culture of the sixties and the computer revolution, and really there was about how government defense spending drove the computer revolution that we now saw with Apple and PC, and then the rest is history in California has really participated. Stanford, uh, Berkeley and the University of California School system and all the education community colleges around it. That moment, the enablement. And now you're seeing space kind of bringing that that are a lot of research coming in and you eat a lot of billionaires putting money in. You got employers playing a role. You have this new focus space systems, cybersecurity, defending and making it open and and not congested and peaceful is going to enable quickly new inflection points for opportunities. E want to get your thoughts on that? Because California is participate in drove these revolutions that created massive value This next wave seems to be coming upon us. >>Yeah, absolutely. And again, Nazis covered again as too much of ah starting point to this. But I think that is also an opportunity to actually, because I think one of the things that we were seeing seven months ago was a skill shortage, and we still see the skills shortage, obviously. But I think a key piece to that is we saw people shortage. Not only was it skills shortage, but we didn't have enough people really to fill positions in addition to and I think that people also felt they were already paying the bills and they were making ends meet and they didn't have the opportunities. Thio get additional skills This again is where we're looking at. You know that our world has changed. It changed in the sixties based on what you're you're just expressing in terms of California leading the way. Let's like California lead the way again in developing a system from which labor, workforce development with our universities are, you know, are amazing universities and community college system and structure of how do we get students back into school? You know, a lot of graduates may already have a degree, but how do they now take a skill so that they already have and develop that further with the idea that they those jobs have changed? Whales have a lot of folks that don't have a degree, and that's okay. But how do we make that connection to a system that may have failed? Ah, lot of our people over the years, um, and our students who didn't make it through the school system. How do we develop in adult training school? How do we develop contract education through our community college system with our employer sets that we developed cohorts within those systems of of workers that have amazing talents and abilities to start to fill these needs? And I think that's the key components of hearing Agency, Labor, Workforce Development Agency. We work with our community. Colleges are UCS in our state universities t develop and figure that piece out, and I think it is our opportunity for the future. >>That's such a great point. I want to call that out This whole opportunity to retrain people that are out there because these air new jobs, I think that's a huge opportunity, and and I hope you keep building and investing in those programs. That's that's really worth calling out. Thank you for doing that. And, yeah, it's a great opportunity. Thes jobs they pay well to cyber security is a good job, and you don't really need to have that classical degree. You can learn pretty quickly if you're smart. So again, great call out there question for you on geography, Um, mentioned co vid we're talking about Covic. Virtualization were virtual with this conference. We couldn't be in person. People are learning virtually, but people are starting to relocate virtually. And so one observation that I have is the space state that California is there space clusters of areas where space people hang out or space spaces and whatnot. Then you got, like, the tech community cybersecurity market. You know, Silicon Valley is a talented in these hubs, and sometimes cyber is not always in the same hubs of space. Maybe Silicon Valley has some space here, Um, and some cyber. But that's not generally the case. This is an opportunity potentially to intersect. What's your thoughts on this? Because this is This is something that we're seeing where your space has historical, you know, geography ease. Now, with borderless communication, the work boat is not so much. You have to move the space area. You know what I'm saying? So okay. What's your thoughts on this? How do you guys look at this? Is on your radar On how you're viewing this this dynamic? >>It's absolute on our radar, Like you said, you know, here we are talking virtually on and, you know, 75% of all of our staff currently in some of our department that 80% of our staff are now virtual. Um you know, seven months ago, uh, we were not were government again being slow move, we quickly transitioned. Obviously, Thio being able to have a tele work capacity. We know employers move probably even quickly, more quickly than we did, but we see that as an opportunity for our rural areas. Are Central Valley are north state um, inland Empire that you're absolutely correct. I mean, if you didn't move to a city or to a location for which these jobs were really housed, um, you didn't have an opportunity like you do today. I think that's a piece that we really need to work with our education partners on of to be able to see how much this has changed. Labor agency absolutely recognizes this. We are investing funding in the Central Valley. We're investing funding in the North State and empire to really look a youth populations of how the new capacity that we have today is gonna be utilized for the future for employers. But we also have to engage our universities around. This is well, but mostly are employers. I know that they're already very well aware. I know that a lot of our large employers with, um, Silicon Valley have already done their doing almost 100% tele work policies. Um, but the affordability toe live in rural areas in California. Also, it enables us to have, ah, way thio make products more affordable is, well, potentially in the future. But we want to keep California businesses healthy and whole in California. Of course, on that's another way we can We can expand and keep California home to our 40 plus million people, >>most to a great, great work. And congratulations for doing such a great job. Keep it up. I gotta ask about the governor. I've been following his career since he's been office. A za political figure. Um, he's progressive. He's cutting edge. He likes toe rock the boat a little bit here and there, but he's also pragmatic. Um, you're starting to see government workers starting to get more of a tech vibe. Um um just curious from your perspective. How does the governor look at? I mean, the old, almost the old guard. But like you know, used to be. You become a lawyer, become a lawmaker Now a tech savvy lawmaker is a premium candidates, a premium person in government, you know, knowing what COBOL is. A start. I mean, these are the things. As we transform and evolve our society, we need thinkers who can figure out which side the streets, self driving cars go on. I mean, who does that? I mean, it's a whole another generation off thinking. How does the Governor how do you see this developing? Because this is the challenge for society. How does California lead? How do you guys talk about the leadership vision of Why California and how will you lead the future? >>Absolutely no governor that I'm aware of that I've been around for 26 27 years of workforce development has led with an innovation background, as this governor has a special around technology and the use of technology. Uh, you know, he's read a book about the use of technology when he was lieutenant governor, and I think it's really important for him that we, as his his staff are also on the leading edge of technology. I brought a badge. I'll systems. Earlier, when I was under the Brown administration, we had moved to where I was at a time employment training panel. We moved to an agile system and deported that one of the first within within the state to do that and coming off of an old legacy system that was an antique. Um, I will say it is challenging. It's challenging on a lot of levels. Mostly the skill sets that are folks have sometimes are not open to a new, agile system to an open source system is also an issue in government. But this governor, absolutely. I mean, he has established three Office of Digital Innovation, which is part of California and department technology, Um, in partnership with and that just shows how much he wants. Thio push our limits to make sure that we are meeting the needs of Californians. But it's also looking at, you know, Silicon Valley being at the heart of our state. How do we best utilize systems that already there? How do we better utilize the talent from those those folks is well, we don't always pay as well as they dio in the state. But we do have great benefit packages. Everybody does eso If anybody's looking for a job, we're always looking for technology. Folks is well on DSO I would say that this governor, absolute leads in terms of making sure that we will be on cutting edge of technology for the nation, >>you know, and, you know, talk about pay. I mean, I know it's expensive to live in some parts of California, but there's a huge young population that wants a mission driven job and serving, um, government for the governments. Awesome. Ah, final parting question for you, Stuart, is, as you look at, um, workforce. Ah, lot of people are passionate about this, and it's, you know, you you can't go anywhere without people saying, You know, we got to do education this way and that way there's an opinion everywhere you go. Cybersecurity is a little bit peaked and focused, but there are people who are paying attention to education. So I have to ask you, what creative ways can people get involved and contribute to workforce development? Whether it's stem underrepresented minorities, people are looking for new, innovative ways to contribute. What advice would you give these people who have the passion to contribute to the next cyber workforce. >>Yeah, I appreciate that question, because I think is one of the key components. But my secretary, Julie Sue, secretary of Labor and Workforce Development Agency, talks about often, and a couple of us always have these conversations around. One is getting people with that passion to work in government one or on. I brought it up community based organizations. I think I think so many times, um, that we didn't work with our CBS to the level of in government we should. This administration is very big on working with CBS and philanthropy groups to make sure that thing engagement those entities are at the highest level. So I would say, You know, students have opportunities. Thio also engage with local CBS and be that mission what their values really drives them towards Andi. That gives them a couple of things to do right. One is to look at what ways that we're helping society in one way or another through the organizations, but it also links them thio their own mission and how they could develop those skills around that. But I think the other piece to that is in a lot of these companies that you are working with and that we work with have their own foundations. So those foundations are amazing. We work with them now, especially in the new administration. More than we ever have, these foundations are really starting to help develop are strategies. My secretary works with a large number of foundations already. Andi, when we do is well in terms of strategy, really looking at, how do we develop young people's attitudes towards the future but also skills towards the future? >>Well, you got a pressure cooker of a job. I know how hard it is. I know you're working hard, appreciate you what you do and and we wish you the best of luck. Thank you for sharing this great insight on workforce development. And you guys working hard. Thank you for what you do. Appreciate it. >>Thank you so much. Thistle's >>three cube coverage and co production of the space and cybersecurity supposed in 2020 Cal Poly. I'm John for with silicon angle dot com and the Cube. Thanks for watching

>> Announcer: From around the globe, it's theCUBE! Covering Space and Cybersecurity Symposium 2020. Hosted by Cal Poly. >> Hello everyone. Welcome to the Space and Cybersecurity Symposium 2020, put on by Cal Poly and hosted with SiliconANGLE theCUBE here in Palo Alto, California for a virtual conference. Couldn't happen in person this year, I'm John Furrier, your host. The intersection of space and cybersecurity, obviously critical topics, great conversations. We've got a great guest here to talk about the addressing the cybersecurity workforce gap. And we have a great guest, and a feature speaker, Stewart Knox, the undersecretary with California's Labor and Workforce Development Office. Stewart, thanks for joining us today. >> Thank you so much, John. I appreciate your time today and listening to a little bit of our quandaries with making sure that we have the security that's necessary for the state of California and making sure that we have the workforce that is necessary for cybersecurity in space. >> Great. I'd love to get started. I've got a couple of questions for you, but first take a few minutes for an opening statement to set the stage. >> Sure, realizing that in California, we lead the nation in much of cybersecurity based on Department of Defense contractors within the state of California, leading the nation with over 160 billion dollars within the industry just here in California alone and having over 800,000 plus workers full time employment in the state of California is paramount for us to make sure that we face defense manufacturers, approximately 700,000 jobs that are necessary to be filled. There's over 37,000 vacancies that we know of in California, just alone in cybersecurity. And so we look forward to making sure that California Workforce Development Agency is leading the charge to make sure that we have equity in those jobs and that we are also leading in a way that brings good jobs to California and to the people of California, a good education system that is developed in a way that those skills are necessarily met for the employers here in California, and the nation. >> One of the exciting things about California is obviously look at Silicon Valley, Hewlett Packard and the garage story, history, space, it's been a space state, many people recognize California. You mentioned defense contractors. It's well rooted with history, just breakthroughs, bases, technology companies in California. And now you've got technology. This is the cybersecurity angle. Take a minute to give some more commentary to that because that's really notable, and as the workforce changes, these two worlds are coming together and sometimes they're in the same place, sometimes they're not. This is super exciting and a new dynamic that's driving opportunities. Could you share some color commentary on that dynamic? >> Absolutely. And you're so correct. I think in California, we lead the nation in the way that we develop programs, that our companies lead in the nation in so many ways around cyberspace, cybersecurity in so many different areas, for which in the Silicon Valley is just such a leader and those companies are good, qualified companies to do so. Obviously one of the places we play a role is to make sure that those companies have a skilled workforce. And also that the security of those systems are in place for our defense contractors and for the feeder companies, those outlying entities that are providing such key resources to those companies are also leading on a cutting edge for the future. Also again, realizing that we need to expand our training and skills to make sure that those California companies continue to lead, is just such a great initiative. And I think through apprenticeship training programs, and looking at our community college systems, I think that we will continue to lead the nation as we move forward. >> You know, we've had many conversations here in this symposium virtually, certainly around the everyday life of a consumer is impacted by space. You know, we get our car service, Uber, Lyft, we have maps, we have all this technology that was born out of defense contracts and R and D that really changed generations and created a lot of great societal value. Okay, now with space kind of going to the next generation, it's easier to get stuff into space. The security of the systems is now going to be not only paramount for quality of life, but defending that, and the skills are needed in cybersecurity to defend that. And the gap is there. What can we do to highlight the opportunities for career paths? It used to be the day where you get a mechanical engineering degree or aerospace and you graduate and you go get a job, not anymore. There's a variety of paths, career-wise. What can we do to highlight this career path? >> Absolutely correct. And I think it starts, you know, K through 12 system. And I know a lot of the work that (indistinct) and other entities are doing currently. This is where we need to bring our youth into an age where they're teaching us, right, as we become older, on the uses of technology, but it's also teaching where the levels of those education can take them, K through 12, but it's also looking at how the community college system links to that. And then the university system links above and beyond, but it's also engaging our employers. You know, one of the key components, obviously as the employers play a role, for which we can start to develop strategies that best meet their needs quickly. I think that's one of the comments we hear the most, at Labor Agency is how we don't provide a change as fast as we should, especially in technology. You know, we buy computers today and they're outdated tomorrow. It's the same with the technology that's in those computers is that those students are going to be the leaders within that to really develop how those structures are in place. So K through 12 is probably our primary place to start, but also continuing that past the K-12 system. And I bring up the employers and I bring them up in a way, because many times when we've had conversations with employers around what their skills needs were and how do we develop those better? One of the pieces of that, that I think really should be recognized, many times they recognize that they wanted a four year degree, potentially, or a five year or six year degree. But then when we really looked at the skillsets, someone coming out of the community college system could meet those skillsets. And I think we need to have those conversations to make sure, not that they shouldn't be continuing their education. They absolutely should. But how do we get those skillsets built into this into a K-12 plus the two year plus the four year person? >> Yeah, I love the democratization of these new skills, because again, there's no pattern matching 'cause they weren't around before, right? So you got to look at the exposure, to your point, K through 12 exposure, but then there's an exploration piece of it, whether it's community college or whatever progression, and sometimes it's nonlinear, right? I mean, people are learning different ways, combining the exposure and the exploration. That's a big topic. Can you share your view on this? Because this now opens up more doors for people, choice, you got new avenues, you got online, I can get a cloud computing degree now from Amazon and walk in and help. I can be, you know, security clearance possibly in college. So, you know, you get exposure. Is there certain things you see, is it early on? Middle school? And then obviously the exploration, those are two important concepts. Can you unpack that a little bit, exposure and exploration of skills? >> Absolutely, and I think this takes place not only in the K-12 system, but it takes place in our community colleges and our four year universities is that, that connection with those employers is such a key component, that if there's a way we could build in internships, work experiences, what we call on the job training programs, apprenticeship training, pre-apprenticeship training programs, into a design where those students at all levels are getting an exposure to the opportunities within the space and cybersecurity avenue. I think that right there alone will start to solve a problem of having 37 plus thousand openings at any one time in California. Also, I get that there's a burden on employers to do that. And I think that's a piece that we have to acknowledge, and I think that's where education can play a larger role. That's a place we at Labor Workforce Development Agency play a role with our apprenticeship training programs, our pre-apprenticeship training programs. I could go on all day of all of our training programs that we have within the state of California. Many of the list of your partners on this endeavor are partners with Employment Training Panel, which I used to be the director of the Brown administration of. That program alone does incumbent worker training. And so that also is an exposure place where a worker may be, you know, I use the old adage of sweeping the floors one day and potentially writing a large portion of the business, within years. But it's that exposure that that employee gets through training programs, and acknowledging those skill sets and where their opportunities are, is what's valid and important. I think that's where our students, we need to play a larger role than the K-12 system, really, to get that pushed out there. >> It's funny, here in California, you were the robotics clubs in high school are like a varsity sport, you're seeing kids exposed early on with programming, but it's, you know, this whole topic of cybersecurity and space intersection around workforce, and the gaps in the skills, it's not just for the young, certainly the young generation's got to be exposed to what the careers could be and what the possible jobs and societal impact and contributions, what they could be, but also it's people who are already out there. You know, you have retraining, re-skilling, this plays an important role. I know you guys do a lot of thinking on this as the undersecretary, you have to look at this because you know, you don't want to have a label "old and antiquated" systems. And a lot of them are, and they're evolving and they're being modernized by digital transformation. So what does the role of retraining and skill development for these programs play? Can you share what you guys are working on and your vision for that? >> Absolutely. That's a great question. 'Cause I think that is where we play a large role, obviously in California and with COVID-19 is we are faced with today that we've never seen before. At least in my 27 years of running programs, similar to all workforce and economic development, we are having such a large number of people displaced currently that it's unprecedented, we've got employment rates to where we are. We're really looking at how do we take, and we're also going to see industries not return to the level for which they stood at one point in time, you know, entertainment industries, restaurants, all of the alike, really looking at how do we move people from those jobs that were middle skill jobs to upper skill jobs, but the pay points maybe weren't great, potentially. And there's an opportunity for us to skill people into jobs that are there today. It may take training, obviously, but we have dollars to do that, generally, especially within our K-12 and our K-14 systems and our universities. But we really want to look at where those skillsets are at, currently. And we want to take people from that point in time where they sit today, and try to give them that exposure to your point earlier question is how do we get them exposed to a system for which there are job with means that pay well, with benefit packages, with companies that care about their employees. 'Cause that's what our goal is. >> You know, I don't know if you have some visibility on this or an opinion, but one of the observations that I've had and talk to whether it's a commercial or public sector, is that with COVID, there's been a lot of awareness of the situation. We're adequately prepared. There's some readiness, but as everyone kind of deals with it, they're also starting to think about what to do post-COVID as we come out of it, a growth strategy for a company or someone's career. People are starting to have that on the top of their minds. So I have to ask you, is there anything that you see that they say, "Okay, certain areas, maybe not doubling down on other areas, we're going to double down on because we've seen some best practices on a trajectory of value for coming out of COVID with, you know, well-armed skills or certain things." 'Cause that's what a lot of people are thinking right now. And certainly cyber is, I mean, how many jobs are open? So you got "Well that that's kind of maybe not something to double down on, here are areas we see that are working." Can you share your current visibility into that dynamic? >> Absolutely. Another great question. One of the key components that we look at at Labor Workforce Development Agency is to look at the industries in growth modes and ones that are in decline modes. Now COVID has changed that greatly. We were in a growth mode for the last seven, eight years. We saw almost every industry, minus a few, that were all in growth in one way or another, but obviously that has changed. Our landscape is completely different than we saw six, seven months ago. So today we're looking at cybersecurity, obviously with 30 plus thousand job openings, we are looking at Defense Department contractors, obviously, with federal government contracts. We are looking at the supply chains within those. We are looking at healthcare, which has always been one of obviously our large, one of our large entities that has grown over the years. But it's also changed with COVID-19. We're looking at the way protective equipment is manufactured and the way that that will continue to grow over time, we're looking at the service industry. I mean, it will come back, but it won't come back the way we've seen it probably in the past, but where are the opportunities that we develop programs that we are making sure that the skill sets of those folks are transferable to other industries. We have one of the issues that we face constantly in Labor and Workforce Development programs is understanding that over the period of time, especially in today's world, again, with technology, that people's skillsets, we don't see as in my parents' day that you worked at a job for 45 years and you retired at one job potentially. That's been gone for 25 years, but now at the pace for which we are seeing systems change, this is going to continue to amp up, and I will say, youth of today, my 12 year old nephew is in the room next door to me, in a classroom right now online. And so, you know, it's a totally different atmosphere and he's enjoying actually being at home and learning from an all online system. I would not have been able to learn that way, but I think we do see through the K through 12 system, the way we're moving, people's interests will change. And I think that they will start to see things in a different way than we have in the past. They were forced systems. We are an old system, been around since the 30s. Some even we'll say prior to the 30s, came out of the Great Depression in some ways. And that system, we have to change the way we develop our programs. It should not be constant and it should be an evolving system. >> It's interesting. A lot of the conversations between the private and public partnerships and industry, you're seeing an agile mindset where it's a growth mindset, it's also a reality-based mindset and certainly space kind of forces this conversation with cybersecurity of being faster, faster, more relevant, more modern. And you mentioned some of those points, and with COVID impact, the workforce development is certainly going to put a lot of pressure on faster learning. And then you mentioned online learning. This has become a big thing. It's not just putting education online per se. There's new touchpoints. You know, you've got apps, you've got digital. This digital transformation is also accelerating. How do you guys view the workforce development? Because it's going to be open. It's going to be evolving. There's new data coming in and maybe kids don't want to stare at a video conference. Is there some game aspect to it? Is there, how do you integrate these new things that are coming really fast, and it's happening kind of in real time in front of our eyes. So I'd love to get your thoughts on how you guys see that because it'll certainly impact their ability to compete for jobs and/or to self-learn. >> Well, I think one of the key components of California is our innovation, right? And so I think one of the things that we pride ourselves in California is around that. That said, that is the piece that I think the Silicon Valley, and then there's many areas in California that have done the same, or tried to do the same, at least in their economy is to build in innovation. And I think that's part of the K through 12 system, with our state universities and our UCs is to be able to bridge that. I think that you, we see that within universities that really instill an innovative approach to teaching, but also instill innovation within their students. I'm not sure we're there yet fully, with our K-12 system, and I think that's a place that either our community colleges could be a bridge to as well. So that's one component of workforce development I think that we look at as being a key piece. You brought up something that's really interesting to me is when you talk about agile, and one of the things that even in state government, this is going to be shocking to you, but we have not been an agile system as well. I think one of the things that the Newsom administration, Governor Newsom's administration has brought is, and when I talk about agile systems, I actually mean agile systems. We've gone from COBOL systems, which are old and clunky, still operating, but at the same time, we're looking at upgrading all of our systems in a way that even in our technology, in the state of California should be matching, the technology that our great state has within our state. So therein lies, it's also challenges of finding the qualified staff that we need in the state of California for all of our systems and servers and everything that we have currently. So, you know, not only are we looking at external users of labor workforce development, but we're looking at internal users, that the way we redevelop our systems so that we are more agile in two different ways. >> You just got me triggered with COBOL. I programmed in the 80s with COBOL, only one credit lab in college. Never touched it again, thank God. But this is the benefit of cloud computing. I think this is at the heart and this is the undertone of the conference and symposium is cloud computing, you can actually leverage existing resources, whether they're legacy systems, because they are running, they're doing a great job and they do a certain workload extremely well. Doesn't make sense to replace if it does a job. You can integrate it and that's what cloud does. This is opening up more and more capabilities and workloads. This is kind of what the space industry is pointing to when they say "We need people that can code and that can solve data problems," not just the computer scientists, but a large range of people, creative, data, science, everything. How does California's workforce solve the needs of America's space industry? This is because it's a space state. How do you see the labor workforce meeting those needs? >> Yeah, I think it's an investment. Obviously it's an investment on our part. It's an investment with our college partners. It's an investment from our K-12 system to make sure that we are allocating dollars in a way through meeting the demand of industry. And we do look at industry-specific around their needs, obviously this is a large one. We want to be very receptive, and work with our employers and our employee groups to make sure that we meet that demand. I think it's putting our money where our mouth is and designing and working with employer groups to make sure that the training meets their needs. It's also working with our employer groups to make sure that the employees are taken care of and that equity is built within the systems, that we keep people employed in California, and they're able to afford a home and they're able to afford a life here in California, but it's also again and I brought up the innovation component. I think it's building an innovation within systems for which they are employers, but are also our incoming employees and our incumbent workers. And you brought those up earlier, people that are already employed and people that are unemployed currently with a skill set that might match up is how do we bridge those folks into employment that they maybe have not thought about? We have a whole career network of systems out throughout The City of California with the America's Job Centers of California, and they will be working, and they already are working with a lot of dislocated workers. And one of the key components of that is to really look at how do we take what their current skillset might be, and then expose them to a system for which we have 37 plus thousand job openings, too, and how do we actually get those folks employed? It's paid for potentially through that local Workforce Innovation and Opportunity Act funding through our America's Job Centers, to pay for some on the job training. It's to be able to pay for work experiences, it's to be able to pay for internships for students to get that opportunity with our employers and also partnering with our employers that they're paying, obviously a percentage of that too. >> You know, one of the things I've observed over my career, 54 times around the sun is, you know, in the old days, when I was in college and school, you had career, people had the longer jobs, as you mentioned it's not like that anymore. But also I knew someone I'm going to to be in line to get that job, maybe nepotism or things of that nature. Now the jobs have no historical thing or someone worked longer in a job and has more seniority. A lot of these jobs, Stewart, don't have requirements, like no one's done them before. So the ability for someone who is jumping in, either from any college, there's no real, it's all level set, it's a complete upside down script here. It's not like, "Oh, I went to school, therefore I get the job." It can be, anyone can walk into these careers because the jobs are so new. So it's not where you came from or what school you went to or your nationality or gender. The jobs have been democratized. They're not discriminating against people with skills. This opens up more. How do you see that? Because this really is an opportunity for this next generation to be more diverse and to be more contributive because diversity brings expertise and different perspectives. Your thoughts on that. >> Absolutely, and that was one of the things we welcome, obviously. We want to make sure that that everybody is treated equally and that the employers view everyone as an employer of choice, but an employee of choice as well. We've also been looking at, as I mentioned before on the COVID situation, looking at ways that folks that are maybe stuck in jobs that don't have a huge career pathway, or they don't have a pathway out of poverty. I mean, we have a lot of working poor people in the state of California that may now due to COVID lost their employment. This, you know, let's turn back to the old adage, let's turn lemons into lemonade. How do we take those folks and get them employed into jobs that do have a good career pathway? And it's not about just who you knew, or who you might have an in with to get that job. It is based on skills. I think though, that said, we need to have a better way to actually match those jobs up with those employers. And I think those are the ongoing conversations with those employer groups to make sure that, one, that they see those skill sets as valid and important. They're helping design those career sets with us so that they do match up and that we're quickly matching up those close skillsets so that we're not training people for yesterday's skills. >> I think the employer angle's super important, but also the educators as well. One of the things that was asked in another question by the guest, they said, she said, the real question to ask is, how early do you start exposing the next generation? You mentioned K through 12, do you have any data or insight into or intuition or best practice of where that insertion point is, that exposure point? Is it middle school? Is it elementary, honestly, high school, once you're in high school, you got your training wheels are off, you're off to the races, but is there a best practice? What's your thoughts, Stewart, on exposure level to these kinds of new cyber and technical careers? >> Sure, absolutely. I would say kindergarten. We, San Bernardino has a program that they've been running for a little bit of time, and they're exposing students K through 12, but really starting in kindergarten. One is the exposure to what a job looks like. And then actually I've gone down to that local area and I've had the opportunity to see, you know, second graders in a healthcare facility, basically, that they have on campus built-in. And they're going from one workstation as a second grader, looking at what those skills would be and what that job would entail from a nurse to a doctor, to a physician's assistant, and really looking at what that is. You know, obviously they're not getting the training that a doctor gets, but they are getting the exposure of what that would be. And I think that is amazing. And I think it's the right place to start. It was really interesting 'cause as I left, this was pre-COVID, but as I jumped on the plane to come back up north, I was thinking to myself, "How do we get this to all school districts in California where we see that opportunity to expose jobs and skill sets to kids throughout the system and develop those skill sets so that they do understand that they have an opportunity?" >> We are here at Cal Poly Space and Cybersecurity Symposium. We have educators, we have students, we have industry and employers and government together. What's your advice to them all watching and listening about the future of work, this workforce, what can people do? What do you think you're enabling? What can maybe the private sector help with and what are you trying to do? Can you share your thoughts on that? Because we have a range from the dorm room to the boardroom here at this event. I'd love to get your thoughts on the workforce development view of this. >> Yeah, absolutely. And I think that's the mix. I mean, I think it's going to take industry to lead, in a lot of ways in terms of understanding what their needs are and what their needs are today and what they will be tomorrow. I think it takes education to listen, and to understand, and labor and workforce development to also listen and understand what those needs will look like. And then how do we move systems? How do we move systems quickly? How do we move systems in a way that meets those needs? How do we put money into systems where the most need is, but also looking at trends? What is that trend going to look like in two years? What is that trend going to look like in five years, (indistinct), again, listening to those employers, it's also listening to the community-based organizations. I think obviously some of our best students are also linked to CBOs in one way or another. It may be for services, it may be for faith-based, it may be anything, but I think we also need to bring in the CBOs as well. A lot of outreach goes through those systems in conjunction with, but I think that's the key component is to make sure that our employers are heard and that they sit at the table, like you said, to the boardroom of understanding, and I think bringing students into that so that they get a true understanding of what that looks like as well, is a key piece of this. >> Stu, one of the things I want to bring up with you is maybe a little bit more about the research side of it, but John Markoff, who was a former New York times reporter, but author of the book, "What the Dormouse Said," it was a book about the counterculture of the 60s and the computer revolution. And really it was about how government defense spending drove the computer revolution that we now saw with Apple and PC. And then the rest is history in California, has really participated, Stanford, the Berkeley, and the University of California school system, and all the education community colleges around it. That moment, the enablement, and now you're seeing space kind of bringing that, a lot of research coming in, need a lot of billionaires putting money in, you've got employers playing a role. You have this new focus, space systems, cybersecurity defending and making it open and, not congested and peaceful, is going to enable quickly, new inflection points for opportunities. I want to get your thoughts on that because California's participated and drove those revolutions, that's created massive value. This next wave seems to be coming upon us. >> Yeah, absolutely. And again, not to use COVID again as too much of a starting point to this, but I think that is also an opportunity to actually, 'cause I think one of the things that we were seeing seven months ago was a skill shortage, and we still see the skill shortage, obviously. But I think a key piece to that is we saw a people shortage. Not only was it skill shortage, but we didn't have enough people really to fill positions in addition, too, and I think that people also felt they were already paying the bills and they were making ends meet and they didn't have the opportunities to get additional skills. This again is where we're looking at, you know, our world has changed. It changed in the 60s based on what you're just expressing in terms of California leading the way. Let's let California lead the way again in developing a system for which labor workforce development with our universities, our amazing universities and community college system structure, of how do we get students back into school? You know, a lot of graduates may already have a degree, but how do they now take a skill set that they already have and develop that further with the idea that those jobs have changed? We also have a lot of folks that don't have a degree, and that's okay, but how do we make that connection to a system that may have failed a lot of our people over the years, and our students who didn't make it through the school system, how do we develop an adult training school? How do we develop contract education through our community college system with our employer sets, that we develop cohorts within the systems of workers that have amazing talents and abilities to start to fill these needs. And I think that's the key components that here at Labor Workforce Development Agency, we work with our community colleges, our UCs and our state universities to develop and figure that piece out. And I think it is our opportunity for the future. >> That's such a great point. I want to call that out, this whole opportunity to retrain people that are out there because these are new jobs. I think that's a huge opportunity and, I hope you keep building and investing in those programs. That's really worth calling out. Thank you for doing that. And yeah, it's a great opportunity to gain these jobs. They pay well, too, cybersecurity's a good job and you don't really need to have that classical degree. You can learn pretty quickly if you're smart. So again, great call out there. A question for you on geography. You mentioned COVID, we're talking about COVID, virtualization, we're virtual with this conference. We couldn't be in person. People are learning virtually, but people are starting to relocate virtually. And so one observation that I have is the space state that California is, there's space clusters of areas where space people hang out, or space spaces and whatnot. Then you got like the tech community, the cybersecurity market, you know, Silicon Valley, you know, the talent is in these hubs. And sometimes cyber's not always in the same hubs as space. Maybe Silicon Valley has some space here, and some cyber, but that's not generally the case. This is an opportunity potentially to intersect. What's your thoughts on this? Because this is something that we're seeing, where space has historical, you know, geographies. Now with borderless communication, the work mode is not so much "You have to move to this space area." You know what I'm saying? So what's your thoughts on this? How do you guys look at, this is on your radar, and how you're viewing this dynamic. >> It's absolutely on our radar. Like you said, you know, here we are, talking virtually, and you know, 75% of all of our staff currently, in some of our departments, it's 80% of our staff, are now virtual. Seven months ago, we were not. Government, again, being slow move, we quickly transitioned, obviously, to being able to have a telework capacity. We know employers moved probably even more quickly than we did, but we see that as an opportunity for our rural areas, our Central Valley, our Northstate, Inland Empire. That you're absolutely correct. I mean, if you didn't move to a city or to a location for which these jobs were really housed, you didn't have an opportunity like you do today. I think that's a piece that we really need to work with our education partners on, to be able to see how much this has changed. Labor Agency absolutely recognizes this. We are investing funding in the Central Valley. We're investing funding in the Northstate and Inland Empire to really look at youth populations, of how the new capacity that we have today is going to be utilized for the future for employers. But we also have to engage our universities around this as well, but mostly our employers. I know that they're already very well aware. I know that a lot of our large employers within Silicon Valley have already done it. They're doing almost 100% telework policies, but the affordability to live in rural areas in California, also enables us to have a way to make products more affordable as well, potentially in the future. But we want to keep California businesses healthy and whole in California, of course. And that's another way we can expand and keep California home to our 40 plus million people. >> Well Stewart, great work and congratulations for doing such a great job. Keep it up. I got to ask you about the governor. I've been following his career since he's been in office as a political figure. He's progressive, he's cutting edge. He likes to rock the boat a little bit here and there, but he's also pragmatic. You're starting to see government workers starting to get more of a tech vibe. Just curious from your perspective, how does the governor look at, I mean, the old, I won't say "old guard," but like, you know, it used to be, you become a lawyer, you become a lawmaker. Now a tech savvy lawmaker is a premium candidate, is a premium person in government. Knowing what COBOL is, is a start. I mean, these are the things that as we transform and evolve our society, we need thinkers who can figure out which side of the streets self driving cars go on. I mean, who does that? It's a whole nother generation of thinking. How does the governor, how do you see this developing? Because this is the challenge for society. How does California lead? How do you guys talk about the leadership vision of why California and how will you lead the future? >> Absolutely. No governor that I'm aware of, and I've been around for 26, 27 years of workforce development, has led with an innovation background as this governor has, especially around technology and the use of technology. You know, he's wrote a book about the use of technology when he was lieutenant governor. And I think it's really important for him that we, as his staff are also on the leading edge of technology. I brought up agile systems earlier. When I was under the Brown administration, we had moved to where I was at the time, Employment Training Panel, we moved to an agile system and deployed that. One of the first within the state to do that and coming off of an old legacy system that was an antique. I will say it is challenging. It's challenging on a lot of levels. Mostly the skill sets that our folks have, sometimes are not open to a new agile system, to an open source system is also an issue in government. But this governor absolutely, I mean, he has established the Office of Digital Innovation, which is part of California Department of Technology, in partnership with, and that just shows how much he wants to push our limits to make sure that we are meeting the needs of Californians. But it's also looking at, you know, Silicon Valley being at the heart of our state, how do we best utilize systems that are already there? How do we better utilize the talent from those folks as well? We don't always pay as well as they do in the state, but we do have great benefit packages, everybody knows. So if anybody's looking for a job, we're always looking for technology folks as well. And so I would say that this governor absolutely leads in terms of making sure that we will be on cutting edge technology for the nation. >> And, you know, talk about pay, I mean, I know it's expensive to live in some parts of California, but there's a huge young population that wants a mission-driven job, and serving the government for the government, it's awesome. A final parting question for you, Stewart, is as you look at the workforce, a lot of people are passionate about this and it's, you know, you can't go anywhere without people saying, you know, "We've got to do education this way, and that way," there's an opinion everywhere you go. Cybersecurity, obviously a little bit peaked and focused, but there are people who are paying attention to education. So I have to ask you what creative ways can people get involved and contribute to workforce development, whether it's STEM, underrepresented minorities, people are looking for new, innovative ways to contribute. What advice would you give these people who have the passion to contribute to the next cyber workforce? >> Yeah, I appreciate that question because I think it's one of the key components that my secretary, Julie Su, secretary of Labor and Workforce Development Agency, talks about often. And a couple of us always have these conversations around one is getting people with that passion to work in government, one, or, and I brought it up community-based organizations. I think so many times that we didn't work with our CBOs to the level that in government, we should, this administration is very big on working with CBOs and philanthropy groups to make sure that the engagement of those entities are at the highest level. So I would say, students have opportunities to also engage with local CBOs and be that mission, what their values really drives them towards. And that gives them a couple of things to do, right? One is to look at ways that we're helping society in one way or another through those organizations, but it also links them to their own mission and how they can develop those skills around that. But I think the other piece to that is in a lot of these companies that you are working with and that we work with, have their own foundations. So those foundations are amazing. We work with them now, especially in the Newsom administration, more than we ever have. These foundations are really starting to help develop our strategies. My secretary works with a large number of foundations already, and we do as well in terms of strategy, really looking at how do we develop young people's attitudes towards the future, but also skills towards the future? >> Well, you got a pressure cooker of a job. I know how hard it is. I know you're working hard and appreciate what you do. And, and we wish you the best of luck, thank you for sharing this great insight on workforce development. And you guys are working hard. Thank you for what you do. Appreciate it. >> Great. Thank you so much. I appreciate it. >> This is theCUBE coverage and co-production of the Space and Cybersecurity Symposium 2020 with Cal Poly. I'm John Furrier with siliconangle.com and theCUBE. Thanks for watching. (calm music)

(upbeat music) >> Announcer: Live from Las Vegas, it's theCUBE! Covering UIPath FORWARD America's 2019. Brought to you by UIPath. >> Welcome back, everyone, to theCUBE's live coverage of UIPath FORWARD, here in Sin City, Las Vegas Nevada. I'm your host, Rebecca Knight, co-hosting alongside Dave Velante. We have two guests for this segment. We have Kurt Carlson, Associate Dean for faculty and academic affairs of the Mason School of Business at the college of William and Mary. Thanks for coming on the show. >> Thanks you for having me. >> Rebecca: And we have Tom Clancy, the SVP of learning at UIPath, thank you so much. >> Great to be here. >> You're a Cube alum, so thank you for coming back. >> I've been here a few times. >> A Cube veteran, I should say. >> I think 10 years or so >> So we're talking today about a robot for every student, this was just announced in August, William and Mary is the first university in the US to provide automation software to every undergraduate student, thanks to a four million dollar investment from UIPath. Tell us a little bit about this program, Kurt, how it works and what you're trying to do here. >> Yeah, so first of all, to Tom and the people at UIPath for making this happen. This is a bold and incredible initiative, one that, frankly, when we had it initially, we thought that maybe we could get a robot for every student, we weren't sure that other people would be willing to go along with that, but UIPath was, they see the vision, and so it was really a meeting of the minds on a common purpose. The idea was pretty simple, this technology is transforming the world in a way that students, we think it's going to transform the way that students actually are students. But it's certainly transforming the world that our students are going into. And so, we want to give them exposure to it. We wanted to try and be the first business school on the planet that actually prepares students not just for the way RPA's being used today, but the way that it's going to be used when AI starts to take hold, when it becomes the gateway to AI three, four, five years down the road. So, we talked to UIPath, they thought it was a really good idea, we went all in on it. Yeah, all of our starting juniors in the business school have robots right now, they've all been trained through the academy live session putting together a course, it's very exciting. >> So, Tom, you've always been an innovator when it comes to learning, here's my question. How come we didn't learn this school stuff when we were in college? We learned Fortran. >> I don't know, I only learned BASIC, so I can't speak to that. >> So you know last year we talked about how you're scaling, learning some of the open, sort of philosophy that you have. So, give us the update on how you're pushing learning FORWARD, and why the College of William and Mary. >> Okay, so if you buy into a bot for every worker, or a bot for every desktop, that's a lot of bots, that's a lot of desktops, right? There's studies out there from the research companies that say that there's somewhere a hundred and 200 million people that need to be educated on RPA, RPA/AI. So if you buy into that, which we do, then traditional learning isn't going to do it. We're going to miss the boat. So we have a multi-pronged approach. The first thing is to democratize RPA learning. Two and a half years ago we made, we created RPA Academy, UIPath academy, and 100% free. After two and a half years, we have 451,000 people go through the academy courses, that's huge. But we think there's a lot more. Over the next next three years we think we'll train at least two million people. But the challenge still is, if we train five million people, there's still a hundred million that need to know about it. So, the second biggest thing we're doing is, we went out, last year at this event, we announced our academic alliance program. We had one university, now we're approaching 400 universities. But what we're doing with William and Mary is a lot more than just providing a course, and I'll let Kurt talk to that, but there is so much more that we could be doing to educate our students, our youth, upscaling, rescaling the existing workforce. When you break down that hundred million people, they come from a lot of different backgrounds, and we're trying to touch as many people as we can. >> You guys are really out ahead of the curve. Oftentimes, I mean, you saw this a little bit with data science, saw some colleges leaning in. So what lead you guys to the decision to actually invest and prioritize RPA? >> Yeah, I think what we're trying to accomplish requires incredibly smart students. It requires students that can sit at the interface between what we would think of today as sort of an RPA developer and a decision maker who would be stroking the check or signing the contract. There's got to be somebody that sits in that space that understands enough about how you would actually execute this implementation. What's the right buildout of that, how we're going to build a portfolio of bots, how we're going to prioritize the different processes that we might automate, How we're going to balance some processes that might have a nice ROI but be harder for the individual who's process is being automated to absorb against processes that the individual would love to have automated, but might not have as great of an ROI. How do you balance that whole set of things? So what we've done is worked with UIPath to bring together the ideas of automation with the ideas of being a strategic thinker in process automation, and we're designing a course in collaboration to help train our students to hit the ground running. >> Rebecca, it's really visionary, isn't it? I mean it's not just about using the tooling, it's about how to apply the tooling to create competitive advantage or change lives. >> I used to cover business education for the Financial Times, so I completely agree that this really is a game changer for the students to have this kind of access to technology and ability to explore this leading edge of software robotics and really be, and graduate from college. This isn't even graduate school, they're graduating from college already having these skills. So tell me, Kurt, what are they doing? What is the course, what does it look like, how are they using this in the classroom? >> The course is called a one credit. It's 14 hours but it actually turns into about 42 when you add this stuff that's going on outside of class. They're learning about these large conceptual issues around how do you prioritize which processes, what's the process you should go through to make sure that you measure in advance of implementation so that you can do an audit on the backend to have proof points on the effectiveness, so you got to measure in advance, creating a portfolio of perspective processes and then scoring them, how do you do that, so they're learning all that sort of conceptual straight business slash strategy implementation stuff, so that's on the first half, and to keep them engaged with this software, we're giving them small skills, we're calling them skillets. Small skills in every one of those sessions that add up to having a fully automated and programmed robot. Then they're going to go into a series of days where every one of those days they're going to learn a big skill. And the big skills are ones that are going to be useful for the students in their lives as people, useful in lives as students, and useful in their lives as entrepreneurs using RPA to create new ventures, or in the organizations they go to. We've worked with UIPath and with our alums who've implement this, folks at EY, Booz. In fact, we went up to DC, we had a three hour meeting with these folks. So what are the skills students need to learn, and they told us, and so we build these three big classes, each around each one of those skills so that our students are going to come out with the ability to be business translators, not necessarily the hardcore programmers. We're not going to prevent them from doing that, but to be these business translators that sit between the programming and the decision makers. >> That's huge because, you know, like, my son's a senior in college. He and his friends, they all either want to work for Amazon, Google, an investment bank, or one of the big SIs, right? So this is a perfect role for a consultant to go in and advise. Tom, I wanted to ask you, and you and I have known each other for a long time, but one of the reasons I think you were successful at your previous company is because you weren't just focused on a narrow vendor, how to make metrics work, for instance. I presume you're taking the same philosophy here. It transcends UIPath and is really more about, you know, the category if you will, the potential. Can you talk about that? >> So we listen to our customers and now we listen to the universities too, and they're going to help guide us to where we need to go. Most companies in tech, you work with marketing, and you work with engineering, and you build product courses. And you also try to sell those courses, because it's a really good PNL when you sell training. We don't think that's right for the industry, for UIPath, or for our customers, or our partners. So when we democratize learning, everything else falls into place. So, as we go forward, we have a bunch of ideas. You know, as we get more into AI, you'll see more AI type courses. We'll team with 400 universities now, by end of next year, we'll probably have a thousand universities signed up. And so, there's a lot of subject matter expertise, and if they come to us with ideas, you mentioned a 14 hour course, we have a four hour course, and we also have a 60 hour course. So we want to be as flexible as possible, because different universities want to apply it in different ways. So we also heard about Lean Six Sigma. I mean, sorry, Lean RPA, so we might build a course on Lean RPA, because that's really important. Solution architect is one of the biggest gaps in the industry right now so, so we look to where these gaps are, we listen to everybody, and then we just execute. >> Well, it's interesting you said Six Sigma, we have Jean Younger coming on, she's a Six Sigma expert. I don't know if she's a black belt, but she's pretty sure. She talks about how to apply RPA to make business processes in Six Sigma, but you would never spend the time and money, I mean, if it's an airplane engine, for sure, but now, so that's kind of transformative. Kurt, I'm curious as to how you, as a college, market this. You know, you're very competitive industry, if you will. So how do you see this attracting students and separating you guys from the pack? >> Well, it's a two separate things. How do we actively try to take advantage of this, and what effects is it having already? Enrollments to the business school, well. Students at William and Mary get admitted to William and Mary, and they're fantastic, amazingly good undergraduate students. The best students at William and Mary come to the Raymond A. Mason school of business. If you take our undergraduate GPA of students in the business school, they're top five in the country. So what we've seen since we've announced this is that our applications to the business school are up. I don't know that it's a one to one correlation. >> Tom: I think it is. >> I believe it's a strong predictor, right? And part because it's such an easy sell. And so, when we talk to those alums and friends in DC and said, tell us why this is, why our students should do this, they said, well, if for no other reason, we are hiring students that have these skills into data science lines in the mid 90s. When I said that to my students, they fell out of their chairs. So there's incredible opportunity here for them, that's the easy way to market it internally, it aligns with things that are happening at William and Mary, trying to be innovative, nimble, and entrepreneurial. We've been talking about being innovative, nimble, and entrepreneurial for longer than we've been doing it, we believe we're getting there, we believe this is the type of activity that would fit for that. As far as promoting it, we're telling everybody that will listen that this is interesting, and people are listening. You know, the standard sort of marketing strategy that goes around, and we are coordinating with UIPath on that. But internally, this sells actually pretty easy. This is something people are looking for, we're going to make it ready for the world the way that it's going to be now and in the future. >> Well, I imagine the big consultants are hovering as well. You know, you mentioned DC, Booz Allen, Hughes and DC, and Excensior, EY, Deloitte, PWC, IBM itself. I mean it's just, they all want the best and the brightest, and now you're going to have this skill set that is a sweet spot for their businesses. >> Kurt: That's the plan. >> I'm just thinking back to remembering who these people are, these are 19 and 20 year olds. They've never experienced the dreariness of work and the drudge tasks that we all know well. So, what are you, in terms of this whole business translator idea, that they're going to be the be people that sit in the middle and can sort of be these people who can speak both languages. What kind of skills are you trying to impart to them, because it is a whole different skill set. >> Our vision is that in two or three years, the nodes and the processes that are currently... That currently make implementing RPA complex and require significant programmer skills, these places where, right now, there's a human making a relatively mundane decision, but it's sill a model. There's a decision node there. We think AI is going to take over that. The simple, AI's going to simply put models into those decision nodes. We also think a lot of the programming that takes place, you're seeing it now with studio X, a lot of the programming is going to go away. And what that's going to do is it's going to elevate the business process from the mundane to the more human intelligent, what would currently be considered human intelligence process. When we get into that space, people skills are going to be really important, prioritizing is going to be really important, identifying organizations that are ripe for this, at this moment in time, which processes to automate. Those are the kind of skills we're trying to get students to develop, and what we're selling it partly as, this is going to make you ready of the world the way we think it's going to be, a bit of a guess. But we're also saying if you don't want to automate mundane processes, then come with us on a different magic carpet ride. And that magic carpet ride is, imagine all the processes that don't exist right now because nobody would ever conceive of them because they couldn't possibly be sustained, or they would be too mundane. Now think about those processes through a business lens, so take a business student and think about all the potential when you look at it that way. So this course that we're building has that, everything in the course is wrapped in that, and so, at the end of the course, they're going to be doing a project, and the project is to bring a new process to the world that doesn't currently exist. Don't program it, don't worry about whether or not you have a team that could actually execute it. Just conceive of a process that doesn't currently exist and let's imagine, with the potential of RPA, how we would make that happen. That's going to be, we think we're going to be able to bring a lot of students along through that innovative lens even though they are 19 and 20, because 19 and 20 year olds love innovation, while they've never submitted a procurement report. >> Exactly! >> A innovation presentation. >> We'll need to do a Cube follow up with that. >> What Kurt just said, is the reason why, Tom, I think this market is being way undercounted. I think it's hard for the IDCs and the forces, because they look back they say how big was it last year, how fast are these companies growing, but, to your point, there's so much unknown processes that could be attacked. The TAM on this could be enormous. >> We agree. >> Yeah, I know you do, but I think that it's a point worth mentioning because it touches so many different parts of every organization that I think people perhaps don't realize the impact that it could have. >> You know, when listening to you, Kurt, when you look at these young kids, at least compared to me, all the coding and setting up a robot, that's the easy part, they'll pick that up right away. It's really the thought process that goes into identifying new opportunities, and that's, I think, you're challenging them to do that. But learning how to do robots, I think, is going to be pretty easy for this new digital generation. >> Piece of cake. Tom and Kurt, thank you so much for coming on theCUBE with a really fascinating conversation. >> Thank you. >> Thanks, you guys >> I'm Rebecca Knight, for Dave Velante, stay tuned for more of theCUBEs live coverage of UIPath FORWARD. (upbeat music)

(funky guitar music) >> From our studios, in the heart of Silicon Valley, Palo Alto, California, This is theCUBE conversation. >> Everyone welcome to this CUBE conversation here in Palo Alto, California CUBE studios, I'm John Furrier, the host of theCUBE. Were with CUBE alumni, special guest Amit Walia, President of Products & Marketing at Informatica. Amit, it's great to see you. It's been a while. It's been a couple of months, how's things? >> Good to be back as always. >> Welcome back. Okay, Informatica worlds is coming up, we have a whole segment on that but we have been covering you guys for a long long time, data is at the center of the value proposition again and again, it's more amplified now, the fog is lifting. >> Sure. >> And the world is now seeing what we were talking about four years ago. (giggles) >> Yeah. >> With data, what's new? What's the big trends that going on that you guys are doubling down on? What's new, what's changed? Give us the update. >> Sure. I think we have been talking the last couple of years, I think your right, data has becoming more and more important. I think, three things we see a lot. One is obviously, you saw this whole world of digital transformation. I think that has de faintly has picked up so much steam now. I mean, every company is going digital and obviously that creates a whole new paradigm shift for companies to carry out almost recreate themselves, rebuild them, so data becomes the new definition. And that's what we call those things you saw at Infomatica even before data3.org, but data is the center of everything, right? And you see the volume of data growth, you know, the utilization of data to make decisions, whether it's, you know, decisions on the shop floor, decisions basically related to cyber security or whatever it is. And the key to what you see different now is the whole AI assisted data management. I mean the scale of complexity, the scale of growth, you know, multi-cloud, multi-platform, all the stuff that is in front of us, it's really difficult to run the old way of doing things, so that's why we see one thing that we see a whole lot is AI is becoming a lot more mainstream, still early days but it's assisting the whole ability for companies, what I call, exploit data to really become a lot more transformative. >> You have been on this for a while, again we can go back to theCUBE archives, we can almost pull out clips from two years ago, be relevant today, you know, the data control, understanding >> Yeah. >> Understanding where the data governance is-- >> Sure. >> That's always a foundational thing but you guys nailed the chat bots, you have been doing AI was previous announcements, this is putting a lot of pressure on you, the president of the products, you got to get this out there. >> What's new? What's happening inside Informatica? pedaling as fast as you can? What is some of the updates? >> No. >> Gives us the-- >> The best example always is like a duck, right? Your really swimming and feel things are calm at the top and then you are really paddling. No, I think it's great for us. I think, I look at AI's, AI is like, there is so much FUD [fear, uncertainty and doubt] around it and machine learning AI. We look at it as two different ways. One is how we leverage machine learning within our products to help our customers. Making it easy for them, like I said, so many different data types, think of IOT data, unstructured data, streaming data, how do you bring all that stuff together and marry it with your existing transactional data to make sense. So, we're leveraging a lot of machine learning to make the internal products a lot more easier to consume, a lot more smarter, a lot more richer. The second thing is that, we're what we call it our AI, CLAIRE, which we unveiled, if you remember, a couple of years ago at the Informatica World. How that then helps our customers make smarter decisions, you know, in data science and all of these data workbenches, you know, the old statistical models is only as good as they can ever be. So, we leveraging helping our customers see the value proposition of our AI, CLAIRE, then to what I make things that, you know, find patterns, you know, statistical models cannot. So, to me I look at both of those really, leveraging ML to shape our products, which is where we do a lot of innovation and then creating our AI, CLAIRE, to help customers to make smarter decisions, easier decisions, complex decisions, which I called the humans or statistical models, really cannot. >> Well this is the balance with machines and humans. >> Right. >> working together, you guys have nailed this before and I'm, I think this was two years ago. I started to hear the words, land, adopt, expand, form you guys, right? Which is, you got to get adoption. >> Right. >> And so, as you're iterating on this product focus, you got to getting working, making secure your products-- >> Big, big maniacal focus on that one. >> So, tell me what you have learned there because that's a hard thing. >> Right. >> You guy are doing well at it. You got to get adoption, which means you got to listen customers, you got to do the course correction. >> Yeah. >> what's the learnings coming out of that piece of that. >> That's actually such a good point. We've made such, we've always been a customer centric company but as you said, like, as whole world shifted towards a new subscription cloud model, we've really focused on helping our customers adopt our products and you know, in this new world, customers are struggling with new architectures and everything, so we doubled down on what we called customer success. Making sure we can help our customers adopt the products and by the way it's to our benefit. Our customers get value really quickly and of course we believe in what we call a customer for life. Our ability to then grow with our customers and help them deliver value becomes a lot better. So, we really focused, so, we have globally across the board customers, success managers, we really invest in our customers, the moment a customer buys a product from us, we directly engage with them to help them understand for this use case, how you implement the product. >> It's not just self service, that's one thing that I appreciate 'cause I know how hard it is to build products these days, especially with the velocity of change but it's also when you have a large scale data. >> Yeah. >> You need automation, you got to have machine learning, you got to have these disciplines. >> Sure. >> And this is both on your end and but also on the customer. >> Yes. >> Any on the updates on the CLAIRE and some customer learnings you're seeing that are turning into use cases or best practices, what are some of them? >> So many of them. So take a simple example, right? I mean, we think of, we take these things for granted, right? I mean, take note, we don't talk about IOB these days right? All these cell cells, we were streaming data, right? Or even robots on the shop floor. So much of that data has no schema, no structure, no definition, it's coming, right? Netflix data and for customers there is a lot of volume in it, a lot of it could be junk, right? So, how do you first take that volume of data? Create some structure to it for you to do analytics. You can only do analytics if you put some structure to it, right? So, first thing is I've leverage CLAIRE, we help our customers to create, what I call, schema and you can create some structure to it. Then what we do allow is basically CLAIRE through CLAIRE, it can naturally bring what we have the data quality on top of it, like how much of it is irrelevant, how much of it is noise, how much of it really makes sense, so, then, as you said it, signal from the noise We are helping our customers get signal from the noise of data. That's where it AI comes very handy because it's very manual, cumbersome, time consuming and sometimes very difficult to do. So, that's a area we have leveraged creating structure and data quality on top and finding rules that didn't naturally probably didn't exist, that you and me wouldn't be able to see. Machines are able to do it and to your point, our belief is, this is my 100% belief, we believe AI assisting the humans. We have given the value of CLAIRE to our users, so it complements you and that's where we are trying to help our users get more productive and deliver more value to you faster. >> Productivity is multifold, it's like, also, efficiency, people wasting time on project that can be automated, so you can focus that valuable resource somewhere else. >> Yeah. >> Okay, let's shift gears onto Informatica World coming up. Let's spend some time on that. What's the focus this year, the show, it's coming up, right around the corner, what's going to be the focus? What's going to be the agenda? What's on the plate? >> Give you a quick sense on how it's shape up, it's probably going to be our Informatica World. So, it's 20th year, again back in Waze, you know, we love Waze of course. We have obviously, a couple of days lined up over there, I know you guys will be there too. A great set of speakers. Obviously, we will have me on stage, speakers like, we'll have some, the CEO of Google Cloud, Thomas Kurian is going to be there, we'll have on the main stage with Anil, we'll have the CEO of Databricks, Ali, with me, we'll also have CMO of AWS, Ariel, there, then we have a couple of customers lined up, Simon from Credit Suisse, Daniel is the CDO of Nissan, we also have the Head of AI, Simon Guggenheimer from Microsoft as well as the Chief Product Officer of Tableau, Francois Ajenstat, so, we have a great line up of speakers, customers and some of our very very strategic partners with us. If you remember last year, We also had Scott Guthrie there main stage. 80 plus sessions, pretty much 90% lead by customers. We have 70 to 80 customers presenting. >> Technical sessions or going to be a Ctrack? >> Technical, business, we have all kinds of tracks, we have hands on labs, we have learnings, customers really want to learn our products, talk with the experts, some want to the product managers, some want to talk to the engineers, literally so many hands on labs, so, it's going to be a full blown couple of days for us. >> What's the pitch for someone watching that never been Informatica World? Why should they come for the show? >> I'll always tell them three things. Number one is that, it's a user conference for our customers to learn all things about data management and of course in that context they learn a lot about. So, they learn a lot about the industry. So, day one we kick it off by market perspectives. We are giving a sense on how the market is going, how everybody is stepping back from the day to and understanding, where are these digital transformation, AI, where is all the world of data going. We've got some great annalists coming, talkings, some customers talking, we are talking about futures over there. Then it is all about hands on learning, right?, learning about the product. Hearing from some of these experts, right?, from the industry experts as well as our customers, teaching what to do and what not to do and networking, it's always go to network, right, it's a great place for people to learn from each other. So, it's a great forum for all those three things but the theme this year is all about AI. I talked about CLAIRE, I'll in fact our tagline this year is, Clarity Unleashed. We really want, basically, AI has been developing over the last couple of years, it's becoming a lot more mainstream, for us in our offerings and this year we're really taking it mainstream, so, it's kind of like, unleashing it for everybody can genuinely use it, truly use it, for the day to day data management activities. >> Clarity is a great theme, I mean, it plays on CLAIRE but this is what we're starting to see some visiblility into some clear >> Yeah. >> Economic benefits, business benefits. >> Yep. >> Technical benefits, >> Yep. >> Kind of all starting to come in. How would you categorize those three areas because you know, generally that's the consensus these days that what was once a couple years ago was, like, foggy when you see, now you're starting to see that lift, you're seeing economic, business and technical benefits. >> To me it's all about economic and business. So, technology plays a role in driving value for the business, right, I'm a full believer in that, right, and if you think about some of the trends today, right, a billion users are coming into play that will be assisted by AI. Data is doubling every year, you know the volume of data, >> Yep. >> The amount of, and I always say business users today, I mean, I run a business, I want, I always say, tomorrow data, yesterday to make a decision today. It's just in time and that's where AI comes into play. So our goal is to help organizations transform themselves, truly be more productive, reduce operation cost, by the way governance and compliance, that's becoming such a mainstream topic. It's not just basically making analytical decisions. How do you make sure your data is safe and secure, you don't want to get basically get hit by all of these cyber attacks, they're all are coming after data. So, governance, compliance of data that's becoming very, so, those-- >> Again you guys are right on the data thing. >> Yeah. >> I want to get your reaction, you mentioned some stats. >> Sure. >> I've got some stats here. Data explosion, 15.3 zettabytes per year >> Yeah, in global traffic. >> Yeah. >> 500 million business data users and growing 20 billion in connected devices, one billion workers will be assisted by machine learning, so, thanks for plugging those stats but I want to get your reaction to some of these other points here. 80% of enterprises are looking at multicloud, their really evaluating where the data sits in that equation >> Sure. And the other thing is the responsibility and role of the Chief Data Officer >> Yes. >> These are new dynamics, I think you guys will be addressing that into the event. >> Absolutely, absolutely. >> Because organizational dynamics, skill gaps are issues but also you have multicloud. So your thoughts on those to. >> That's a big thing, look at, in the old world, John, Hidrantes is always still in large enterprises, right, and it's going to stay here. In fact I think it's not just cloud, think of it this way, on-premise is still here, it's not going a way. It's reducing in scope but then you have this multicloud world, SAS apps, PAS apps, infrastructure, if I'm a customer, I want to do all of it but the biggest problem is that my data is everywhere, how do I make sense of it and then how do I govern it, like my customer data is sitting somewhere in this SAS app, in that platform, on this on-prem application transaction app I'm running, how do I connect the three and how do I make sense it doesn't get, I can have a governance control around it. That's when data management becomes more important but more complex but that's why AI comes in to making it easier. What are the things we've seen a lot, as you touched upon, is the rise of CDO. In fact we have Daniel from Nissan, she is the CDO of Nissan North America, on main stage, talking about her role and how they have leveraged data to transform themselves. That is something we're seeing a lot more because you know, the role of the CDO is making sure that is not only a sense of governance and compliance, a sense of how do we even understand the value of data across an enterprise. Again, I see, one of the things we going to talk about is system thinking around data. We call it System Thinking 3.0, data is becoming a platform. See, there was OSA-D hardware layer whether it is server, or compute, we believe that data is becoming a platform in itself. Whether you think about it in terms of scale, in terms of governance, in terms of AI, in terms of privacy, you have to think of data as a platform. That's the other big thing. >> I think that is a very powerful statement and I like to get your thoughts, we had many conversations on camera, off camera, around product, Silicon Valley, Venture Capital, how can startups create value. On of the old antigens use to be, build a platform, that's your competitive strategy, you were a platform company and that was a strategic competitive advantage. >> Yes. >> That was unique to the company, they created enablement, Facebook is a great example. >> Yeah. >> They monetized all the data from the users, look where they are. >> Sure. >> If you think about platforms today. >> Sure. >> It seems to be table steaks, not as a competitive advantage but more of a foundational. >> Sure. >> Element of all businesses. >> Yeah. >> Not just startups and enterprises. This seems to be a common thread, do you agree with that, that platforms becoming table steaks, 'cause of if we have to think like systems people >> Mm-hmm. >> Whether it's an enterprise. >> Sure. >> Or a supplier, then holistically the platform becomes table steaks on premer or cloud. Your reaction to that. Do you agree? >> No, I think I agree. I'll say it slightly differently, yes. I think platform is a critical component for any enterprise when they think of their end to end technology strategy because you can't do piece meals otherwise you become a system integrator of your own, right? But it's no easy to be a platform player itself, right, because as a platform player, the responsibility of what you have to offer your customer becomes a lot bigger. So, we obviously has this intelligent data platform but the other thing is that the rule of the platform is different too. It has to be very modular and API driven. Nobody wants to buy a monolithic platform. I don't want to, as a enterprise, I don't buy all now, I'm going to implement five years of platform. You want it, it's going to be like a Lego block, okay you, it builds by itself. Not monolithic, very API driven, maybe microservices based and that's our belief that in the new world, yes, platform is very critical for to accelerate your transformational journeys or data driven transformational journeys but the platform better be API driven, microservices based, very nimble that is not a percussor to value creation but creates value as you go along. >> It's all, kind of up to, depends on the customer it could have a thin foundational data platform, from you guys for instance, then what you're saying, compose. >> Of different components. >> On whatever you need. >> For example you have data integration platform, you can do data quality on top, you can do master data management on top, you can provide governance, you can provide privacy, you can do cataloging, it all builds. >> Yeah. >> It's not like, oh my gosh, I have go do all these things over the course of five years, then I get value. You got to create value all along. >> Yeah. >> Today's customers want value like, in two months, three months, you don't want to wait for a year or two. >> This is the excatly the, I think, the operating system, systems mindset. >> Yes. >> You were referring too, this is kind of how enterprises are behaving now. There is the way you see on-premise, >> Yep. >> Thinking around data, cloud, multicloud emerging, it's a systems view distributed computing, with the right Lego blocks. >> That's what our belief is. That's what we heard from customers. See our, I spend most of my time talking to customers and are we trying to understand what customers want today and you know, some of this latent demands that they have, sometimes can't articulate, my job, I always end up on the road most of the time, just hearing customers, that's what they want. They want exactly to your point, a platform that builds, not monolithic, but they do want a platform. They do want to make it easy for them not to do everything piece meal. Every project is a data project. Whether it's a customer experience project, whether it's a governance project, whether it's nothing else but a analytical project, it's a data project. You don't repeat it every time. That's what they want. >> I know you got a hard stop but I want to get your thoughts on this because I have heard the word, workload, mentioned so many more times in the past year, if there was a tag cloud of all theCUBE conversations where the word workload was mentioned, it would be the biggest font. (laughs) >> Yes. >> Workload has been around for a while but now you are seeing more workloads coming on. >> Yeah. >> That's more important for data. >> Yes. >> Workloads being tied into data. >> Absolutely. >> And then sharing data across multiple workloads, that's a big focus, do you see that same thing? >> We absolutely see that and the unique thing we see also is that newer workloads are being created and the old workloads are not going away, which is where the hybrid becomes very important. See, we serve large enterprises and their goal is to have a hybrid. So, you know, I'm running a old transaction workload order here, I want to have a experimental workload, I want to start a new workload, I want all of them to talk to each other, I don't want them to become silos and that's when they look to us to say connect the dots for me, you can be in the cloud, as an example, our cloud platform, you know last time, we talked about a 5 trillion transactions a month, today is double that, eight to ten trillion transactions a month. Growing like crazy but our traditional workload is also still there so we connect the dots for our customers. >> Amit, thank you for coming on sharing your insights, obviously you guys are doing well. You've got 300,000 developers, billions in revenue, thanks for coming on, appreciate the insight and looking forward to your Informatica World. >> Thank you very much. >> Amit Walia here inside theCUBE, with theCUBE conversation, in Palo Alto, thanks for watching.

>> from our studios in the heart of Silicon Valley. HOLLOWAY ALTO, California It is a cube conversation. >> Welcome to this. Keep conversation here in Palo Alto, California. Keep studios. I'm John for the host of the Cube were with Cuba Lum nine. Special gas *** while the president of products and marking it in from Attica. I make great to see you has been a while, but a couple months. How's things good to be >> back has always >> welcome back. Okay, so in dramatic, a world's coming up. We have a whole segment on that, but we've been covering you guys for a long, long time. Data is at the center the value proposition. Again and again, it's Maur amplified. Now the fog is lifting. Show in the world is now seeing what we think we were told about four years ago with data. What's new? What's that? What's the big trends going on that you guys air doubling down on what's new? What's changed? Here's the update. Sure, >> I think we've been talking for the last couple of years. I think you're right. It is becoming more and more important. I think three things we see a lot one is. Obviously you saw this whole world of district transformation. I think that definitely has picked up so much steam. Now. I mean, every company's going digital and And that the officer, that creates a whole new paradigm shift for companies to come almost recreate themselves remained. And so that data becomes the new definition. And that's what we call the thing is you side and fanatical even before the data three dollar word. But data is the center of everything, right? And in basically see the volume of data growth, you know, the utilization of data to make decisions, whether it's, you know, a decision on the shop floor decisions basically related to a cyber security or whatever it is on the keel of your signal is different now. Is the hole e. I assisted data management. I mean the scale ofthe complexity, the scale of growth, you know, multi cloud, multi platform, all the stuff that's in front of us. It's very difficult to run the old way of doing things. So that's where we see the one thing that we see a whole lot is is becoming a lot more mainstream still early days. But it's assisting the whole ability for companies to what I call exploit data to really become a lot more transformative. >> You've been on this for a while again. We get what we had to go back to. The Cube archives were almost pullout clips from two years ago be relevant today. You know the data control understanding. You know that. You know, I understand where the date of governance is ours. So is the foundational thing. But you guys nailed the chat box. You've been doing a Iot of previous announcements. This is putting a lot of pressure on you. The president of products you got. Get this out there. What's new? What's happening inside in from Attica? He's pedaling as fast as you can. What are some of the updates? Give >> us the best example. I was just like the duck, right? You know, you're really selling your Felix comma the top and then you're really finally I think it's great for us. I think I look a tw ee eye ee eye. It's like this so much fun around machine learning. We look at it, it's two different ways. One is how we leverage machine learning Vidin our products to help our customers, making it easy for them to. As I said, so many different data types Think of I ot data instructor data streaming data. How do you bring all that stuff together and married with your existing transaction? It'LL make sense. So we're leveraging a lot of machine learning to make the internal products a lot more easier to consume. A lot more smarter, a lot more. Richard, The second thing is that we what we call his are a clear which we are. Really? If you remember a couple years ago and in America World, how guard then helps our customers make smarter decisions in the in the one of data signs and all these new data workbench is, you know, the old statistical models are only as good as they can never be. So we're leveraging, helping our customers take the value proposition of r B. I clear then what? I make things that, you know, find patterns that, you know, statistical models cannot. So, to me, I look att, both of those really leveraging ml to shape our products, which is married to a lot of innovation and then creating our eclair to that help customers make smarter decisions, easier decisions, complex decisions. Which would I kill the humans or the statistical models? >> Really Well, this is the balance between machines and humans working together. And you guys have nailed this before. And I think this was two years ago. I started to hear the words land adopt, expand from you guys. Write, which is you've got to get adoption, right? And so as you're iterating on this product, focus, you've got to get it working your >> butt looks big, maniacal focus of that. Let's talk about >> what? What you've learned there because that's a hard thing. You guys are doing well at it. We've got to get a doctor. Means you gotta listen to customers going do the course correction. What's the learning is coming out of that. That >> is actually such a good point. We made such. We were always a very customer centric company. But as you said like that, as the world shifted towards a new subscription cloud model, be really focused on helping our customers adopt our products. And you know, in this new world, customers are also struggling with new architectures and everything, so we double down on what we call customer success, making sure we can help our customers adopt the products. And whether it's it's, it's too will benefit. Our customers can value very quickly. And of course, we believe in what we call a customer for life. Our ability to then grow without customers and held them deliver value becomes a lot better, so we're really for So we have globally across the board customers, success managers, we really invest in a customer's. The moment we a customer, buys a product from us, we directly engage with them to help them understand forthis use case. How you >> implement its not just self serving. That's one thing which I appreciate because you know, how hard is it? Build products these days, especially with philosophy, have changed, but it's also we have in the large scale data. You need automation. You've gotta have machine learning. You gotta have these disciplines. Sure this both on your own, but also for the customer. Yes, any updates on the Clare and some customer learnings, and you're seeing that air turning into either use cases or best practices, >> many of them. So take a simple example, right? I mean, we think if we take these things for granted, right? I mean, taking over here to talk about I open these designs on all of these sensors. We were streaming data, right? Or even robots in the shop floor. Sort of. That data has no schema, no structure, nor definition. It's coming like Netflix data has to. And for customers, there's a lot of volume on it. None of it could be junk. Right? So how do you first think that volume of data creates some structure to it for you to do analytics? You You can only do analytics if you put some structure to it. Right. So first thing is that we leverage clear help customers create what are called scheme, and you can create some structure to it. Then what we do allow is basically clear through clear. It can naturally bring what we have. The data quality on top of it. Like how much of it is irrelevant? How much of it is noise? How much would it really make sense? So then what was you said? It signal from the noisy were helping customers get signal from the noise of data. That's where it becomes very handy because It's a very man will cumbersome, time consuming and something very difficult to do. So that's an area of every have leveraged, creating structure, adding data quality on top and finding rules that didn't probably naturally didn't exist, that you and he would be able to see machines are able to do it. And to your point, our belief is this is my one hundred percent believe we believe in the eye assisting the humans. We have given the value ofthe Claire, tow our users that it compliments you. And that's where we're trying to help our users get more productive and deliver more value faster. >> Productivity is multifold. It's like also efficiency. You don't want people wasting time on project that can be automated. You focus that valuable resource somewhere else. Yeah, okay, so let's shift gears on. Taking from Attica World coming up. Let's spend some time on that. What's the focus this year? The show. It's coming up right around the corner. What's going to focus on what's going to be the agenda? What's on the plate >> give you a quick sense of how it's the shape of its going to be our biggest in from Attica well, so it's twentieth year again. Back in Vegas, you know we love Vegas. Of course, we have obviously a couple of days line up over there and you guys will be there too Great sort of speakers. So obviously we'LL have mean stage speakers like so we'LL have some CEO of Google Cloud Thomas Korean is going to be there We'LL have on main stage with Neil We'LL have the CEO of dealer Breaks Ali with me We'LL also have the CMO off a ws ariel there. Then we have a couple of customers lined up Simon from Credit Suisse Daniels CD over Nissan. We also have the head of the eye salmon Guggenheimer from Microsoft, as well as the chief product officer of Tableau Francois on means. So we have a great lineup of speakers, customers and some of our very, very strategic partners with us. Remember last year we also had Scott country. That means too eighty plus session's pretty much a ninety percent led by customers. We have seventy to eighty customers. Presentable sessions, technical business. We have all kinds of tracks. We have hands on labs. We have learnings. Customers really want to come. Lana products. Talked to the experts someone to talk to the product manager. Someone talk to the engineers literally, so many hands on lab. So it's going to be a full blown a couple of days. What's >> the pitch for someone watching that has never been in from Attica world? Why should they come for the show? >> I always tell them three things. Number one is that it's a user conference for our customers to known all things about data management. And then, of course, in that context, they learned a lot about so they learned a lot about the industry. So Dave one we kicked around by market perspective giving Assessor the market is going, how everybody should be stepping back from the data and understanding. Where are these district transformation? E I? Where is the world of detail going? We have some great analysts coming, talking, some customers talking. We'LL be talking about futures over there. Then it is all about hands on learning, right, learning about the product hearing from some of these experts, right from the industry experts as well as our customers teaching what to do, what not to do and networking. It's always great to network writes a great place for people to learn from each other. So it's a great forum for for two of those three things. But the team this year is all around here. I talked about clear. In fact, our tagline Dissidents, clarity unleashed. I really want to, basically has been developing for the last couple of years. It's become becoming a lot who means stream for us in our offerings. And this year we really are taking it being stream. So it's kinda like unleashing it where everybody can genuinely use a truly use it from the data data management. Active >> clarity is a great team. I mean plays on Claire, But this is what we're starting to see. Some visibility into some clear economic benefits, business benefits, technical benefits, kind of all starting to come in. How would you categorize those three years? Because, you know, that's generally the consensus these days is that what was once a couple years ago was like foggy. When you see now you're starting to see that lift. You see economic, business and technical benefits. >> To me, it's all about economic and business. Anniversary technology plays a role in driving value for the business, my gramophone believing that right? And if you think about some of the trans today, right, ah, billion users are coming into play. That he be assisted by data is doubling every year. You know, the volume of data and and amount ofthe amount off. And I obviously business users today. I mean, when I run a business I want, I always say, tomorrow's data yesterday to make a decision. Today it's just in time, and that's where it comes into play. So our goal is to help organizations transformed themselves truly, you know, be more productive, produce operational cost by the government and compliance that's becoming such a mainstream topic. It's not just basically making analytical decisions. How do you make sure that your data is safe and secure? You don't want to get basically hit by any of these cyberattacks. They're all coming after data. So governance and compliance of data that's becoming but in the end got stored on the >> data thing. Yeah, I wanna get your reactions. You mention some shots like some stats here. Date explosion fifteen point three's added bytes per year in traffic, five million business data users and growing twenty billion connected devices. One billion workers will be assisted by learning. So no thanks for putting those stats, but I want to get your reactors. Some of these other points here, eighty percent of enterprises air that we're looking at multi cloud. They're really evaluating their where the data sits in that kind of equation short. And then the other thing is that the responsibility and role of the chief data? Yes, these air new dynamic. I think you guys will be addressing that. And because organizational stuff dynamics, skill, gaps are issues. But also you have multi clouds form. >> And that's a big thing. I mean, look thin. The old World John hatred Unite is always too large in the price is right, and it's going to stay here. In fact, I think it's not just cloud. Think of it this way, one promised. Ilya is not going away. It's producing in school. But then you have this multi cloud world sassafras pass halves infrastructure. If I'm a customer, I want to do all of it. But the biggest problem comes, you said, is that my data is everywhere. How do I make sense of it? And then how do I go on it like my customer data sitting somewhat in this *** up in that platform in this on prime application transaction after running hardware Connect three. And how do I make sense? It doesn't get. I can have a governance and control around it. That's where data management becomes more important but more complex. But that's where it comes into making it easier. One of the things we've seen a lot of you touched upon is the rise of the Sirio. In fact, we have Danielle from the Sanchez, a CD off Mr North America on Main Stage, talking about her rule and how they've leveraged data to transform themselves. That is something we're seeing a lot more because you know, the rule of the city or making sure there is, You know, not only a sense of governance and compliance, a sense of how to even understand the value of dude across an enterprise again. I see one of the things we're gonna talk about this. It's old system thinking around data. We call it system, thinking three daughter data is becoming a platform C. There was always that the hard way earlier, whether it is server or computer. We believe that data is becoming a platform in itself. Whether you think about it in terms of scary, in terms ofthe governance, in terms of e i times a privacy, you have to think of data as a platform. That's the that's the other. But >> I think that is very powerful statement, and I'd like to get your thoughts. You know, we've had many countries. Is on camera off camera around product. Silicon Valley Venture Capital. How come started to create value. One of the old adage is used to be build a platform. That's your competitive strategy. There were a platform company, and >> that was a >> strategic competitive advantage that is unique to the company. And they created enablement. Facebook's a great example. Monetize all the data from users. Look where they are short. If you think about platforms today, Charlie, it seems to be table stakes. Not as a competitive is more of a foundational element of all businesses, not just startups enterprises. This seems to be a common thread. Do you agree with that that platforms were becoming table stakes? Because if we have to think like systems people, whether it's an enterprise show supplier ballistically the platform becomes stable. States that could be on primary cloud. Your reactions >> are gonna agree that I'll say it slightly differently. Yes, I think I think platform is a critical competent for any enterprise when they think of their entire technology strategy because you can't do peace feels otherwise. You become a system integrated over your own right. But it's not easy to be a platform clear itself, right? Because it's a platform player. The responsibility of what you have to offer your customer becomes a lot bigger. So we always t have this intelligent in a platform. Uh, but the other thing is that the rule of the platform is different. It has to be very modeling and FBI driven. Nobody wants to buy a monolithic platform. I don't want as an enterprise it on my own. I'm gonna implement five years a platform you want. It's gonna be like a Lego block. Okay? You It builds by itself, not monolithic, very driven my micro services based And that's our belief that in the new World, yes, black form is very critical for youto accelerate your district transformation journeys or data driven district transformation journeys but the platform better be FBI driven micro services based, very nimble that it's not a precursor to value creation but creates value as you want. It's >> all kind of depends on the customer. Get up a thin, foundational data platform from you guys, for instance. And then what you're saying is composed off >> different continents. For example, you have a data integration platform, then you can do the quality on top. You do. You could do master data management on top. You can provide governance. You can provide privacy. You could do cataloging it all builds its not like Oh my gosh, I have to go do all these things over the course of five years. Then I'LL get value. You gotta create value all along. Today's customers want value like in two months. Three months. You don't wait for a year or >> two years. This is exactly why I think the kind of Operation Storm systems mindset that you're referring to. This is kind of enterprises. They're behaving others the way that you see on premise, thinking around data and cloud multi cloud emerging. It's a systems view of distributed computing with the right block Lego blocks >> that that's what I believe is. That's what we heard from customers. He r I spend most of my time traveling, talking to customers on my way to try to understand what customers want today. And you know some of this late and demand that they have it. They can't sometimes articulate my job. I always end up on the road most of the time just to hearing customers, and that's what they want. They want exactly appoint a platform that Bill's not monolithic, but they don't want the platform. They do want to make it easy for them not to do everything piecemeal. Every project is a data project, whether it's a customer experience project, whether it's the government's project, whether it is nothing else but an analytical. It's a data project, but you don't want to repeat it every time. That's what they want, >> but I know you got a hard stuff, but I want your thoughts on this because I've heard the word workload mentioned so many more times these in the past year. It was a tad cloud of all the cute conversation with a word workload was mentioned to be the biggest fund. Yes, work has been around for a while, but nice seeing more and more workloads coming on. Yeah, that's more important for day that we're close to being tied into the data absolutely, and then sharing data cross multiple workloads. That's a big focus. Perhaps you see that same thing. >> We absolutely see that, Onda. The unique thing that we see also that new work towards getting created and the old workloads are not going away, which is where the hybrid becomes very important. See, these serve large enterprises and their goal is to have an hybrid. So, you know, I'm running a old transaction workload over here. I want to have an experimental workload. I want to start a new book. I want all of them to talk to each other. I don't want them to become silos. And that's when they look to us to say connect the dots for me. You can be in the cloud as an example. Our cloud platform, you know, last time and fanatical will remember we talked about like it wasn't five trillion transactions a month, but it's double that it to pen trillion transaction a month growing like crazy. But our traditional workload is also still there. So we connect the dots for customers. >> I mean, thank you for coming on sharing the insights house. You guys doing well? You got three thousand developers, billions in revenue. Thanks for coming. Appreciate the insight. And looking for Adrian from Attica World. Thank you very much. Meanwhile, here inside the Cuban shot furry with cute conversation in Palo Alto. Thanks for watching.

>> Narrator: Live from the Wynn Hotel in Las Vegas, it's theCUBE covering Magento Imagine 2018. Brought to you by Magento. >> Hey, welcome back to theCUBE. We are continuing our coverage live from the Wynn Las Vegas at Magento Imagine 2018. We've had a really exciting day talking about commerce and how it's limitless and changing dramatically. Joining me next is Sucharita Kodali, the vice president and principal analyst at Forrester. Sucharita, it's great to have you on theCUBE. >> Thanks for having me, Lisa. >> So commerce is limitless. We've been hearing this thematically all day. You primarily are working with retailers on their digital strategies. And you've been doing this for a long time. Let's talk about the evolution that you've seen in the retail space with everybody expecting to have access to whatever they want to buy in their pockets. >> Right, right, right. I would say, so I've been working in the retail industry for the last two decades. I've been an analyst for the last 10 plus years. I've really seen a number of changes. And if I had to just summarize the biggest changes, one is just the inventory across different retail channels. So, that's definitely been a huge huge one. It's like, how do you, how do you order online, but then fulfill the item from a physical store or fulfill the item from another store? So those are, that's basically the digital transformation of retailers. Those are investments that companies like WalMart and Target have really been doubling down on and focusing on. The second big change is Amazon. And they single-handedly have transformed the retail industry. They have increased consumer expectations. And what Amazon's also done is reinvented retail as a business model. Because it is no longer about just selling product and being profitable selling that product. Amazon actually is not profitable with a lot of the items that it sells. It makes money in other ways. And it is probably what I would describe as America's first retail conglomerate. And that becomes a really interesting question for other companies to compete, do you have to become a retail conglomerate? Then, the third big change is just brand selling direct to consumer. I remember when I started at Forrester, my very first project was with a large consumer electronics company that asked, Well, should we even sell directly to consumers? There's channel conflict and issues with our distributors. And now, that's not even a factor. It's sort of table stakes you have to sell direct to consumer. And that's probably where we'll continue to see a lot of retail sales in the future. >> So the Amazon model, we expect to be able to get whatever we want whenever we want it, have it shipped to us either at home or shipped to us so we can go pick it up at a store. It's really set the bar. In fact, they just announced the other day that a hundred million Amazon Prime members. I know people that won't buy something if it's not available through Prime. But I think this morning the gentleman that was on main stage from Amazon said at least 50% of their sales are not products they sell, they're through all of the other retailers that are using Amazon as a channel as part of their omni-channel strategy. If you think of a retailer from 20 years ago, how do they leverage your services and expertise and advice to become omni-channel? Because as today, you said essentially it's table stakes for companies to have to sell to consumers. >> Yeah, yeah. There are so many questions that really require, I call it destroying the retail orthodoxies. And retail has historically been about buyers and merchandisers buying goods. There's the old expression in retail, You stack 'em high and watch 'em fly. And that is just where buyers would, Take a company like Toys R Us, they would basically take what Mattel and Hasbro told them to buy. They would buy a ton of it, put it in stores. And because there was less competition back in the '80s, consumers actually would buy that merchandise. And unfortunately, the change for retailers is that consumers have so much more choice now. There's so such more innovation. There are small entrepreneurs who are creating fabulous products, consumer tastes have changed. And this old paradigm of Mattel and Hasbro, or kind of fill in the blank with whatever vendors and suppliers, pushing things is no longer relevant. So, there was just an article in the journal today about how Hasbro sales were down by double digits because Toys R Us is now going to go out of business. So those are the kinds of things that retailers who did not adjust to those changes, they are the ones that really suffer. They don't find ways to develop new inventory, they don't find new channels for growth, and they don't protect their own. They don't build a moat around their customers like Amazon has done, or they don't find ways to source inventory creatively. That's where the problems are. >> You think that's more of a function of a legacy organization; having so much technology that they don't know how to integrate it all together? What do you think are some of the forcing functions old orthodoxies that companies that don't do it well are missing? >> Yeah, it's a lot of it is just in the old ways of doing business. So, a lot of it is being heavily dependent, for instance, on buyers and merchandisers buying things. I mean, one of the biggest innovations that Amazon realized was that, look you can sell things without actually owning the inventory. And that is, their entire, what we call the third party marketplace, and that is just so simple. But if you were to ask a buyer at a major retailer a decade or two ago, "Why do you have to buy the inventory?" their response would be, Well, you have to buy the inventory, that's just the way it is. And it's like, well why? Why don't you try to find a new way to do business? And they never did. But it took Amazon to figure that out. And the great irony of why so many retailers continue to struggle is that Amazon has exposed the playbook on how to sell inventory without owning it. And so few retailers to this day have adopted that approach. And that's the great irony I think, is that that's the most profitable part of Amazon's business is that third party marketplace. And every retailer I've talked to is like, Oh, it's really hard. We can't do that. But, the part of Amazon's business that everyone is looking to imitate is their fast shipping. Which, is the most expensive part of their business. Amazon is only able to afford the fast free shipping because of the third party marketplace. Other retailers want to get the fast free shipping without the marketplace. And it just doesn't make any sense. And that's really the heart of the challenge is that they just don't think about alternative business models. They don't want to change the way that they've historically run their businesses. And some of this could mean that merchants are not as powerful in organizations. And maybe that's part of the pushback is that, there could be a lot of people who lose jobs. The future will be robo-buyers and financial services you have robo-advisors, why not robo-planners in retail? >> So one of the keys then, of eliminating some of the old orthodoxies for merchants is to be able to pivot and be flexible. But it has to start from where in an organization from a digital strategy perspective? Where do you help an organization not fall into the Toys R Us bucket? >> Yeah, I think a lot of it does have to start with merchandising and putting in some interesting digital tools to help merchants be more flexible. So, you want to flex to supply and demand. And some of that comes with integrating marketplaces into your own experience. Some of it can be investing in 3D printers that can make things that are plastic or metals based on demand. That's something that I always wondered why Toy R Us didn't, for instance, make Fidget Spinners on demand. Why did you have to get them with a six month leave time from China, it never made any sense. You can scale service, so use technology to match great store associates with a customer who may have a question. And you don't have to be in the same store. It can be a Facetime call with somebody who is far away. But very few retailers do that. And finally, the last bit is really to look at new alternative business models and finding new ways of making money beyond just selling inventory. >> That's really key because there are so many oppurtunities when companies go omni-channel of not just increasing sales and revenue, but also reducing attrition, making the buying process simple and seamless. Everybody wants one click, right? >> Right. >> Super seamless, super fast, and relevant. It's got to be something if you're going to attract my business, you need to be able to offer something where you know me to a degree. >> Absolutely. >> Or know what it is I might have a propensity to buy. >> Absolutely. And that's the entire area of personalization. And that personalization can be anything from a recommendation that I give you. It can be proactively pushing a recommendation. That's what companies like Stitch Fix do is I tell you what I want and then they send you a box in the mail of things I think you would like and oh, by the way are your size and within your budget. It can be customization. One of Nike's most successful parts of their business is their Nike ID program which allows you to customize shoes according to colors and different sort of embellishments that you may like. And that's exactly the kind of thing that more retailers need to be looking at. >> What are some of the trends maybe that a B2B organization might be able to love or some of the conveniences that we have as consumers and we expect in terms of-- Magento, I was looking on their website the other day and a study that they've done suggests 93 percent of B2B buyers want to be able to purchase online. So, new business models, new revenue streams, but it really is a major shift of sales in marketing to be able to deliver this high velocity low touch model. What are some of the things that a business like a Magento, could learn from say a Nike with how they have built this successful omni-channel experience? >> Well, interestingly I think one of the most important things to recognize is that every B2B buyer is also a B2C buyer. And their expectations are set by their experiences in B2C. So, if you have everything from all of the information at your fingertips, all of that information is optimized for mobile devices. You have different ways to view that information, you have all of your loaded costs, like shipping, or tax, or if there's cross-border. All of the information related to the time to ship, any customs and duties, all of that needs to be visible because in any experience that you have with say a site like Amazon, you're going to get that information. So, the expectation is absolutely there to have it in any situation whether it's B2B or whether it's buying components or kind of very long tail items. That's basically the cost of doing business at this point, is that you have to deliver all of the information that the customer wants and needs. And if you don't, the customer is just going to opt to go purchase that product at whatever destination offers it. >> Somewhere else. >> And somebody will. That's the challenge when you have 800 thousand Plus eCommerce sellers out there selling every product imaginable in the both B2B and B2C landscape. >> So, on the data side there's so much data out there that companies have any type of business to be able to take advantage of that. I know that there's, BI has so much potential. Are you hearing retailers start to embrace advanced analytics techniques, AI machine learning, Where are they with starting to do that? I know that some eyeglass companies have virtual reality augmented reality type of apps where you can kind of try on a pair of frames. Where are you seeing advanced analytics start to be successful and help retailers to be able to target buyers that might say, oh, I can't try that on? No, I want to go somewhere that I can touch and feel it. >> Yeah, well, it's emerging still. I mean, retailers have a lot of data. I think they're trying to figure out where is it most useful. And one of the places where it is incredibly useful is in the backend with fraud management. So, after retailers were forced to put in chip cards as a payment form, what you started to see was more of the fraud shifting to eCommerce. I just had two credit cards that had to be shut off because of E-commerce fraud. But that is where you see the fraudsters going to. And what you see as a result of that is some innovators in that space technology companies really leveraging machine learning, AI, other advanced data techniques to identify fraudulent transactions and to better help retailers eliminate or reduce the percent of transactions that have to then be charged back. So, that's probably one of the most promising areas. There are others that are emerging. We're seeing more visual recognition technologies. House for instance, is excellent at that and Pinterest too. If there's part of an image you like you can click on it or you can tap it and see other images like that. And that's incredibly difficult. And it was even more difficult 10-15 years ago, but it's becoming easier. There's the voice element, voice to text or text to voice. I think that the best applications they're often in customer service, there are so many interactions that happen anywhere in a consumer facing world. It doesn't even have to be within retail. You can think about the complaints to the airline industry or to a bank. And a lot of it falls into a black hole. You always hear that oh, This call may be recorded, but it is really difficult to go back and transcribe that. And to really synthesize that into major themes. And what ML in particular can do is to basically pull out those themes, it can automate all of that, and can give insights as to what you could be doing, what you should be doing, what are the opportunities that you may not have even known existed. So there are definitely emerging places. I mean even a visual recognition, so we talked about House and Pinterest. Another great example is the computer vision that you have in the Amazon Go stores. And there's a robot that the Wal Mart stores are now testing to go find if there are gaps in the inventory that need to be filled. Or if something is running low or out of stock. So there are definitely some interesting applications, but it's still early days for sure. >> So last question, we've got to wrap here, but, we're in April 2018, what are some of the, your top three recommendations for merchants, as they prepare for say Black Friday coming up in what, six or eight months. What are you top three recommendations for merchants to be successful and be able to facilitate a seamless online offline experience? >> Well, we always have kind of imbalances between supply and demand, and that's where I do think things like third party sellers, third party marketplaces are huge. So to be able to leverage that is certainly one opportunity. Another is to think creatively about promotions. In Japan they have these promotions called Fukubukuro promotions, and it's basically like grab bags of like all the left over inventory. But then they basically put it into mystery bags where you can buy it for half off. And consumers line up around the block at stores to go buy these grab bags. Because they also have also like a gamified approach where, you know, one of out 10 of the bags will have like an Ipad or some really high value item. So people really like these things, and they have trading parties. So just new ways of having promotions beyond just the typical door busters that retailers think about. And then kind of third I think is just try to pace out the demand. One of the big issues in E-commerce has been just the burst in demand that always happen in December. And that creates a lot of problems from the standpoint of actually shipping the orders. So the more that you can pull those transaction forward into November, the better off you are from a fulfillment and supply chain standpoint. >> Alright Sucharita thank you so much for stopping by theCUBE >> Thanks Lisa >> And sharing your insights on the trends and what's going on in the commerce and E-commerce space. Really enjoy talking with you. >> Nice to talk to you too. >> We want to thank you for watching. You're watching theCUBE live from Magento Imagine 2018, I'm Lisa Martin. Stick around, I'll be back with my next guest after a short break. (upbeat music)

>> [Announcer] Live from New York, it's theCube, covering the IBM Machine Learning Launch Event brought to you by IBM. Now, here are your hosts, Dave Vellante and Stu Miniman. >> Welcome back to the Waldorf Astoria, everybody. This is theCube, the worldwide leader in live tech coverage. We're covering the IBM Machine Learning announcement. IBM bringing machine learning to its zMainframe, its private cloud. Dinesh Nirmel is here. He's the Vice President of Analytics at IBM and a Cube alum. Dinesh, good to see you again. >> Good to see you, Dave. >> So let's talk about ML. So we went through the big data, the data lake, the data swamp, all this stuff with the dupe. And now we're talking about machine learning and deep learning and AI and cognitive. Is it same wine, new bottle? Or is it an evolution of data and analytics? >> Good. So, Dave, let's talk about machine learning. Right. When I look at machine learning, there's three pillars. The first one is the product. I mean, you got to have a product, right. And you got to have a different shared set of functions and features available for customers to build models. For example, Canvas. I mean, those are table stakes. You got to have a set of algorithms available. So that's the product piece. >> [Dave] Uh huh. >> But then there's the process, the process of taking that model that you built in a notebook and being able to operationalize it. Meaning able to deploy it. That is, you know, I was talking to one of the customers today, and he was saying, "Machine learning is 20% fun and 80% elbow grease." Because that operationalizing of that model is not easy. Although they make it sound very simple, it's not. So if you take a banking, enterprise banking example, right? You build a model in the notebook. Some data sense build it. Now you have to take that and put it into your infrastructure or production environment, which has been there for decades. So you could have a third party software that you cannot change. You could have a set of rigid rules that already is there. You could have applications that was written in the 70's and 80's that nobody want to touch. How do you all of a sudden take the model and infuse in there? It's not easy. And so that is a tremendous amount of work. >> [Dave] Okay. >> The third pillar is the people or the expertise or the experience, the skills that needs to come through, right. So the product is one. The process of operationalizing and getting it into your production environment is another piece. And then the people is the third one. So when I look at machine learning, right. Those are three key pillars that you need to have to have a successful, you know, experience of machine learning. >> Okay, let's unpack that a little bit. Let's start with the differentiation. You mentioned Canvas, but talk about IBM specifically. >> [Dinesh] Right. What's so great about IBM? What's the differentiation? >> Right, exactly. Really good point. So we have been in the productive side for a very long time, right. I mean, it's not like we are coming into ML or AI or cognitive yesterday. We have been in that space for a very long time. We have SPSS predictive analytics available. So even if you look from all three pillars, what we are doing is we are, from a product perspective, we are bringing in the product where we are giving a choice or a flexibility to use the language you want. So there are customers who only want to use R. They are religious R users. They don't want to hear about anything else. There are customers who want to use Python, you know. They don't want to use anything else. So how do we give that choice of languages to our customers to say use any language you want. Or execution engines, right? Some folks want to use Park as execution engine. Some folks want to use R or Python, so we give that choice. Then you talked about Canvas. There are folks who want to use the GUI portion of the Canvas or a modeler to build models, or there are, you know, tekkie guys that we'll approach who want to use notebook. So how do you give that choice? So it becomes kind of like a freedom or a flexibility or a choice that we provide, so that's the product piece, right? We do that. Then the other piece is productivity. So one of the customers, the CTO of (mumbles) TV's going to come on stage with me during the main session, talk about how collaboration helped from an IBM machine learning perspective because their data scientists are sitting in New York City, our data scientists who are working with them are sitting in San Jose, California. And they were real time collaborating using notebooks in our ML projects where they can see the real time. What changes their data scientists are making. They can slack messages between each other. And that collaborative piece is what really helped us. So collaboration is one. Right from a productivity piece. We introduced something called Feedback Loop, whereby which your model can get trained. So today, you deploy a model. It could lose the score, and it could get degraded over time. Then you have to take it off-line and re-train, right? What we have done is like we introduced the Feedback Loops, so when you deploy your model, we give you two endpoints. The first endpoint is, basically, a URI, for you to plug-in your application when you, you know, run your application able call the scoring API. The second endpoint is this feedback endpoint, where you can choose to re-train the model. If you want three hours, if you want it to be six hours, you can do that. So we bring that flexibility, we bring that productivity into it. Then, the management of the models, right? How do we make sure that once you develop the model, you deploy the model. There's a life cycle involved there. How do you make sure that we enable, give you the tools to manage the model? So when you talk about differentiation, right? We are bringing differentiation on all three pillars. From a product perspective, with all the things I mentioned. From a deployment perspective. How do we make sure we have different choices of deployment, whether it's streaming, whether it's realtime, whether it's batch. You can do deployment, right? The Feedback Loop is another one. Once you deployed, how do we keep re-training it. And the last piece I talked about is the expertise or the people, right? So we are today announcing IBM Machine Learning Hub, which will become one place where our customers can go, ask questions, get education sessions, get training, right? Work together to build models. I'll give you an example, that although we are announcing hub, the IBM Machine Learning Hub today, we have been working with America First Credit Union for the last month or so. They approached us and said, you know, their underwriting takes a long time. All the knowledge is embedded in 15 to 20 human beings. And they want to make sure a machine should be able to absorb that knowledge and make that decision in minutes. So it takes hours or days. >> [Dave] So, Stu, before you jump in, so I got, put the portfolio. You know, you mentioned SPSS, expertise, choice. The collaboration, which I think you really stressed at the announcement last fall. The management of the models, so you can continuously improve it. >> Right. >> And then this knowledge base, what you're calling the hub. And I could argue, I guess, that if I take any one of those individual pieces, there, some of your competitors have them. Your argument would be it's all there. >> It all comes together, right? And you have to make sure that all three pillars come together. And customers see great value when you have that. >> Dinesh, customers today are used to kind of the deployment model on the public cloud, which is, "I want to activate a new service," you know. I just activate it, and it's there. When I think about private cloud environments, private clouds are operationally faster, but it's usually not miniature hours. It's usually more like months to deploy projects, which is still better than, you know, kind of, I think, before big data, it was, you know, oh, okay, 18 months to see if it works, and let's bring that down to, you know, a couple of months. Can you walk us through what does, you know, a customer today and says, "Great, I love this approach. "How long does it take?" You know, what's kind of the project life cycle of this? And how long will it take them to play around and pull some of these levers before they're, you know, getting productivity out of it? >> Right. So, really good questions, Stu. So let me back one step. So, in private cloud, we are going, we have new initiative called Download and Go, where our goal is to have our desktop products be able to install on your personal desktop in less than five clicks, in less than fifteen minutes. That's the goal. So the other day, you know, the team told me it's ready. That the first product is ready where you can go less than five clicks, fifteen minutes. I said the real test is I'm going to bring my son, who's five years old. Can he install it, and if he can install it, you know, we are good. And he did it. And I have a video to prove it, you know. So after the show, I will show you because and that's, when you talk about, you know, in the private cloud side, or the on-premise side, it has been a long project cycle. What we want is like you should be able to take our product, install it, and get the experience in minutes. That's the goal. And when you talk about private cloud and public cloud, another differentiating factor is that now you get the strength of IBM public cloud combined with the private cloud, so you could, you know, train your model in public cloud, and score on private cloud. You have the same experience. Not many folks, not many competitors can offer that, right? So that's another . .. >> [Stu] So if I get that right. If I as a customer have played around with the machine learning in Bluemix, I'm going to have a similar look, feel, API. >> Exactly the same, so what you have in Bluemix, right? I mean, so you have the Watson in Bluemix, which, you know, has deep learning, machine learning--all those capabilities. What we have done is we have done, is like, we have extracted the core capabilities of Watson on private cloud, and it's IBM Machine Learning. But the experience is the same. >> I want to talk about this notion of operationalizing analytics. And it ties, to me anyway, it ties into transformation. You mentioned going from Notebook to actually being able to embed analytics in workflow of the business. Can you double click on that a little bit, and maybe give some examples of how that has helped companies transform? >> Right. So when I talk about operationalizing, when you look at machine learning, right? You have all the way from data, which is the most critical piece, to building or deploying the model. A lot of times, data itself is not clean. I'll give you an example, right. So >> OSYX. >> Yeah. And when we are working with an insurance company, for example, the data that comes in. For example, if you just take gender, a lot of times the values are null. So we have to build another model to figure out if it's male or female, right? So in this case, for example, we have to say somebody has done a prostate exam. Obviously, he's a male. You know, we figured that. Or has a gynocology exam. It's a female. So we have to, you know, there's a lot of work just to get that data cleansed. So that's where I mentioned it's, you know, machine learning is 20% fun, 80% elbow grease because it's a lot of grease there that you need to make sure that you cleanse the data. Get that right. That's the shaping piece of it. Then, comes the building the model, right. And then, once you build the model on that data comes the operationalization of that model, which in itself is huge because how do you make sure that you infuse that model into your current infrastructure, which is where a lot of skill set, a lot of experience, and a lot of knowledge that comes in because you want to make sure, unless you are a start-up, right? You already have applications and programs and third-party vendors applications worth running for years, or decades, for that matter. So, yeah, so that's operationalization's a huge piece. Cleansing of the data is a huge piece. Getting the model right is another piece. >> And simplifying the whole process. I think about, I got to ingest the data. I've now got to, you know, play with it, explore. I've got to process it. And I've got to serve it to some, you know, some business need or application. And typically, those are separate processes, separate tools, maybe different personas that are doing that. Am I correct that your announcement in the Fall addressed that workflow. How is it being, you know, deployed and adopted in the field? How is it, again back to transformation, are you seeing that people are actually transforming their analytics processes and ultimately creating outcomes that they expect? >> Huge. So good point. We announced data science experience in the Fall. And the customers that who are going to speak with us today on stage, are the customers who have been using that. So, for example, if you take AFCU, America First Credit Union, they worked with us. In two weeks, you know, talk about transformation, we were able to absorb the knowledge of their underwriters. You know, what (mumbles) is in. Build that, get that features. And was able to build a model in two weeks. And the model is predicting 90%, with 90% accuracy. That's what early tests are showing. >> [Dave] And you say that was in a couple of weeks. You were, you developed that model. >> Yeah, yeah, right. So when we talk about transformation, right? We couldn't have done that a few years ago. We have transformed where the different personas can collaborate with each other, and that's a collaboration piece I talked about. Real time. Be able to build a model, and put it in the test to see what kind of benefits they're getting. >> And you've obviously got edge cases where people get really sophisticated, but, you know, we were sort of talking off camera, and you know like the 80/20 rule, or maybe it's the 90/10. You say most use cases can be, you know, solved with regression and classification. Can you talk about that a little more? >> So, so when we talk about machine learning, right? To me, I would say 90% of it is regression or classification. I mean there are edge case of our clustering and all those things. But linear regression or a classification can solve most of the, most of our customers problems, right? So whether it's fraud detection. Or whether it's underwriting the loan. Or whether you're trying to determine the sentiment analysis. I mean, you can kind of classify or do regression on it. So I would say that 90% of the cases can be covered, but like I said, most of the work is not about picking the right algorithm, but it's also about cleansing the data. Picking the algorithm, then comes building the model. Then comes deployment or operationalizing the model. So there's a step process that's involved, and each step involves some amount of work. So if I could make one more point on the technology and the transformation we have done. So even with picking the right algorithm, we automated, so you as a data scientist don't need to, you know, come in and figure out if I have 50 classifiers and each classifier has four parameters. That's 200 different combinations. Even if you take one hour on each combination, that's 200 hours or nine days that takes you to pick the right combination. What we have done is like in IBM Machine Learning we have something called cognitive assistance for data science, which will help you pick the right combination in minutes instead of days. >> So I can see how regression scales, and in the example you gave of classification, I can see how that scales. If you've got a, you know, fixed classification or maybe 200 parameters, or whatever it is, that scales, what happens, how are people dealing with, sort of automating that classification as things change, as they, some kind of new disease or pattern pops up. How do they address that at scale? >> Good point. So as the data changes, the model needs to change, right? Because everything that model knows is based on the training data. Now, if the data has changed, the symptoms of cancer or any disease has changed, obviously, you have to retrain that model. And that's where I talk about the, where the feedback loop comes in, where we will automatically retrain the model based on the new data that's coming in. So you, as an end user, for example, don't need to worry about it because we will take care of that piece also. We will automate that, also. >> Okay, good. And you've got a session this afternoon with you said two clients, right? AFCU and Kaden dot TV, and you're on, let's see, at 2:55. >> Right. >> So you folks watching the live stream, check that out. I'll give you the last word, you know, what shall we expect to hear there. Show a little leg on your discussion this afternoon. >> Right. So, obviously, I'm going to talk about the different shading factors, what we are delivering IBM Machine Learning, right? And I covered some of it. There's going to be much more. We are going to focus on how we are making freedom or flexibility available. How are we going to do productivity, right? Gains for our data scientists and developers. We are going to talk about trust, you know, the trust of data that we are bringing in. Then I'm going to bring the customers in and talk about their experience, right? We are delivering a product, but we already have customers using it, so I want them to come on stage and share the experiences of, you know, it's one thing you hear about that from us, but it's another thing that customers come and talk about it. So, and the last but not least is we are going to announce our first release of IBM Machine Learning on Z because if you look at 90% of the transactional data, today, it runs through Z, so they don't have to off-load the data to do analytics on it. We will make machine learning available, so you can do training and scoring right there on Z for your real time analytics, so. >> Right. Extending that theme that we talked about earlier, Stu, bringing analytics and transactions together, which is a big theme of the Z 13 announcement two years ago. Now you're seeing, you know, machine learning coming on Z. The live stream starts at 2 o'clock. Silicon Angle dot com had an article up on the site this morning from Maria Doucher on the IBM announcement, so check that out. Dinesh, thanks very much for coming back on theCube. Really appreciate it, and good luck today. >> Thank you. >> All right. Keep it right there, buddy. We'll be back with our next guest. This is theCube. We're live from the Waldorf Astoria for the IBM Machine Learning Event announcement. Right back.