>>Yeah, >>from the Cube Studios in Palo Alto and Boston. It's the Cube covering IBM. Think brought to you by IBM. >>Everybody, this is Dave Vellante of the Cube. Welcome back. The continuous coverage that we're running here of the IBM Think Digital 2020 Experience. I'm with Radica Gunnar, who is a longtime Cube alum. She's the vice president for Data and AI. Expert labs and learning Radica. Always a pleasure. I wish we were seeing each other face to face in San Francisco. But, you know, we have to make the best. >>Always a pleasure to be with you, Dave. >>So, listen, um, we last saw each other in Miami Attain IBM data event. You hear a lot of firsts in the industry. You hear about Cloud? First, you hear about data. First hear about AI first. I'm really interested in how you see AI first coming customers. They want to operationalize ai. They want to be data first. They see cloud, you know, is basic infrastructure to get there, but ultimately they want insights out of data. And that's where AI comes in. What's your point of view on this? >>I think any client that's really trying to establish how to be able to develop a AI factory in their organization so that they're embedding AI across the most pervasive problems that they have in their order. They need to be able to start first with the data. That's why we have the AI ladder, where we really think the foundation is about how clients organized there to collect their data, organize their data, analyze it, infuse it in the most important applications and, of course, use that whole capability to be able to modernize what they're doing. So we all know to be able to have good ai, you need a good foundational information, architecture and the US A lot of the first steps we have with our clients is really starting with data doing an analysis of where are you with the data maturity? Once you have that, it becomes easier to start applying AI and then to scale AI across the business. >>So unpack that a little bit and talk about some of the critical factors and the ingredients that are really necessary to be successful. What are you seeing with customers? >>Well, to be successful with, a lot of these AI projects have mentioned. It starts with the data, and when we come to those kind of characteristics, you would often think that the most important thing is the technology. It's not that is a myth. It's not the reality. What we found is some of the most important things start with really understanding and having a sponsor who understands the importance of the AI capabilities that you're trying to be able to drive through business. So do you have the right hunger and curiosity of across your organization from top to bottom to really embark on a lot of these AI project? So that's cultural element. I would say that you have to be able to have that in beds within it, like the skills capabilities that you need to be able to have, not just by having the right data scientists or the right data engineers, but by having every person who is going to be able to touch these new applications and to use these new applications, understand how AI is going to impact them, and then it's really about the process. You know, I always talk about AI is not a thing. It's an ingredient that makes everything else better, and that means that you have to be able to change your processes. Those same applications that had Dev ops process is to be able to put it in production. Need to really consider what it means to have something that's ever changing, like AI as part of that which is also really critical. So I think about it as it is a foundation in the data, the cultural changes that you need to have from top to bottom of the organization, which includes the skills and then the process components that need to be able to change. >>Do you really talking about like Dev ops for AI data ops, I think is a term that's gonna gaining popularity of you guys have applied some of that in internally. Is that right? >>Yeah, it's about the operations of the AI life cycle in, and how you can automate as much of that is possible by AI. They're as much as possible, and that's where a lot of our investments in the Data and AI space are going into. How do you use AI for AI to be able to automate that whole AI life site that you need to be able to have in it? Absolutely >>So I've been talking a lot of C. XO CEO CEOs. We've held some C so and CEO roundtables with our data partner ET are. And one of the things that's that's clear is they're accelerating certain things as a result of code 19. There's certainly much more receptive to cloud. Of course, the first thing you heard from them was a pivot to work from home infrastructure. Many folks weren't ready, so okay, but the other thing that they've said is even in some hard hit industries, we've essentially shut down all spending, with the exception of very, very critical things, including, interestingly, our digital transformation. And so they're still on that journey. They realized the strategic imperative. Uh, and they don't want to lose out. In fact, they want to come out of this stronger AI is a critical part of that. So I'm wondering what you've seen specifically with respect to the pandemic and customers, how they're approaching ai, whether or not you see it accelerating or sort of on the same track. What are you seeing out there with clients? >>You know, this is where, um in pandemics In areas where, you know, we face a lot of uncertainty. I am so proud to be an IBM. Er, um, we actually put out offer when the pandemic started in a March timeframe. Teoh Many of our organizations and communities out there to be able to use our AI technologies to be able to help citizens really understand how Kobe 19 was gonna affect them. What are the symptoms? Where can I get tested? Will there be school tomorrow? We've helped hundreds of organizations, and not only in the public sector in the healthcare sector, across every sector be able to use AI capabilities. Like what we have with Watson assistant to be able to understand how code in 19 is impacting their constituents. As I mentioned, we have hundreds of them. So one example was Children's health care of Atlanta, where they wanted to be able to create an assistant to be able to help parents really understand what symptoms are and how to handle diagnosis is so. We have been leveraging a lot of AI technologies, especially right now, to be able to help, um, not just citizens and other organizations in the public and healthcare sector, but even in the consumer sector, really understand how they can use AI to be able to engage with their constituents a lot more closely. That's one of the areas where we have done quite a bit of work, and we're seeing AI actually being used at a much more rapid rate than ever >>before. Well, I'm excited about this because, you know, we were talking about the recovery, What there's a recovery look like is it v shaped? Nobody really expects that anymore. But maybe a U shaped. But the big concern people have, you know, this w shape recovery. And I'm hopeful that machine intelligence and data can be used to just help us really understand the risks. Uh, and then also getting out good quality information. I think it's critical. Different parts of the country in the world are gonna open at different rates. We're gonna learn from those experiences, and we need to do this in near real time. I mean, things change. Certainly there for a while they were changing daily. They kind of still are. You know, maybe we're on a slower. Maybe it's three or four times a week now, but that pace of change is critical and, you know, machine machines and the only way to keep up with that wonder if you could comment. >>Well, machines are the only way to keep, and not only that, but you want to be able to have the most up to date relevant information that's able to be communicated to the masses and ways that they can actually consume that data. And that's one of the things that AI and one of the assistant technologies that we have right now are able to do. You can continually update and train them such that they can continually engage with that end consumer and that end user and be able to give them the answers they want. And you're absolutely right, Dave. In this world, the answers change every single day and that kind of workload, um, and and the man you can't leave that alone to human laborers. Even human human labors need an assistant to be able to help them answer, because it's hard for them to keep up with what the latest information is. So using AI to be able to do that, it's absolutely critical, >>and I want to stress that I said machines you can't do without machines. And I believe that, but machines or a tool for humans to ultimately make the decisions in a crisis like this because, you see, I mean, I know we have a global audience, but here in the United States, you got you have 50 different governors making decisions about when and how certainly the federal government putting down guidelines. But the governor of Georgia is going to come back differently than the governor of New York, Different from the governor of California. They're gonna make different decisions, and they need data. And AI and Machine intelligence will inform that ultimately their public policy is going to be dictated by a combination of things which obviously includes, you know, machine intelligence. >>Absolutely. I think we're seeing that, by the way, I think many of those governors have made different decisions at different points, and therefore their constituents need to really have a place to be able to understand that as well. >>You know, you're right. I mean, the citizens ultimately have to make the decision while the governor said sick, safe to go out. You know, I'm gonna do some of my own research and you know, just like if you're if you're investing in the stock market, you got to do your own research. It's your health and you have to decide. And to the extent that firms like IBM can provide that data, I think it's critical. Where does the cloud fit in all this? I mentioned the cloud before. I mean, it seems to be critical infrastructure to get information that will talk about >>all of the capabilities that we have. They run on the IBM cloud, and I think this is where you know, when you have data that needs to be secured and needs to be trusted. And you need these AI capabilities. A lot of the solutions that I talked about, the hundreds of implementations that we have done over the past just six weeks. If you kind of take a look at 6 to 8 weeks, all of that on the IBM Public cloud, and so cloud is the thing that facilitates that it facilitates it in a way where it is secure. It is trusted, and it has the AI capabilities that augmented >>critical. There's learning in your title. Where do people go toe? Learn more How can you help them learn about AI And I think it started or keep going? >>Well, you know, we think about a lot of these technologies as it isn't just about the technology. It is about the expertise and the methodologies that we bring to bear. You know, when you talk about data and AI, you want to be able to blend the technology with expertise. Which is why are my title is expert labs that come directly from the labs and we take our learnings through thousands of different clients that we have interacted with, working with the technologies in the lab, understanding those outcomes and use cases and helping our clients be successful with their data and AI projects. So we that's what we do That's our mission. Love doing that every day. >>Well, I think this is important, because I mean, ah company, an organization the size of IBM, a lot of different parts of that organization. So I would I would advise our audience the challenge IBM and say, Okay, you've got that expertise. How are you applying that expertise internally? I mean, I've talked into public Sorry about how you know the data. Science is being applied within IBM. How that's then being brought out to the customers. So you've actually you've got a Petri dish inside this massive organization and it sounds like, you know, through the, you know, the expert labs. And so the Learning Center's you're sort of more than willing to and aggressively actually sharing that with clients. >>Yeah, I think it's important for us to not only eat our own dog food, so you're right. Interpol, The CDO Office Depot office we absolutely use our own technology is to be able to drive the insights we need for our large organization and through the learnings that we have, not only from ourselves but from other clients. We should help clients, our clients and our communities and organizations progress their use of their data and their AI. We really firmly believe this is the only way. Not only these organizations will progress that society as a whole breast, that we feel like it's part of our mission, part of our duty to make sure that it isn't just a discussion on the technology. It is about helping our clients and the community get to the outcomes that they need to using ai. >>Well, guy, I'm glad you invoke the dog food ing because, you know, we use that terminology a lot. A lot of people marketing people stepped back and said, No, no, it's sipping our champagne. Well, to get the champagne takes a lot of work, and the grapes at the early stages don't taste that pain I have to go through. And so that's why I think it's a sort of an honest metaphor, but critical your you've been a friend of the Cube, but we've been on this data journey together for many, many years. Really appreciate you coming on back on the Cube and sharing with the think audience. Great to see you stay safe. And hopefully we'll see you face to face soon. >>All right. Thank you. >>Alright. Take care, my friend. And thank you for watching everybody. This is Dave Volante for the Cube. You're watching IBM think 2020. The digital version of think we'll be right back after this short break. >>Yeah, yeah, yeah.

>>From the cube studios in Palo Alto in Boston. It's the cube covering the IBM thing brought to you by IBM. Everybody we're back. This is Dave Vellante the cube, and this is our wall-to-wall coverage, IBM's digital thing experienced for 2020. We're really excited to have Jerry Cuomo on. He's the, uh, vice president of blockchain technologies and an IBM fellow and longtime cube alum. Jerry, good to see you again. Thanks for coming on and wish we were face to face, but yeah, this'll do. Good to see you too. Yes, thanks for having me. So we've been talking a lot of and talking to, I've been running a CEO series a, of course, a lot of the interviews around, uh, IBM think are focused on, on COBIT 19. But I wonder if you could start off by just talking a little bit about, you know, blockchain, why blockchain, why now, especially in the context of this pandemic. >>David's, it's as if we've been working out in the gym, but not knowing why we needed to be fixed. And I know now why we need to be fit. You know, blockchain is coming just in time. Mmm. You know, with the trust factor and the preserving privacy factor. Okay. The way we move forward the world is now becoming more digital than ever people working from home. Um, the reliance and online services is, that's critical. our ability to work as a community accompanies companies. The shared data is critical. you know, blockchain brings a magical ingredient and that's the ingredient of trust, you know, in sharing data. Okay. When, if that data and the sources that are providing that data arc okay. From verified and trusted, we're more likely to use that data and you the, any friction that's caused for fear of trepidation that the data is going to be misused. >>Mmm. It goes start to go away. And when that happens, you speed up an exchange and we need speed. Time is of the essence. So blockchain brings a platform for trusted data exchange while preserving privacy. And that provides a foundation. I can do some amazing things in this time of crisis, right? Yeah. And it's, it's not only trust, it's also expediency and you know, cutting out a lot of the red tape. And I want to talk about some of the applications. You're heavily involved in that in the distributed ledger, a project, you know, one of the early leads on that. Um, talk about some of the ways in which you're flying that distributed a ledger. And let's go into some of the examples. So we're, we're really fortunate to be an early adopter blockchain and, and provider of blockchain technology and kind of the fruit of that. >>Um, as I said, it couldn't happen any sooner where we have, Mmm, I would say over a thousand, alright. Users using IBM blockchain, which is powered by the opensource Hyperledger fabric, I'd say over a hundred of those users, um, have reached a level of production networks. you know, it's been great to see some of the proprietors of those networks now repurpose the networks towards hastening the relief of, uh, and one, a couple of examples that stand out, Dave. Mmm. You've seen what's happening to our supply chain. And then I think we got some rebound happening as we speak, but companies all of a sudden woke up one morning and their supply chains were, I'm exhausted. So suppliers, we're out of key goods and the buyers needed very rapidly to expand. They're, the supplier is in their, in their supply chain. there are laws and regulations about what it takes to onboard a new supplier. >>You want to make sure you're not onboarding bad actors. So in IBM for example, we have over 20,000 suppliers to our business and it takes 30 to 40 days who, uh, validate and verify one of those suppliers. We don't have 30 to 45 days, you know, think about you're a healthcare company or a food company. So working with a partner called Jane yard, uh, co-created a network called trust yourself buyer. And we've been able to repurpose, trust your supplier now or companies that are looking, you know, around Kobe 19 to rapidly okay, expand, you know, their, their supply chain. So if you imagine that taking us 45 days or 40 days to onboard a new supplier, okay. Pick, pick a company in our supply chain, Lenovo, that supplier may very well want to go to Lenovo to and provide services to them. Well guess what, it's going to take 40 days, the onboard to Lenovo. >>But if they're part of the trust or supplier network and they've already onboarded to IBM, they're well on their way. You're being visible to all of these other buyers that are part of the IBM network, like Lenovo and many others. And instead of taking 40 days, maybe it only takes five days. All right. So radically, radically, you know, improving the time it takes them. You know, with companies like Ford making ventilators and masks, it will kind of be able to onboard Ford into, you know, health care, uh, companies. But you know, we want to be able to do it with speed. So trust your supplier is a great use of blockchain. Two, expand a buyer and suppliers. Mmm. Exposure. Mmm. And they expand their network to quickly onboard. And you know, with the trust that you get an exchanging data from blockchain with the Mmm provenance, that Hey, this company information was truly vetted by one of the trusted members of the network. >>There's no fee or trepidation that somehow these records were tampered with or, or misused. So that's one example they have of using blockchain. That's a huge, uh, example that you gave because you're right, there are thousands and thousands of companies that are pivoting to making, like you said, ventilators and masks and yeah, they're moving so fast and there's gotta be a trust involved. On the one hand, they're moving fast to try to save their businesses or you know, in the case of Ford, you help save the, the country or the world. On the other hand, you know, there's risks there. So that, that helps. I want to understand me. Pasa basically is, if I understand it, you can privately share, uh, information on folks that are asymptomatic but might be carriers of covert 19. Am I getting that right on? Okay. So me Pasa starts as a project, uh, from a company called has Sarah and their CEO Jonathan Levy. >>And among other things, Jonathan Levy is an amazing, uh, software developer and he's helped us and the community at large, bill, the Hyperledger fabric, uh, blockchain technology, that's part of IBM. Mmm. The power is IBM blockchain. So Jonathan, I have this idea because w what was happening is there were many, many data sources, you know, from the very popular and well known, uh, Johns Hopkins source. And we have information coming from the weather company. There are other governments, um, putting out data. Jonathan had this, this idea of a verified Mmm. Data hub, right? So how do we kind of bring that information together in a hub where a developer can now to get access to not just one feed, but many feeds knowing that both the data is an a normalized format. So that's easy to consume. And like if you're consuming 10 different data sources, you don't have to think about 10 different ways to interact it. >>No kind of normalizing it through a fewer, like maybe one, but also that we really authentically know that this is the world health organization. This is indeed John Hopkins. So we have that trust. So, okay. Yeah. With me, Pasa being I'm a data hub four, uh, information verified information related to the Kronos virus, really laying a foundation now for a new class of applications that can mash up information to create new insights, perhaps applying Mmm. Artificial intelligence machine learning to really look not just at any one of those, uh, data sources, but now look across data sources, um, and start to make some informed decisions. No, I have to say operate with the lights on, uh, and with certainty that the information is correct. So me Pasa is that foundation and we have a call for code happening that IBM is hosting for developers to come out and okay. Bring their best ideas forward and X for exposing me Pasa as a service to the, in this hackathon so that developers can bring some of their best ideas and kind of help those best ideas come alive with me. Me has a resource. >>That's great. So we've got two, we got the supply chain, we just need to share the Pasa. There's the other one then I think we can all relate to is the secure key authentication, >>which I love. >>Uh, maybe you can explain that and talk about the role that blockchain >>we're launching fits, right. So you know, there is people working from home and digital identity verification. It is key. You know, think about it. You're working remotely, you're using tools like zoom. Um, there's a huge spike in calls and online requests from tele-health or government benefits programs. Yeah. So this is all happening. Everything behind the scenes is, yeah. Around that is, is this user who they say they are, is this doctor who they say they are, et cetera. And there are scams and frauds out there. So working with speed, it means working with certainty. and with the verified me networks set out to do a couple of years ago and the beautiful part is, you know, it's ready to go now for this, for this particular usage it's been using. Mmm. Basically think about it as my identity is my identity and I get to lease out information too different institutions to use it for my benefit, not necessarily just for their benefit. >>So it's almost like digital rights management. Like if you put out a digital piece of art or music, you can control the rights. Who gets to use it? What's the terms and conditions, um, on, on your terms? So verified me, um, allows through a mobile app users to invite institutions who represent them, verify them. No. And so I'll allow my department of motor vehicle and my employer, Mmm. Two to verify me, right? Because I want to go back to work sooner. I want to make sure my work environment, um, I'm making this up. I want to make sure my work environment, the people have been tested and vaccinated, but I don't want to necessarily, you know, kind of abuse people's privacy. Right? So I'll opt in, I'll share that information. I'll get my, my doctor and my, uh, department of motor vehicle to say, yes, this is Gary. >>He's from this address. Yes, he has been vaccinated and now I can kind of onboard to services as much quicker whether that service is going through TSA. Do you get on an airplane badging back into my office or you know, signing on to a, you know, telemedicine, a service or government, a benefits program, et cetera. So verify me is using the self, uh, at the station through a mobile application to help speed up the process of knowing that that is truly you and you truly want this service. Uh, and you are also calling the shots as to that. What happens with your information that, you know, it's not spread all over the interweb it's under your control at all time. Right. So I think it's the best of all worlds. The national Institute for standards and technology looked at, verified me. They're like, Oh my gosh, this is like the perfect storm of goodness for identity. >>They actually appointed, yeah, it has a term, it's called triple blind data exchange. It sounds like a magical act. A triple blind data exchange means the requester. Mmm. Doesn't know who the provider is and less know the requester. Um, allows the provider to know, Mmm, the provider doesn't know who the requester requested, doesn't know who the prior provider is that is double-blind. And then the network provider doesn't know either. Right. But somehow across disformed and that's the magic of blockchain. I'm allowing that to happen and with that we can move forward knowing we're sharing information where it matters without the risk of it leaking out to places we don't want to do. So great application of secure key and verified me. Yeah, I love that. Then the whole concept of being able to control your own data. You hear so much today about, you know, testing and in contact tracing using mobile technology to do that. >>But big privacy concerns. I've always felt like, you know, blockchain for so many applications in healthcare or just being able to, as you say, control your own data. I want to better understand the technology behind this. When I think about blockchain, Mmm. I obviously you don't think about it. Cryptography, you've mentioned developers a number of times. There's software engineering. Yeah. Distributed ledger. Um, I mean there's, there's game theory in the, in the, in the cryptocurrency world, we're not talking about that, but there's the confluence of these technologies coming to them. What's the technology underneath these, these applications? Talking about it there, there is an open source, an organization called Hyperledger. It's part of the Linux foundation. They're the gold standard and open source, openly governed, Mmm. Technology you know, early on in 2018 yep. 18, 26. I mean, we got involved, started contributing code and developers. >>Two Hyperledger fabric, which is the industry's first permissioned blockchain technology. Permission meaning members are accountable. So the network versus Bitcoin where members are anonymous and to pass industry Reggie regulations, you can't be anonymous. You have to be accountable. Um, that's not to say that you can't, okay. Work privately, you know, so you're accountable. But transactions in the network, Mmm. Only gets shared with those that have a need, need to know. So that the foundation is Hyperledger fabric. And IBM has a commercial offering called the IBM blockchain platform that embodies that. That kind of is a commercial distribution of Hyperledger fabric plus a set of advanced tools to make it really easy to work with. The open source. All the networks that I talked about are operating their network across the worldwide IBM public cloud. And so cloud technology lays a really big part of blockchain because blockchains are networks. >>Mmm. You know, our technology, IBM blockchain platform runs really well in the IBM wow. But it also allows you to run anywhere, right? Or like to say where it matters most. So you may have companies, I'm running blockchain nodes in the IBM cloud. You may have others running it on their own premises behind their firewall. You might have others running an Amazon and Microsoft Azure. Right. So we use, um, you may have heard of red hat open shift, the container technology so that we can run Mmm. Parts of a blockchain network, I guess they said where they matter most and you get strengthened a blockchain network based on the diversity of the operators. Because if it was all operated by one operator, there would be a chance maybe that there can be some collusion happening. But now if you could run it know across different geographies across the IBM cloud. >>So almost three networks all run on use this technology or run on the IBM cloud. And Dave, one more thing. If you look at these applications, they're just modern application, you know, their mobile front ends, their web portals and all of that kind of, okay. Okay. The blockchain part of these applications, usually it's only 20% of the overall endeavor that companies are going through. The other 80% it's business as usual. I'm building a modern cloud application. So what we're doing in IBM with, but you know, red hat with OpenShift with our cloud packs, which brings various enterprise software across different disciplines, blends and domains like integration, application, data, security. All of those things come together to fill the other 80% the above and beyond blockchain. So these three companies, okay. You know, 99 plus others are building applications as modern cloud applications that leverage this blockchain technology. So you don't have to be a cryptographer or you know, a distributed database expert. It's all, it's all embodied in this code. Mmm. Available on the IBM cloud, 29 cents a CPU hour. It was approximately the price. So it's quite affordable. And you know, that's what we've delivered. >>Well, the thing about that, that last point about the cloud is it law, it allows organizations, enterprises to experiment very cheaply, uh, and so they can get, uh, an MVP out or a proof of concept out very quickly, very cheaply, and then iterate, uh, extremely quickly. That to me is the real benefit, the cloud era and the pricing model. >>I just mentioned, David, as I said it when I started, you know, it's like we were working out in a gym, but we weren't quite sure. We knew why we were, we were so keen on getting fit. And what I see now is this, you know, blossoming of users who are looking at, you know, a new agreement. We thought we understood digital transformation. Mmm. But there's a whole new nice to be digitized right now. You know, we're probably not going to be jumping on planes and trains, uh, working as, as, as more intimately as we were face to face. So the need for new digital applications that link people together. Uh, w we're seeing so many use cases from, um, trade finance to food safety, to proxy voting for stock, know all of these applications that we're kind of moving along at a normal speed. I've been hyper accelerated, uh, because of the crisis we're in. So blockchain no. Couldn't come any sooner. >>Yeah. You know, I want to ask you, as a technologist, uh, you know, I've learned over the years, there's a lot of ways to skin a cat. Um, could you do the types of things that you're talking about without blockchain? Um, I'm, I'm sure there are ways, but, but why is blockchain sort of the right path, >>Dave? Mmm. You can, you can certainly do things with databases. Mmm. But if you want the trust, it's as simple as this. A database traditionally has a single administrator that sets the rules up for when a transaction comes in. Mmm. What it takes to commit that transaction. And if the rules are met, the transactions committed, um, the database administrator has access who commands like delete and update. So at some level you can never be a hundred percent sure that that data was the data that was intended in there. With a blockchain, there's multiple administrators to the ledger. So the ledger is distributed and shared across multiple administrators. When a transaction is submitted, it is first proposed for those administrators, a process of consent happens. And then, and only then when the majority of the group agrees that it's a valid transaction, is it committed? And when it's committed, it's committed in a way that's cryptographically linked two other transactions in the ledger, I'm making it. >>Mmm tamper-proof right. Or very difficult to tamper with. And unlike databases, blockchains are append only so they don't have update and delete. Okay. All right. So if you really want that center of trusted data that is a tested, you know, that has checks and balances across different organizations, um, blockchain is the key to do it, you know? So could you do it in data with a database? Yes. But you have to trust that central organization. And for many applications, that's just fine. All right. But if we want to move quickly, we really want to share systems of record. Mmm. I hear you. Sharing a system of record, you have regulatory obligations, you can say, Oh, sorry, the record was wrong, but it was put in there by, by this other company. Well, they'll say, well, >>okay, >>nice for the other company, but sorry, you're the one in trouble. So with a blockchain, we have to bring assurances that we can't get into that kind of situation, right? So that shared Mmm. Distributed database that is kind of provides this tamper resistant audit log becomes the Colonel cross. And then with the privacy preservation that you get from encryption and privacy techniques, um, like we have like these things, both channels, um, you can transact, um Hm. And be accountable, but also, Mmm. Only share of transactions with those that have a need to know, right? So you get that level of privacy in there. And that combination of trust and privacy is the secret sauce that makes blockchain unique and quite timely for this. So yeah, check it out. I mean, on the IBM cloud, it's effortless. So to get up and running, you know, building a cloud native application with blockchain and you know, if you're used to doing things, um, on other clouds or back at the home base, we have the IBM blockchain software, which you can deploy. Yeah. Open shift anywhere. So we have what you need in a time of need. >>And as a technologist, again, you're being really, I think, honest and careful about the word tamper. You call it tamper resistant. And if I understand it right, that, I mean, obviously you can fish for somebody's credentials. Yeah. That's, you know, that's one thing. But if I understand that, that more than 50% of the peers in the community, it must agree to tamper in order for the system. You tampered with it. And, and that is the beauty of, of blockchain and the brilliance. Okay. >>Okay. Yeah. And, and, and for, um, performance reasons we've created optimizations. Like you can set a consensus policy up because maybe one transaction it's okay just to have a couple people agree and say, Oh, well, you know, out of the a hundred nodes, Mmm. Three agree, it's good enough. Okay. Other, other policies may be more stringent depending on the nature of the data and the transaction, right? So you can tone, you can kind of tune that in based on the class of transaction. And so it's kind of good and that's how we can get performance levels in the, you know, thousand plus. In fact, IBM and RBC, um, recently did, um, a series of performance analysis because RBC said, Hey, can I use this for some of my bank to bank exchanges and we need to support over a thousand transactions per second. They were able, in their use case, there's support over 3000. Transact for a second. Okay. Mmm. You know, that we were very encouraged by that. I'm glad you clarified that because, so essentially you're saying you can risk adjust the policies if you will. >>That's great to know. Mmm. I could go on forever on this topic. Well, we're unfortunately, Jerry, we're well over our time, but I want to thank you for coming back, planning this important topic. Thrilled. IBM has taken a leadership position here, and I think, you know, to your point, this pandemic is just going to, can accelerate a lot of things and blockchain is, but in my view anyway, one of them. Thank you, Dave. Oh, great questions and I really appreciate it. So everyone out there, um, stay safe. Stay healthy. All right. Thank you Jerry, and thank you for watching everybody. This is Dave Volante for the cube. Our coverage of the IBM think digital 2020 event. We'll be right back. Perfect. The short break.

>>Yeah, >>from the Cube Studios in Palo Alto and Boston. It's the Cube covering IBM. Think brought to you by IBM. >>Welcome back, everybody. This is Dave Vellante of the Cube, and you're watching our continuous coverage of the IBM think Digital 2020 experience. And we're really pleased to have Rob High here. He's not only an IBM fellow bodies. He runs the vice president CTO of the IBM Edge Computing Initiative. Rob, thanks so much for coming on the Cube. Good to see you. Which we're face to face, but yeah, that time to be safe and healthy, I guess. And did so edge obviously hot topic. Everybody has this sort of point of view would be interested in how IBM looks at edge. You define it and what your thoughts are on. It's evolution. >>Yeah, well, you know, there's ah really kind of two fairly distinct ways of thinking about the edge of the telcos. Our, ah, you know, they're creating edge capabilities in their own network facilities. We call that the network edge on the other side of the edge they that I think matters a lot to our enterprise businesses is there's remote on premise locations where they actually perform the work that they do, where the majority of people are, where the data that actually gets created is first formed and where the actions that they need to operate on are being taken. That is a lot of interest, because if we can move work workloads, Iot workloads to where that data is being created, where those actions are being taken Uh, not only can we dramatically reduce the late and see to those decisions, uh, but we can also ensure continuous operations and the failed in the presence of perhaps network failures. We can manage the growth of increasing demand for network bandwidth as Maura born data gets created and we can optimize the efficiency of both the business operations as well as the I t operations before that. So for us edge computing at the end of the day is about movie work where the data and the actions are being taken >>well, so this work from home, you know, gives a result of this pandemic is kind of creating a new stresses on networks and people are putting, you know, pouring money actually into beefing up that infrastructure is sort of an extension of what we used to think about edge. But I wonder if you could talk about some of the industries and the use cases that you guys we are seeing and notwithstanding, though assay that >>work from home pivot. Yeah, absolutely. So I mean, look, we have seen ah, the need for placing workloads close to where it is being created and where actions have been picking in virtually every industry, the ones that are probably easier for us to think about and more common in terms of our mindset. Our is manufacturing. If you think about all the things that go on in a factory floor that need to be able to perform analytic in, uh, in the equipment and the processes that are performing in the affection for, If you think, for example, production quality. Uh, you know, if you've got a machine that's putting out parts and maybe it's welding seams on metal boxes, uh, you know, you want to be able to look at the quality of that seem at the moment that is being performed, so that if there are any problems, you can remediate that immediately rather than having that box move on down the line and find that you know the quality issues they were created earlier on now have exacerbated in other ways. Um, you know, so quality, productive quality. Ah, inspection production optimization in our world of Covic Cover 19 and worker safety and getting workers back to work and ensuring that you know people wearing the masks and are exercising social distancing. This is on the factory floor. Worker Insight is another major use case that we're seeing surface of lake with a lot of interest in using whether that's infrared cameras or Bluetooth beacons or infrared cameras. Any variety of devices that could be employed in the work area to help ensure that factories are operating efficiently, that workers are safe. Ah, and whether that's in a factor situation or even in an office situation or e a r in a warehouse or distribution center. And all these scenarios the the utility, the edge computing to bring to those use cases is tremendous. >>And a lot of these devices are unattended or infrequently attended. I always use the windmill example. Um, you know, you don't want to have to do a truck roll to figure out you know what the dynamics are going on, that at the windmill s, so I can instrument that. But what about the management of those devices you know from an autonomous standpoint? And and are you? What are you doing? Or are you doing anything in the autonomous managed space? >>Yeah. In fact, that's really kind of key here, because when you think about the scale, the diversity and the dynamic dynamism of equipment in these environments And as you point out, Dave, you know the lack of I t resource lack of skills on the factory floor, or even in the retail store or hotel or distribution center or any of these environments. The situation is very similar. You can't simply manage getting the right workloads to the right place at the right time. In sort of the traditional approach is, you have to really think about another autonomous approach to management and, you know, let the system the side for you. What software needs to be placed out there? Which software to put their If it's an analytic algorithm, what models to be associated with that software and getting to the right place at the right place at the right Time is a key Part of what we do in this thing that we call IBM Edge application manager is that product that we're really kind of bringing to market right now in the context of edge computing that facilitates this idea of autonomous management. >>You know, I wonder if you could comment Robb on just sort of the approach that you're taking with regard to providing products and services. I mean, we've seen a lot of, uh, situations where people are just essentially packing, packaging traditional, you know, compute and storage devices and sort of throwing it over the fence at the edge. Uh, and saying, Hey, here's our edge computing solution and another saying there's not a place for that. Maybe that will help flatten the network and, you know, provide Ah, gateway for storing on maybe processing information. But it seems to us that that that a bottoms up approach is going to be more appropriate. In other words, you've got engineers, you know who really understand operations, technology, people, maybe a new breed of developers emerging. How do you see the evolution you know of products and services and architectures at >>the edge? Yeah, so First of all, let me say IBM is taking a really pretty broad approach to edge computing we have. What I just described is IBM Edge Application Manager, which is the if you will the platform or the infrastructure on which we can manage the appointment of workloads out to the edge. But then add to that we do have a whole variety of edge and Nevil enabled applications that are being created are global service of practices and our AI applications business all are creating, um, variations of their product specific to address and exploit edge computing and to bring that advantage to the business. And of course, then we also have global services Consulting, which is a set of skilled resource, is who know we understand the transformations that business need to go through when they went, take advantage of edge computing and how to think about that in the context of both their journey to the cloud as well as now in this case, the edge. But also then how to go about implementing and delivering that, uh and then firmly further managing that now you know, coupled out then with at the end of the day you're also going to need the equipment, the devices, whether that is an intelligent automobile or other vehicle, whether that is an appellate, a robot or a camera, Um, or if those things are not intelligent. But you want to bring intelligence to them that how you augment that with servers and other forms of cluster computing that resides resident with the device. All of those are going to require participation from a very broad ecosystem. So we've been working with partners of whether that is vendors who create hardware and enabling that hardware in certifying that hardware to work with our management infrastructure or whether those are people who bring higher order services to the table that provide support for, let's, say, data cashing and facilitating the creation of applications, or whether those are device manufacturers that are embedding compute in their device equipment. All of that is part of our partnership ecosystem, Um, and then finally, you know, I need to emphasize that, you know, the world that we operate in is so vast and so large. There are so many edge devices in the marketplace, and that's growing so rapidly, and so many participants in that likewise There are a lot of other contributors to this ecosystem that we call edge computing. And so for all of those reasons, we have grounded IBM education manager on open source. We created an open source project called Open Rise, and we've been developing that, actually now, for about 4.5 years just recently, the Linux Foundation has adopted Stage one adoption of Open arising as part of its Lennox Foundation edge LF edge, uh, Reg X Foundry project. And so we think this is key to building out, Um, a ecosystem of partners who want to both contribute as well consumed value and create ecosystems around this common idea of how we manage the edge. >>Yeah, I'm glad you brought up the ecosystem, and it's too big for any one company toe to go it alone. But I want to tap your brain on just sort of architectures. And there's so many diverse use cases, you know, we don't necessarily see one uber architecture emerging, but there are some characteristics that we think are important at the edge you mentioned sort of real time or near real time. In many cases, it has to be real time you think about autonomous vehicles? Um, yeah. A lot of the data today is analog, and maybe it doesn't have to be digitized, but much of it will be, um, it's not all gonna be sent back to the cloud. It may not all have to be persisted. So we've envisioned this sort of purpose built, you know, architecture for certain use cases that can support real time. That maybe have, you know, arm based processors. Ah, or other alternative processors there that can do real time analytics at the edge and maybe sending portions of the data back. How do you see the architectures evolving from a technologist? >>Well, so certainly one of the things that we see at the edge is a tremendous premium being placed on things like energy consumption. So architectures they're able to operate efficiently with less power is ah is certainly an advantage to any of those architectures that are being brought aboard. Um, clearly, you know x 86 is a dominant architecture in any information technology endeavor. More specifically at the edge. We're seeing the emergence of lot of arm based architecture chips out there. In fact, I would guess that the majority of the edge devices today are not being created with, um, arm architectures, but it's the you know, but some of this is about the underlying architecture of the compute. But also then the augmentation of that compute the the compute Thea the CP use with other types of processing units. Whether those GPS, of course, we're seeing, you know, a number of deep use being created that are designed to be low power consuming, um, and have a tremendous amount of utility at the edge. There are alternate processing units, architectures that have been designed specifically for AI model based analytics. Uh, things like TP use and infuse and and, uh, and set around, which are very purpose built for certain kinds of intellect. And we think that those are starting to surface and become increasingly important. And then on the flip side of this is both the memory storage in network architectures which are sort of exotically different. But at least in terms of capacity, um have quite variability. Specifically, five G, though, is emerging and five g. While it's not necessarily the same computing, there is a lot of symbolism between edge and five G and the kinds of use cases that five G envisions are very similar to those that we've been talking about in the edge world as well. >>Rob, I want to ask you about sort of this notion of program ability at the edge. I mean, we've seen the success of infrastructure as code. Um, how do you see program ability occurring at the edge in terms of fostering innovation and maybe new developer bottles or maybe existing developer models at the edge? Yeah, >>we found a lot of utility in sort of leveraging what we now think of as cloud computing or cloud computing models. Uh, you know, the idea of continue ization extends itself very easily into the edge. Whether that is running a container in a docker runtime, let's say on an edge device which is, you know, resource constrained and purpose built and needs to focus on sort of a very small footprint or even edge clusters edge servers where we might be running a cluster of containers using our kubernetes platform called open shift. Um, you know the course of practices of continuous integration, continuous delivery. What we write a Otherwise think of his Dev ops. Ah, and, of course, the benefits they continue. Realization brings to the idea of component architectures. Three. Idea of loose coupling. The separation of concerns, the ability to mix and match different service implementations to be opposed. Your application are all ideas that were matured in the cloud world but have a lot of utility in the edge world. Now we actually call it edge native programming. But you can think of that as being mostly cloud native programming, with a further extension that there are certain things you have to be aware of what you're building for the edge. You have to recognize that resource is air limited. Unlike the cloud where we have this notion of infinite resource, you don't have that at the edge. Find and constrained resources. Be worried about, you know, Layton sees and the fact that there is a network that separates the different services and that network can be and reliable. It can introduce his own forms of Layton sees it, maybe bandwidth constrained and those air issues that you now have to factor into your thinking as you build out the logic of your application components. But I think by building on the cloud native programming about me paradigm. You know, we get to exercise sort of all of the skills that have been developing and maturing in the cloud world. Now, for the edge >>that makes sense. My last question is around security. I mean, I've often sort of tongue in cheek said, you know, building a moat around the castle doesn't work anymore. The queen i e. The data has left the castle. She's everywhere. So what about the security model? I mean, I feel like the edge is moving so fast you feel confident or what gives you confidence >>that we can secure the edge. You know, the edges does introduce some very interesting and challenging concerns with respect to security because, frankly, the compute is out there in the wild. You know, you've got computers in the store you've got, you know, people walking around the kiosks you have in the manufacturing site, you know, workers that are, you know, in the midst of all of this compute capability and so the attack surface is substantially bigger. And that's been a big focus for us, is how to the only way validate in 30 of the software that was But it also takes advantage of one of the key characters with edge computing to bring to the table, which is, if you think about it. You know, when you've got personal and private information being entered into quote system, the more often you move that personal private data around, and certainly the more that you move it to a central location and aggregate that with other data, the more of a target becomes more vulnerable, exposed that data becomes and by using edge computing, which moves the workloads out to the edge where that did has been created in some sense, you can process on it there and then move it back. They need central location, you don't have to aggregate it. And that actually in itself is a counterbalance of all of the other issues that we also describe about security by essentially not moving the personal privacy and in protecting by keeping it exactly where it began. >>You know, Rob, this is an exciting topic. Is a huge opportunity for IBM and Ginny in and talk about the trillion dollar opportunity and hybrid cloud and the Edge is a multi $1,000,000,000 opportunity for IBM and, uh So you just got to go get her done. But I really appreciate you coming on the Cube and sharing your insights. That awesome topic in the best interest of the David. Yeah. Thank you. Thank you for the thank you. Stay safe and thank you for watching everybody. This is Dave Volante for the Cube. This is our coverage of IBM. Think 2020 the digital. Think >>we'll be right back after this short break? >>Yeah, yeah, yeah, yeah.

>>Yeah. >>From the Cube Studios in Palo Alto and Boston. It's the Cube covering IBM. Think brought to you by IBM. >>Welcome back to IBM. Think Digital 2020. This is the Cube, and we're really excited to have two great guests on Michael Jordan is the distinguished engineer with IBM Z Security. Michael, good to see you again. Welcome back. >>Thank you. It's good to be back. >>And, Matt, what Born is the program director and offering lead for Z 15. Good to see that. >>Thank you for having me, >>guys. Easy. Easy is a good place to be. Great corner, 61% growth. You got to love it. Regulations. It'll be feeling pretty good. I mean, other than what we're going through. But from a business standpoint, Z powered through, didn't it? >>It did. I mean, we're really pleased with the contribution that Z continues to make for our clients. Especially right now, given everything that's going on, business continuity, scale, resilient security. They're just so important for our clients in the platform. >>Yes. So we're gonna We're gonna talk a lot about this. Maybe Matt could start with you just in terms of, you know, you talk about. Ah, cyber resiliency. Hear that a lot? Um, e I think it may be. Means a lot of different things to a lot of different people. What does it mean? Busy? >>Yeah, for us. I mean, you know, we kind of start in many ways with, like that, this definition on that which talks about the ability to anticipate, withstand, recover, adapt all of these adverse conditions, might face or stresses compromises in attacks in your systems and your just cyber results. It's so it's a really important top of mind talking point from other clients who are thinking about this both from, I guess, the resilience when it comes to the systems and also the data as well. From our standpoint, you know, Z has been at the forefront of resilience for many, many generations. Now, whether that's the scale that systems we're able to provide, the ability to tap into more capacity is needed, whether on a temporary or permanent basis, cause you never know when a when a spike might be occurring on day, especially with clients going through digital transformation as well. The fact that we can talk about solutions being designed for seven nines of availability on. But the reason why clients like Tesco or alliances for their resilient banking platform or Department of Treasury in Puerto Rico depend on us or for a highly available solution. So it's never been more important for by us. >>So, Michael, from a technical standpoint, um, I mean, I go back to the rack f days and and I I used to ask, why is it that, you know, the mainframe had, you know, such good security, and it was explained to me years ago? Well, cause you knew everything that went on who touched what? You know, there was a clear understanding of that clear visibility of that. Um, but maybe you could explain just for laypeople from just from a technical standpoint. Why is it that Z has such strong cyber resiliency? >>Sure. So So some of it, I think, is there's 22 aspects that I want to mention first is, you know, culture, right? You know, the IBM Z, you know, development team and broader, you know, design team. We have in our culture to build systems that are secure and robust, that that's kind of part of our DNA. And so it's that mindset when you look at, you know, technologies like parallel system, flex and geographic geographically dispersed, parallel, parallel suspects, GPS. You know, those are ingrained in those technologies, but the other capability that we have or I should say, um, you know, benefit that we we have is we own the whole stack, right? We own, you know, the hardware we own the firmware, um, and we own the software that sits on top of there in the middle, where and so whether it's resiliency or whether it's security when we want to design and build solutions, you know, to make optimal solutions, you know any of those spaces we can actually design and architect the solutions, you know, both at the right point in the stack and across the stack as needed to really deliver on these capabilities. >>So, Matt, one of our partners, ET are holds these CEO roundtables, and one of the CEO said we really weren't ready from a resiliency standpoint. We're too focused on on er and kind of missed the boat on business continuity to narrow focus. I presume you're hearing a lot of that these days. I wonder if you could just tell us about some of the things that you're seeing with clients, Maybe the conversations you're having and how you're helping Sort of broaden that capability. >>Yeah, sure. I mean, to your point. I mean, nobody really could have quite predicted. You know what we're dealing with right now, but, you know, we have had over many generations of the Z platform, you know, clients deeply partnered with us to try and make sure they have a a highly available environment for business continuity. And, you know, just thinking about things from a Dell perspective. You know what they can do to fortify and make their solution sort of more resilient on the day by day basis. I mean, one of the things you might be talking about, some of the inherent capabilities we have a hassle. The fact that we build, you know, our systems with the additional capacity kind of baked in. Which means that for so many of our clients, you know, in the first in the first quarter, where they were seeing the huge amounts of peak workload kind of coming in, that they needed to be able to deal with the fact that we design our systems to be able to just kind of gobble up that work. With that we call dark capacity to be turned on at the drop of a hat. It's tremendously important because not only need to be offsite, just resilient in terms of the applications, but you need to get a deal with growth. You're going through that. The other aspect, which is a new capability with the 15 that kind of builds on what we could do with that dark past thing is this concept of instant recovery. But what we're actually helping clients do there in terms of fortifying and making their environment more resilient, is letting them attack into that dark capacity when they're going through restart activities of partitions, not just thinking about unplanned scenarios, but actually planned out just as well. So what that really helps with is because you always have to do planned maintenance. You know, when your systems, you know when you're partitions your your system because the environment. So what we're doing is saying when you're going through that restart sort of process, whether it's the shutdown, whether it's to bring up of the partition or the middleware or even in fact, actually helping you catch up. Kind of for what? You what you lost one weren't sort of processing workflow. We turn on that extra capacity in the system automatically for this boost window that were that we're helping our clients with. Not only we do that. Mike's point about owning a stack means that we can deliver that in a way that there's no increase in IBM software cost a reliever. So we're always kind of looking about what we can do to kind of move the ball forward to make a client's environment even more resilient as well. >>I've always, I learned from my mainframe days many, many years ago. And what when a vendor comes in and shows a new product, they always ask you what happens when something goes wrong? It's all about recovery that's always been one of the main frame strength. Mike, I want to ask you about data protection. I mean, it's a topic that again means a lot of things to a lot of people you know doesn't mean backup. There's data privacy. There's data Providence. There's data sovereignty. We talk about data protection from a Z prism. >>Sure, so So our point of view on data protection is is we view it as a as a multi layered proposition. It's not. It's not just one thing. In effect, we viewed the lens of a broader, you know, layered cybersecurity strategy where you know, data protection. And, you know, in this case, you know, talking about encryption and being another encrypt data on a massive scale is the foundation for, you know, a layered cyber security strategy, um, and providing capabilities for appliance. Do you protect data at the disk level with the 15? We also introduced the ability of actually being able to protect the data as it flows through their storage area network through something we call fibre channel endpoint security and then layering on top of that, you know, host based encryption capabilities, you know, in the operating system, whether it's, you know, buy or or data set level encryption and you know, then on top of that, they can layer additional capabilities for things like multi factor authentication to protect your privileged identities from being compromised or being able to do damage to your system and then, you know, building and layering. On top of that things like security, intelligence and being able to monitor and understand You know what, what's happening across the system. >>So I was talking with Developer the other day in cloud app pretty, you know, non mission critical. But ask them to use encryption and he said, Yeah, we could, but we don't cause it slows us down a little bit. So I'm wondering how you deal with that trade off performance versus Protection Z. How does he deal with that? >>Sure, So that's that. That's a great That's a great question. And that actually goes back to you know what we did with with our Z 14 so that the generation before and I think we've we've improved that with with the 15 and then I'll get to that in a bit. But one of the barriers that we recognized is exactly what you said is the You know, the cost of doing encryption is prohibitive, Um, and what we did is we have, ah, a cryptographic accelerator that's integrated into our micro processor that's capable of encrypting so each or it's capable of encrypting up to 14 gigabytes of data per second. And if you multiply that by the number of cores that you have. You know, a fully configured you nosy 15 met. What does it have any cores? Do we have in that 100 >>90 with >>190 So So do the math right? 190 times, you know, 14 gigabytes per second. It's an encryption powerhouse, and that can all be done synchronously with extremely low latency. So we have the horsepower to do encryption on a very broad scale with very, very low overhead. And that's what our clients are leveraging and taking advantage of. And with the Zy 15. That being we announced it and made available last year. We actually have now compression that's built into the micro processor so you can actually compress the data, Um, first and then encrypted. And there's a twofold benefits that first is now. I have less data to encrypt, so I have lowered my encryption overhead, and at the same time I've managed to preserve my storage efficiency. So it's a It's a twofold benefit there, >>you know. People talk off about Z, they talk about it, it's open. It's kind of all started back when you guys brought in Lennox. And now, of course, it's It's much more than that. Um, but I'm wondering how open plays into this notion of cyber resiliency in some respects there. Counter poised. But But how do you sort of square that circle for me? >>Yeah, I mean, it's kind of look at it is when it comes to openness and digital transformation, it's kind of doing it without compromise on. That's kind of the way I look at the Z platform because you're right. I mean the fact that we have the likes of open shift support on the seat platform or you can use, you know, answerable for for doing automation. I mean, were always looking to try and make sure that we support from A from a management standpoint or development standpoint. We'll use whichever tool frameworks languages are appropriate on the platform and integrated to a hyper cloud wherever you want to go. That's why when we look at it from the perspective of what it really means to have mission critical applications and why, it's why that is the key point about banks. Insurance companies, etcetera continue to trust. Z is there is the home for their system of record because they want to get the benefits. You know, the best of both worlds. So they want to be able to have the security, the resilience and the scale of the platform. But the same time they want to have flexibility to be able to use cloud native technologies to be able to deploy them on our platform. And then this micro sort of talking about the exciting thing for us is even going one step further. That says, if you do want your data to move around your hybrid cloud for very good reasons for certain scenarios, being able to have that capability to protect the data, not just encrypted that manage the privacy over the data as it flows out and see to kind of take those characteristics into the hybrid cloud is something that a lot of that clients been really, really excited to take advantage of it. It's >>about this conference. You might get certain >>charting Matt into a security guide. You see that? >>Yeah, >>I think everybody's got to be a security person these days. I want to ask about zero trust. You know, that term is thrown around a lot of, uh, you know, you can get kind of buzz, wordy. You see, people always have substance. I want to ask you guys what zero trust means the Io. >>So So I think there's, you know, my view of zeros where we're at from an industry from from zero. Trust is is very similar to where we're at with cloud, you know, going back a handful of years where if you ask 10 different people what you know, cloud was you get 10 different answers. Um, and none of them were probably wrong. And so I think, you know, we're very similar state in terms of our understanding and, you know, market maturity around zero trust. But there's, you know, at its for, you know, the the the The idea is, you know, we've been focused on protecting, you know, our environments using a castle and moat of approach. Um, and, you know, you know, protecting the perimeter. Yeah, and then trusting everything inside of inside of that. You know that that mode, if you will, um and what the zero trust is a recognition that that's not sufficient. And, you know, and then if you look at that in the context of our evolving and changing in environment and moving to hybrid multi clouds where, um, the notion of a perimeter is gone. You know that that strategy and approach for protection, it doesn't hold up. And so we need to evolve that, um And we need to have, you know, you know, move from the notion of, um, operational trust to a notion of technical trust and building, you know, building more sophisticated mechanisms for doing authentication, understanding broader what's happening across the environment and feeding that into, you know, decisions that are made in terms of who gets to access. What data. So, >>yeah, good, Matt, bring us home overnight. You know, this pandemic has really heightened our awareness of cyber resiliency. Business continuity have changed our our mindset and definition of those two things. But give us your final thoughts on this top. >>I think it's probably just been into sharp focus, really what? It what it means to have mission critical applications that are right at the heart of your of your business. And, you know, you come to realize very quickly. But if those services are not available to your clients, I mean it can have such a long lasting implications So I think people embittering you know their strategy when it comes to, you know, millions off applications with infrastructure and all of that in the context of business continuity, I think people are gonna gonna have a much sharper focus in the future to really see, you know, what is what does it mean? And it's the lifeblood of their business is not able todo operate and serve their clients. And probably as well, more and more applications that maybe weren't considered mission critical in the past will be considered mission critical now because it's not just the back end services, but it's the way the community a reply. It's so a lot of that, I think, is going to play out the way that people think about their business continuity strategy in the future. >>Yeah, you're right. Video conferencing has become mission critical, isn't it? Guys, thanks so much for coming on the Cube again. You know, keep up the good work. Uh, I really appreciate your time and your insights. Always, always great talking, talking Z. So thanks again. >>Thank you. >>All right. Thank you for watching. Everybody. This is Dave Volante for the Cube. Our wall to wall coverage of the think 2020 digital event experience. Keep right there. Right back after this short break. >>Yeah, yeah, yeah.