live from Las Vegas it's the cube covering IBM think 2018 brought to you by IBM hello everyone welcome back to the cube coverage here at IBM think 2018 in Las Vegas Nevada the Mandalay Bay it's a cubes exclusive covers three days of wall-to-wall interviews thought leaders experts entrepreneurs people making an impact and our next guest artists ani who's the co-founder of hosh io h OS h o de Ojo kayo advisor at the pink sky capital he's a cube alumni a walk in off the streets cuz he lives in Las Vegas but very instrumentals are connected to this community because of his pioneering work in in crypto blockchain and the future of money architects great to see you thanks for coming by thank you for having me it's good to be back on the cube great second time and second time yeah only couple we just saw each other the Bahamas the first security token conference yeah I bike on I I be on IBM's really big on supply chain this is their visitor old school you know generations of providing software for businesses b2b and now blockchains their big thing but blockchains yeah pretty straightforward yeah you know you get efficiencies but they're not talking about token economics because they talk about something execs here they're like well that implies the general public in their world thinks cryptocurrency they think Bitcoin so I want to connect the networks together our network IBM's network your network because the melting pot of this trend is really about blockchain cryptocurrency in the sense of the value around tokens and how tokens can be harnessed to capture the values I want to get your perspective as these worlds collide so I think that IBM is doing a great job by spearheading a blockchain movement and they're very they're focusing on the fortune 500 and the key with Fortune 500 companies right now is that they have rooms full of Java developers Java engineers and aetherium is the protocol right now that is most commonly found the majority of icos and token generation events that have occurred to date have all been on etherium x' network and etherium is the most and they found in blockchain however the etherium blockchain the language to build and launch token generation events on aetherium you have to write in a language called solidity and solidity is a new language and iBM has made a smart move by doing everything in Java and JavaScript similar to a lot of the new block chains that are aiming to compete with aetherium and the key distinction just to kind of put it out there when I get your reaction to and get some commentary around is IBM is not competing with public block chains they're looking at a in a different way they're saying hey you know you can have I guess private blockchains I mean it's not a really a dirty word they because they have a different use case correct I think it's very important especially when it comes to things like healthcare you look at the health care industry healthcare records will not be going on public block chains and so the hyper ledger fabric framework may make sense for things that need to be HIPAA compliant for example so reliability is key so what's their jannat like say hashed crafts got a lot of traction in their performance and their speed they got time stamps that's not a native blockchain yet that's kind of getting some traction IBM's got something similar for those markets that require the reliability the performance and the security so help the audience understand IBM's moves here because IBM's conservative so they don't really want to throw the word cryptocurrency out there because it might be misunderstood but this is gonna end up in token economics how are you explaining what the moves ibm's making to the average person that might not know the inside nuances in baseball for say the crypto market I think what's interesting is that iBM has a more mature focus on this space and you know they have direct ties historically to the fortune 500 companies the way others do not and so they've taken a much more sophisticated and a much much more conservative approach you don't see IBM throwing around the word cryptocurrency and that's a smart move because it's about the cryptography that secures block chains in a decentralized ecosystem and it's that the discussion of just tokens and token sales and leveraging tokens as a currency it's a premature time in this entire industry to be having that discussion so although it's going on it's a distraction for IBM you saying yeah because we but it's more interesting for smart contracts to be written that our functional smart contracts that for the first time ever white collared middlemen are being cut out of the picture in a new trustless decentralized ecosystem so talk about where IBM could take this with token economists obviously do you think that it's all leads to some sort of tokenization is that gonna be where the value capture is gonna be how does IBM get there in your mind I think they get there by having fortune 500 companies launch legitimate decentralized applications on their blockchain and that's just what Java JavaScript it's because most fortune 500 companies already have a plethora of Engineers globally that they can simply have start working on IBM's blockchain whereas you don't see that as a risk for IBM no that's that's IBM's advantage because today if the fortune 500 companies aren't building on aetherium whose blockchain mainly because of the learning curve it takes for a current full stack engineer to become a solidity engineer what's the etherium future now obviously they have they're working on lightning seeing some things going on that area the Lightning is Bitcoin is plasma yeah plasma sorry I got them confused so they got to go through the work this and some real work that's got to get done the theory of childs a big developer community the biggest the biggest so do those merge with the IBM communities downstream at some point or is it okay to be separate and does it matter I think they'll remain separate and in this case I I highly doubt that a theory IBM hyper ledger will go down the route that route stock has gone root stock essentially is the etherium virtual machine sidechain to the Bitcoin blockchain enabling smart contracts on the Bitcoin blockchain for the first time and rootstock is a very interesting project however IBM is its own ecosystem and the way in which they're catering to the fortune 500 is extremely intriguing and from Hojo's perspective we want to be auditing smart contracts that are functional that are written by more sophisticated players in the industry centralized ecosystem our main focus is just security auditing and there's gonna be a lot more smart contracts written by more sophisticated players on IBM's blockchain then possibly the other ones right now we have we have not seen a plethora of Fortune 500 companies by any means launching smart contracts on the theorems blockchain and blue chips banks or whatever as they try to disrupt themselves need to get us to partner governments okay so how about for a minute I just take a second to talk about your business I know we covered this at polycon and the Bahamas but for the sake of the context to IBM yeah talk about what you guys are doing we're specifically in the marketplace of partners would you sit if you were parting with IBM and and your role that you could possibly take with IBM so to take a step back quick host show the word itself hosho and means security in japanese and we started this company eight months ago my co-founder yo Kwon and I and our laser focus is blockchain security and being the global leader within the blockchain security space so as far as we see there's new blockchains being made new protocol tokens being launched as well as new tokens being launched as well as do smart contracts being written that are functional for the entire business and no matter what blockchain a smart contract is written on that smart contract is code that has been written and that code has to be audited by a professional third party and we are that professional third party that there's a line-by-line code review of the smart contract and finds all security vulnerabilities and we've been building proprietary tooling to find vulnerabilities faster and faster and faster we do a gas analysis to make sure that that blockchain is not being clogged we conduct the static analysis to find any hidden functionality within the framework of the smart contract and the last part which is very crucial is that yeah very uniquely qualified full stack engineer with a unique QA mindset and a security background who knows the language in which this is coded which currently most projects that were auditing our aetherium ERC 20 tokens written in solidity someone has to marry the source of truth which in the case of an ICO is a white paper and marry the white paper to the smart contract and make sure is the smart contract doing what the white paper says codify the white paper basically this process of auditing is gonna be ever more crucial within the the business that IBM does with Fortune 500 businesses because when a publicly traded company launches a smart contract for a decentralized application security is the highest priority and abilities is where the hackers could come in just be on a time to market getting those smart contract codes written it was fully baked it's irreversible once the smart contract is launched and millions of dollars are gonna go through this smart contract it's been regular practice in the cybersecurity world to type up code and to have it reviewed by a third party auditor we're simply applying the exact same logic to the blockchain space and it's exciting to see more blockchains by sophisticated players like IBM come to fruition and we're looking forward to actual projects from big players around the world launch on IBM's blockchain and hosho is looking to be a preferred partner of IBM's to do all their security work whether it's smart contract auditing or penetration testing and real quick on penetration testing that's our other core service that we provide and penetration testing is both for websites and for crypto currency exchanges in which we're making sure there's no security vulnerabilities within your website and finding every way possible to penetrate your website or your exchange and every time code is changed you open up the doors to more vulnerabilities and so in the crypto currency exchange space right now we're seeing that new exchanges are being made but sophisticated investors don't know if this is a safe place to trade hundreds of millions of dollars or not yeah and so when you got commerce being John I mean IBM as folk as you mentioned is legit and they're doing a great job by the way props to IBM for doing what they're doing they've been in for multiple years now and they're supporting the Apache project they're putting their their weight behind it but these are real-world examples granted supply chain might be boring to some audiences but not to others I mean you're moving real product around this is commerce with digital fingerprints and code and potentially tokens that's a highly gonna accelerate the payment process I mean the notion of clearing goes away it's instant yes this is a highly accelerated money transfer value capture value Tran for environment you can't take me chances yes and security is primal concern and we're excited that companies like IBM value security and this space is one that the dust has yet to settle and what's gonna help the dust settle within the blockchain ecosystem is more priority on security so what's your take if you are gonna give a talk here we're doing talking here in the cube so it's awesome it's gonna be alive and on-demand as well your advice to people saying you know we got a tokenizer our business I need to start with blockchain I can see some areas to create some efficiencies around some inefficient processes and create new business models I got to get started your thoughts my thoughts are take a step back and first evaluate do you have a business what problem are you solving once your business is actually generating some revenue and you've evaluated why the concept of a blockchain could be interesting for your business then pick a blockchain and stick to it and then when you start building on that block chain you've figured out that a token could actually be leveraged within this decentralized application that you're building then you can start figuring out what the token economics of it would actually be I think what people are doing nowadays is rushing to create a token because of their excitement about the fundraising mechanism that an ICO is and an ICO is democratizing to some extent at least global capital raising and I think that fundraising mechanism is not going anywhere that that fundraising mechanism is here to stay however the majority of ICO projects that we're seeing occurring today I don't think these companies will be around in the next couple of years which shows how immature to some extent the industry actually is whereas maybe the projects that are built and launched on IBM's block chains that they develop maybe they're more sophisticated and will be companies that have gone through a more rigorous process of making sure security was a primary concern and they wrote quality code for quality businesses that are actually leveraging decentralization in the appropriate way not the other way around of we want to raise capital so let's invent a reason to have a token or you have a big case right now in Silicon Valley at least is you have companies that are very serious a and B and decided let's do an icy overseer you see and that that's tricky it's not always the right solution when you're saying is don't confuse the ico crazy fundraising arbitrage and new new model to applying supply chain tokens and blockchain to a durable business agreed and on the same token we have people in the space whether they're investors they're lawyers PR firms exchanges they all need to mitigate their risk by keeping security as a concern for them both in-house and for the companies that they're working with yeah lawyers don't want to be doing lawyer work for a company that will turn out to be a scam coin and someone has to do a security audit of that token the same goes for a PR firm a marketer and in exchange exchanges should not be listing tokens that have not gone through a smart contract audit well it's good to know we got a cube alumni here in the cube to help us with our security audit yeah well the answers the life were in a cube interview so do we got one right here I want to just get into in topic you and I were talking of dinner the other night when we had we saw each other a few nights ago about the problem of picks and shovels and tools and maturity in this new emerging area can you um can you just take a minute to explain what that we were talking about there and I thought you had a good point I mean maturity of the space is not mature it's growing it's embryonic but moving fast and there's need for tools let's unpack that just share your thoughts vision so I think that a lot of people have been more excited to join in an IC o---- a token generation event and do more quick money grabs but to me what's more exciting is the infrastructure that's needed for this industry to actually grow and mature an infrastructure is infamously known as picks and shovels because when the gold rush happened the people who made the real money or the people selling the shovels to the gold diggers and what's included in that is businesses like our own hosho which is selling security audits of smart contracts doing penetration testing bringing maturity and making making things less risky for for everybody in this space so we start we see ourselves as selling picks and shovels on the other hand I'll give you an example Goldman Sachs has a trading desk today it's not 24/7 stock market Oh at 9:00 closes at 5:00 what happens tomorrow when a 24/7 crypto currency trading desk is turned on at Goldman Sachs do the traders that are now 24/7 have the appropriate tools and the governance built into software to manage a team of 24/7 traders at Goldman Sachs today when you have traders trading in the stock market they have a plethora of tools that make them snipers and you have certified market technicians telling hedge funds that this isn't gonna go up two points here in three points they're reading candlesticks in the cryptocurrency space it's like poking a stick you go from being a sniper to having a stick find by Wars like a blind man so companies there's a dozen companies that can be made building the infrastructure for just what I just said the governance with four trading floors this is a really good point and I wanted to bring it up because in these emerging markets these white spaces for tools and technology to help the overall trend grow faster has always been a successful man however you mentioned something about the goldman sachs trading this and that is it literally could be turned down overnight right so that's the problem you can accelerate things too fast and not be prepared that seems Oldman honest I'd know Goldman's done a great job at being very much forward-thinking they've been at every money 20/20 since the beginning of that FinTech conference and they're definitely in this pickle this exercise the analogy is a company can turn on a new model fairly quickly faster than the old days which we're taking months and then now you can do it really on a much shorter timeframe that means they potentially could be exposed if they go too fast yeah this is where the ecosystem has to help yeah I think the bulge bracket banks are treading the water very carefully JPMorgan is doing things they're involved with aetherium Z cash - JPMorgan has a lot going on on this front but these are publicly traded monster banks they're not going to take any risks these are they have a they have stockholders to to answer to they have the US government we have over 150 regulatory arms just regulating the finance industry in the United States and so I think it the American citizen citizen is quick to point fingers to bulge bracket banks and those banks are answering to too many regulatory arms this is one of the downsides of the United States right now in general is the increasingly coercive environment of the government ybm certainly got the blue chip company got the the fortune 500 but they also have a marketplace and that's where they could really kind of change the game feeling in those white spaces yeah IBM's marketplace sounds very exciting and my mind just goes to who's handling the security for everything to do with IBM blockchain we're hoping at Osho arch edge thanks for joining us thanks for sharing your your insight here in the queue with an IBM think conference breaking down all the top news that's really around blockchain at AI would date at the sin of the value proposition all being disrupted by new decentralized technologies blockchain being the beginning and a lot more is happening and certainly we're in and bring it to you on the cube no matter where it is will be there I'm John furrow here and Las Vegas for IBM think coverage we'll be back with more coverage after this short break [Music]

>> Interviewer: Live from Las Vegas, it's the Cube, covering IBM Think 2018. Brought to you by IBM. >> Hello everyone welcome to the Cube, I'm John Furrier, we are here in Las Vegas for the Cube coverage of IBM Think 2018. So Cube Studios, live coverage, all day long three days, this is our third day, our next guest, is Cube alumni, Inhi Cho Suh, she's also the general manager of Watson Customer Engagement, been on so many times I don't know, eight, ten, a lot, you're a VIP. Great to see you. >> Thank you, good seeing you John, I really enjoy hanging out with you guys. >> So we love to hear what you're up to, cause you always have your finger on the pulse, here at IBM, take a minute to explain the group that you're in, Watson Customer Engagement, that's kind of a nice bumper-- but there's a lot to it, you're doing now. >> There is. >> It's large it's got billions of dollars in revenue, give us the numbers, run the numbers for us, size, people, products, all in 30 seconds, no go. >> It's an exciting space. So Watson Customer Engagement is really a Watson business applications, that are relevant for marketers, merchandisers, digital commerce leaders, as well as supply chain professionals. So my team really develops the software, both for on premises and SasS for everything from digital marketing experiences, personalized marketing, campaign management, to managing next generation of interactive sites and shopping sites, to understanding customer journeys, and journey analytics, so supply chains, and big big collaborations. So it is a pretty broad breadth of about 21 solutions in offerings, that span many industries and many countries. >> We you got your hands in a lot of great stuff across the board but I think the big news today was the blockchain announcements, you guys featured a solution on stage, this is hard news, so explain, so talk about the hard news, you have an announcement, it's on stage, it's blockchain related, >> Yup absolutely so my team has been working on creating more analytics in our supply chain solution. So one of our solutions is called Supply Chain Insights which really is about adding visibility to disruptions. And being able to apply analytics to let's say management response, incident management. Then we were thinking about our supply chain business network, so that is a separate offering that we have, which is about 6 thousand clients are on it. With 400 thousand trading partners, we do 8 million transaction documents a day, in terms of this trading network. What we did was we announced a shared visibility ledger, for any of our clients and partners, in the supply chain business network. So we're adding blockchain to that as a way to ensure that transparency, as well as speed of operations, so we're really excited about it >> And security. >> And security huge. >> Huge. So supply chain, blockchain, value activities, all this stuff, this is where blockchain shines, because this is a core competency of IBM, for generations. >> Oh absolutely. >> I mean providing applications for value chains, so this is interesting, so just to get the clarification the product is on preview? >> Yeah it's a technology showcase that we're doing right now that we've prototyped, and we're going to make it available as an offering that's called shared ledger, for any client that's actually on our supply chain business network today. >> And what's in it for them? How do they implement it, and the vision of the product, they already have a product, they bolt in on, is this a new offering? >> Yeah so if they already have it, they'll get access to let's say a visibility layer, so the shared ledger will allow you to see where in the process your transaction document is. So let's say you're in the area of consumer and merchandising and moving goods. From in transit. So knowing when a box actually left a particular warehouse, is it in transit or not and did it actually deliver on time. There's a lot of parties involved in all of that. >> And paperwork, and manual processing, data entry >> You got it. Now you have the actual stamped records, of who's touched it, when, and whether or not with IOT instrumentation too. Of when things have moved or not. >> So this brings up the conversation we've been having on the Cube about the inefficiencies now going to be abstracted away with things like blockchain and AI. Used cases that you've seen that jump out at you, that you'd like to share, that can highlight that, obviously AI, I said analytics, that's your wheelhouse. Now blockchain's emerging, I mean this is the innovation sandwich. AI on one hand is bread, and then you got blockchain, and data's the meat. >> Well you know especially in areas like supply chain, where small bits of optimization, meaning a one percent improvement, or resolving invoice and settlements, have such huge ripple effects downstream. So there was a great example in terms of our Maersk work, and global trade and blockchain. Is food shipments in particular, and food safety. And being able to resolve the source of where the original food, whether it was grown, or harvested, and being able to do that in seconds, not weeks, right, going through that paperwork. So there's huge opportunities there. We're excited because we're now adding in not just AI capabilities, but we're also adding in collaboration capabilities into that, which then allow groups of people to interact together, in time, just in moment, to address alternative decisions and routes. >> Inhi I want to get your personal perspective on something, we've had so many conversations in the past around points in time, show messaging, and products you're announcing, it seems like this show at IBM, with everything coming together under one big tent, you see visibility now on unit economics of value, you're starting to see the path towards solutions, for customers, it's not as foggy as it once was. How do you explain that, you've see this evolve, and Jamie Thomas and I were talking earlier about, you know we base an investments and bets is now paying off what's really happening here, what's the big ah ha moment, where all this is kind of crystallizing right now. >> Well a couple things have happened. You know IBM's gone through, we've gone through our own transformation. If you think about even four or five years ago, the mix of our portfolio, to what it is now, less than I would say three billion of our revenue basis was in the mix that we have now. And if you think about our fourth quarter earnings even as we enter first quarter, we had I think over 46 percent, 46 to 48 percent of our portfolio tied to what we call our strategic imperatives. And that's a huge transformation, so part of that is a couple things, one is, we said look, this world of AI leverages and consumes a tremendous amount of data, and we want to make sure that you're protecting your data set. So we want to be thoughtful about how you engage strategically so let's have your strategy, let's make sure you understand your data, we want to protect you in that. We want to actually enable you to curate, train, harvest, the insights from that. We want to make sure we leverage your expertise. So your people, your talent, so augmenting them with capabilities that are work flow oriented, task management, self discovery, and then most importantly, delivering platforms multiple platforms quite frankly, over time that learn. Right, learn to interact, and evolve and can integrate these data sets, in order to give our clients speed. So that's what's been great about here, is we're actually getting to share our own transformation story, but also our portfolio has evolved across strategy, data, and platform. >> It's been sure and a clear line of sight on some value. What's the big bets that you could look back on the past five years and say wow, we made some big bets, these one's paid off. What were those big bets in your mind. You've been involved in a lot of deals I know, analytics side, what were the big bets that IBM made that's paying off right now? >> You know I feel like I've known you almost eight, nine years now right, since you guys started on some of this. I would say for example, our better round big data. That is a huge bet, in terms of our analytics capability, and that is a full spectrum, that is something that we've been investing in for quite a long time. And then when you think about the bet on Watson and AI, and transforming, not just businesses and business process but actually transforming professions. We have Watson today operating across multiple industries, like 20 different industries in 45 countries. Multiple languages, multiple implementations, and it's getting better and better, whether it's healthcare, it's tax accounting, it's law and cyber security, we're seeing huge opportunities >> Data paid off big time. >> Huge payoff. Cloud. Cloud is huge for every client, because they're in different states of their journey. There may be certain application workloads, that they want to manage themselves, there maybe be applications that they want, and services that they want to subscribe to in the cloud. Public, private, hybrid, we're having that dialogue. So I think everyone is on that journey now. So that's another huge bet. And then verticalizing the application sets. And so one of the things that I've got the opportunity to be a part of right now, is really the business applications, and how are we infusing Watson into our business applications. >> And leveraging the horizontal scale of Cloud, and everything else, and blockchain. So what's the priorities for you going into the new business, you got a big organization, thousands of employees, or people work for you, a lot going on, what's the priorities, what is the focus? >> I've got about five thousand people on the team, so small team (laughs) Globally dispersed, we're working on a number of things actually, and what's so exciting about that is we're thinking about personalizing AI at mass scale. So when you think about, through the lens of a marketer, real time personalization is becoming more, and more challenged, because of not only the data sets, but the types of tools and the varied tool applications, you're switching context all the time. So we're providing ways to integrate and mix data sets, so our user behavior exchange data set really gives insights around consumer sentiment, behavior, and context. The work the team has been doing around metropolts, hyper local store and a city location data, mixing that with events and other activities, and customer transaction data. So a lot on that front. The second category we're really focused on, is next generation of embedding, what I would consider cognitive services, like search, headless search, so really understanding intent that's pervasive, on other platforms. We're adding things also, like embedded agents, so everyone's right now talking about you know they want to create chat bots, and bots, But they may be embedded in systems, and they also may be embedded in different types of use cases, call center, so forth, so we're excited about that. And then obviously the supply chain area with blockchain, so we've got a lot. >> And the payoff in data's interesting because now you've got contextual relevance for things that are embedded, like chat bots, or whatever at the right time. And also if you think about the gamification opportunities, data now in these network affect markets, whether it's blockchain evolving into cryptocurrency, and decentralized web applications. The commerce piece is going to be impacted. Your vertical integrations are going to be gamified. This is coming right down main street for IBM isn't it? >> Well and if you think about blockchain one of the biggest challenges is onboarding into a network. So what we're trying to do is one of the use cases is actually adding blockchain to existing networks, and so that once you're onboarded into a network, you can connect to other networks. So a network of networks sort of effect. >> And their effects is all data driven. >> It's all data driven. So membership and governance around blockchain is important, and then the other piece we're thinking through is use cases by vertical, so retail, so when you go through that lens, and retail in terms of fashion, it's a very different lens than when you think through the business lens of retail banking, right. And our team is thoughtful about what does that mean in the next generation of content services. So how do you automatically tag images, and surface them up, for it be published in the right media form, independent of the channel, or the navigation tools or assets. There's a lot here I'm excited. >> So final question for you, it's kind of a philosophical one, you can answer it or not. You know you always get the zingers from me, but the tools are changing too, so in these new emerging markets, where there's just not-- take finance for instance and say cryptocurrency, and software, the tooling's not there, you can't just stand up at a trading exchange, that's in these new token environments, or what these apps have. So there's new tooling coming out, that's a concern, how are you guys helping customers get the tooling? Is that on your radar? Is that something you guys are talking about? >> Well you know it's interesting that you bring it up, which is technology adoption. I'm just going to call it in a broader sense, because part of tooling is really about in user education and enablement. We are actually adding a capability called Ask Watson, embedded in our software and services, especially our SasS properties, such that hey, I want to build a new email campaign, well what are my choices, and instead of reading through a traditional manual, or having to go and find someone, or watching a bunch of YouTube videos, what if Watson actually surfaced, here are ways here are some existing templates, where would you like to start. And all of a sudden this kind of co-creation happens. So we're actually thinking of applying Watson, embedded in our software, and SasS services to enable, not just tooling, actually automatic assistance in the task, in the moment. >> Yeah no need to code. Insights is a service. >> Huge, customer insights is actually one of our top applications. So we're doing capabilities around journey analytics, and customer experience analytics, so think about when you're any business person, who's got a set of clients, you know what they want to do as they express their brand, it may be done through email communications, it may be push notifications, there may be a SEO notification, and in that scenario, at what point, does the consumer, or the be to be struggle, in actually fulfilling a transaction. Was it as they're zooming in and doing product comparisons was it as they were looking at post purchase serviceability. We are able to actually understand and look at their journey as they travel through all these touch points. So we're actually doing customer experience analytics, too. So for me, just coming from that data analytics background, into this application space of so many domain practitioners, >> And these applications got to be real time, they got to have the data analytics. Inhi, great to see you, thanks for coming on the Cube, it's been eight, nine years, it feels like in analytics years it's like 20. You look great, thanks for sharing your insights, on the Cube and congratulations on your new role, >> Thank you >> Thanks for stopping by the Cube. I'm John Furrier here in the Cube Studios, IBM Think 2018, back with more coverage after this short break.

>> Announcer: Live from Las Vegas, it's The Cube. Covering IBM Think 2018, brought to you by IBM. >> Welcome back to IBM Think 2018. My name is Dave Vellante and you're watching The Cube, the leader in live tech coverage. This is IBM's inaugural Think event. Companies consolidated about six major events into one We're trying to figure it out, 30-40,000 people there's too many people to count, it's just unbelievable. Mary O'Brien is here, she is the vice president of research and development at IBM in from Cork, Ireland. Mary, great to see you, thanks for coming on The Cube. >> Thank you, Dave. >> So tell us a little bit more about your role at IBM as head of research and development. >> Okay so I'm head of research and development for IBM Security explicitly so in that capacity I manage a worldwide team of researchers and developers and we take products from, you know, incubation, initial ideas all the way through to products in the field. Products that help defend businesses against cyber crime. >> So, Jenny was talking today about, you know, security is one of the tenants of your offerings at the core. >> Mary: Yes. >> So, everybody talks about security. >> You can't bolt it on, you know, there's a lot of sort of conversations around that. What does that mean, security at the core from a design and R & D perspective? >> That actually means that the developers of applications are actually aware of security best practices as they design, as they architect and design their applications. So that they don't deliver applications to the field that have vulnerabilities that can be exploited. So, instead of trying to secure a perimeter of an application or a product or, you know, a perimeter full stop they actually design security into the application. It makes it a much more efficient, much cheaper way to deliver security and also, you know, much stronger security base there. >> So, I wonder if you could relate, sort of, what you guys are doing in security with what's happened in the market over the last 10 or 15 years. So, it used to be security was, you know, hacktivists and you know throw some malware in and maybe do some disruption has become cyber criminals, you know, big business now and then of course you've got nation states. >> Mm-hmm How have you had to respond specifically within the R & D organization to deal with those threats? >> So, you know, you have described the evolution of cyber crime over the last years and for sure it's no longer kids in a basement you know, hacking to, for the fun of it. Cyber crime is big business and, you know, there's money to be made for cyber criminals. So, as a result they are looking to hack in and get high value assets out of enterprises, and of course, we as an organization and as a security business unit have had to respond to that. By really understanding, you know, what constitutes a very mature set of security competencies and practices and you know how we break down this massive problem into you know, bite sized consumable pieces that any business can consume and work into their enterprise in order to protect them. So, we have developed a portfolio of products that look at protecting all parts of your enterprise. You know, by infusing security everywhere, you know, on your devices, on the, you know, the perimeter of your business. Protecting your data, protecting all sorts, and we also have developed a huge practice of security professionals who actually will go out and do it for you or will, you know, assess your security posture and tell you where you've got problems and how to fix them. >> I remember a piece that our head of research, >> Peter Burris, wrote years ago and it was entitled something like "Bad User Behavior will Trump Good Security Every Time" and so my understanding is phishing is obviously one of the big problems today. How do you combat that, can you use machine intelligence to help people, you know, users that aren't security conscious sort of avoid the mistakes that they've been making? >> So, before I get into the, the complicated, advanced, you know, machine learning and artificial intelligence practices that we are bringing to bear now, you know, it's important to be clear that you know, a vast number of breaches come from the inside. So, they come from either the sloppy employee who doesn't change their password often or uses the same password for work and play and the same password everywhere. Or, you know, the unfortunate employee who clicks on a malicious link and you know, takes in some malware into their devices and malware that can actually you know, move horizontally through the business. Or it can come from you know, the end user or the insider with malicious intent. Okay, so, it's pretty clear to all of us that basic security hygiene is the fundamental so actually making sure that your laptop, your devices are patched. They have the latest security patches on board. Security practices are understood. Basic password hygiene and et cetera, that's kind of the start. >> Uh oh. >> Okay keep going. >> Okay, so-- >> I'm starting to sweat. >> So, you know, and of course, you know, in this era of cyber crime as we've seen it evolve in the last few years, the security industry has reached a perfect storm because it's well known that by 2020 there will be 1.2 million unfilled security professional roles, okay? Now, couple that with the fact that there are in the region, in the same time frame, in the region of 50 billion connected devices in the internet of things. So what's happening is the attack landscape and you know, the attack surface is increasing. The opportunity for the cyber criminalist to attack is increasing and the number of professionals available to fight that crime is not increasing because of this huge shortage. So, you know, you heard Jenny this morning talking about the era of man assisted by machine so infusing artificial intelligence and machine learning into security products and practices is another instantiation of man being assisted by machine and that is our, our tool and our new practice in the fight against cyber crime. >> So when I talk to security professionals consistently they tell us that they have more demand for their services than supply to chase down, you know, threats. They have, they struggle to prioritize. They struggle with just too many false positives and they need help. They're not as productive as they'd like to be. Can machine intelligence assist there? >> Absolutely, so computers, let's face it, computers are ideally placed to pour over vast quantities of data looking for trends, anomalies, and really finding the needle in the haystack. They have such a vast capacity to do this that's way out, you know, that really surpasses what a human can do and so you know, with, in this era of machine learning you can actually you know, equip a computer with a set of basic rules and you know, set it loose on vast quantities of data and let it test and iterate those rules with this data and become increasingly knowledgeable you know, about the data. The trends in the data, what the data, what good data looks like, what anomalous data looks like and at speed point out the anomalies and find that needle in the haystack. >> So, there's a stat, depending on which, you know, firm you look at or which organization you believe, but it's scary none the less. That the average penetration is only detected 250 or 350 days after the infiltration, and that is a scary stat, it would take a year to find out that somebody has infiltrated my organization or whatever it is, 200 days. Is that number shrinking, is the industry as a whole, not just IBM, attacking that figure? First of all, is it a valid figure, and are you able to attack that? >> Well, the figure is definitely scary. I don't know whether your figure is exactly >> Yeah, well the latest figure but it's a scary figure >> Yeah. and it's well known that attackers will get in. So, of course, there's, uh there's the various phases of, you know, protecting yourself. So, you're going to try to avoid the attackers getting in in the first place. Using the various hygienic means of you know, keeping your devices, you know, clean and free from vulnerabilities and so on. But you've also got to be aware that the attacker does get in so now you've got to make sure that you limit the damage that they can cause when they're in. So, of course, you know security is a, you know you can take a layered approach to security. So you've got to firstly understand what is your most valuable data, where are your most valuable assets and layer up the levels of security around those first. So you make sure that if the attacker gets in, they don't get there and you limit the damage they can do and then of course you limit their ability to exfiltrate data and get anything out of your organization. Because I mean if they are just in there, of course they can do some damage. But, the real damage happens when they can manage to exfiltrate data and do something with that. >> So again Mary, it make sense that artificial intelligence or machine intelligence could help with this but specifically what do you see as the future role of Watson as it relates to cyber security? >> So, I mentioned the shortage of security professionals and that growing problem, okay so Watson in our cyber security space acts as an assistant to the security analyst. So, we have taught Watson the language of cyber security, and Watson manages to ingest vast troves of unstructured security data, that means blogs and you know, written text of security data from, that's available on the internet and out there all day, everyday. It just ingests this and fills a corpus of knowledge with this, with these jewels of information. And, basically that information and that corpus of knowledge is now available to a security analyst who, you know, a junior security analyst could take years to become very efficient and to really be able to recognize the needle in the haystack themselves. But with the Watson assistant they can embellish their understanding and what they see and all of the, all of the relationships and the data that augments the detail about a cyber incident you know, fairly instantaneous. And it, you know, really augment their own knowledge with the knowledge that would take years to generate, you know. >> So, I wonder if we could talk about collaboration a little bit because this is good versus evil. You guys are like one of the super heroes and your competitors are also sort of super heroes. >> Of course. >> You got Batman, you got Superman, Catwoman, and Spiderman, et cetera. How do you guys collaborate and share in a, highly competitive industry? Well, they're vary as far as you know, appearing for sharing okay, so firstly you absolutely nailed the importance for sharing because you know, the cyber criminals share on the dark web. They actually share, they sell their wares, they trade, you know so very important for us to share as well. So, you know, there are various industry forum for sharing and also organizations like IBM have created collaborative capabilities like we have our X-force Exchange which is basically a sharing portal. So, any of our competitors or other security organizations or interested parties can create you know, a piece of work describing a particular incident that they are investigating or a particular event that's happening and others can add to it and they can share information. Now, historically people have not been keen to share in this space so it is an evolving event. >> So speaking of super heroes I got to ask ya, a lot of security professionals that I talk to say well when I was a kid I read comic books. You know, I envisioned saving the world. So, how did you, how did you get into this, and was that you as a kid? Did you like-- >> No, it wasn't. I'm not a long term security professional. But, I've been in technology and evolving products for, you know, in the telecommunication business and now security over many years. So, I got into this to bring that capability of delivering quality software and hardware products to the field back in 2013 when a part of our IBM security business needed some leadership. So, I had the opportunity to take my family to Atlanta, Georgia to lead a part of the IBM security business then. >> Well, it's a very challenging field. It's one of those, you know, never ending, you know, missions so thank you for your hard work and congratulations on all the success. >> Thank you David. >> Alright, appreciate you coming on The Cube, Mary. >> Thank you. >> Keep it right there everybody, we will be back with our next guest, you're watching The Cube. We're live from IBM Think 2018 in Las Vegas, be right back. (pleasant music)

>> Narrator: From Las Vegas, it's The Cube. Covering IBM Think 2018. Brought to you by IBM. >> Welcome back to IBM Think, everybody. My name's Dave Vallante, I'm here with Peter Burris. You're watching The Cube, the leader in live tech coverage. This is our day three. We're wrapping up wall to wall coverage of IBM's inaugural Think Conference. Thirty or forty thousand people, too many people to count, I've been joking all week. Sam Werner is here, he's the VP of Offering Management for Software Defined Storage, Sam, good to see you again. And Steve Kenniston is joining him otherwise known as the storage alchemist. Steven, great to see you again. >> Steven: Thanks, Dave. >> Dave: Alright, Sam. Let's get right into it. >> Sam: Alright. >> Dave: What is the state of data protection today and what's IBM's point of view? >> Sam: Well, I think anybody who's been following the conference and saw Jenny's key note, which was fantastic, I think you walked away knowing how important data is in the future, right? The way you get a competitive edge is to unlock insights from data. So if data's so important you got to be able to protect that data, but you're forced to protect all this data. It's very expensive to back up all this data. You have to do it. You got to keep it safe. How can you actually use that back-up data to, you know, perform analytics and gain some insights of that data that's sitting still behind the scenes. So that's what it's really all about. It's about making sure your data's safe, you're not going to lose it, that big big competitive advantage you have and that data, this is the year of the incumbent because the incumbent can start unlocking valuable data, so - >> Dave: So, Steve, we've talked about this many times. We've talked about the state of data protection, the challenges of sort of bolting on data protection as an afterthought. The sort of one size fits all problem, where you're either under protected or spending too much and being over protected, so have we solved that problem? You know, what is next generation data protection? What does it look like? >> [Steve} Yeah, I think that's a great Question, Dave. I think what you end up seeing a lot of... (audio cuts out) We talk at IBM about the modernize and transform, a lot. Right? And what I've started to try to do is boil it down almost at a product level. WhY - or at least an industry level - why modernize your data protection environment, right? Well if you look at a lot of the new technologies that are out there, costs have come way down, right? Performance is way up. And by performance around data protection we talk RPO's and RTO's. Management has become a lot simpler, a lot of design thinking put in the interfaces, making the Op Ec's job a lot easier around protecting information. A lot of the newer technologies are connected to the cloud, right? A lot simpler. And then you also have the ability to do what Sam just mentioned, which is unlock, now unlock that business value, right? How do I take the data that I'm protecting, and we talk a lot about data reuse and how do I use that data for multiple business purposes. And kind of unhinge the IT organization from being the people that stumble in trying to provide that data out there to the line of business but actually automate that a little bit more with some of the new solutions. So, that's what it means to me for a next generation protection environment. >> Dave: So it used to be this sort of, okay, I got an application, I got to install it on a server - we were talking about this earlier - get a database, put some middleware on - uh! Oh, yeah! I got to back it up. And then you had sort of these silos emerge. Virtualization came in, that obviously change the whole back up paradigm. Now you've got the cloud. What do you guys, what's your point of view on Cloud, everybody's going after this multi-cloud thing, protecting SAS data on prem, hybrid, off-prem, what are you guys doing there? >> Sam: So, uh, and I believe you spoke to Ed Walsh earlier this we very much believe in the multi-cloud strategy. We are very excited on Monday to go live with a Spectrum Protect Plus on IBM's cloud, so it's now available to back up workloads on IBM Cloud. And what's even more exciting about it is if you're running Spectrum Protect Plus on premises, you can actually replicate that data to the version running in the IBM cloud. So now you have the ability not only to back up your data to IBM cloud, back up your data IN IBM cloud where you're running applications there, but also be able to migrate work loads back and forth using this capability. And our plan is to continue to expand that to other clouds following our multi-cloud strategy. >> Dave: What's the plus? >> Sam: Laughs >> Dave: Why the plus? >> Kevin: That's the magic thing, they can't tell you. >> Group: (laughing) >> Dave: It's like AI, it's a black box. >> Sam: Well, I will answer that question seriously, though. IBM's been a leader in data protection for many years. We've been in the Gardeners Leaders Quadrant for 11 years straight with Spectrum Protect, and Spectrum Protect Plus is and extension of that, bringing this new modern approach to back up so it extends the value of our core capability, which you know, enterprises all over the world are using today to keep their data safe. So it's what we do so well, plus more! (laughing) >> Dave: Plus more! - [Sam] Plus more. >> Dave: So, Steve, I wonder if you could talk about the heat in the data protection space, we were at VM World last year, I mean, it was, that was all the buzz. I mean, it was probably the most trafficked booth area, you see tons of VC money that have poured in several years ago that's starting to take shape. It seems like some of these upstarts are taking share, growing, you know, a lot of money in, big valuations, um, what are your thoughts on What's that trend? What's happening there? How do you guys compete with these upstarts? >> Steve: Yeah, so I think that is another really good question. So I think even Ed talks a little bit about a third of the technology money in 2017 went to data protection, so there's a lot of money being poured in. There's a lot of interest, a lot of renewed interest in it. I think what you're seeing, because it cut - it's now from that next generation topic we just talked about, it's now evolving. And that evolution is it's not, it's no longer just about back up. It's about data reuse, data access, and the ability to extract value from that data. Now all of a sudden, if you're doing data protection right, you're backing up a hundred percent of your data. So somewhere in the repository, all my data is sitting. Now, what are the tools I can use to extract the value of that data. So there used to be a lot of different point products, and now what folks are saying is, well now, look, I'm already backing it up and putting it in this data silo, so to speak. How do I get the value out of it? And so, what we've done with Plus, and why we've kind of leap frogged ourselves here with - from going from Protect to Protect Plus, is to be able to now take that repository - what we're seeing from customers is there's a definitely a need for back up, but now we're seeing customers lead with this operational recovery. I want operational recovery and I want data access. So now, what Spectrum Protect Plus does is provides that access. We can do automation, we can provide self service, it's all rest API driven, and then what we still do is we can off load that data to Spectrum Protect, our great product, and then what ends up happening is the long term retention capabilities about corporate compliance or corporate governance, I have that, I'm protecting my business, I feel safe, but now I'm actually getting a lot more value out of that silo of data now. >> Peter: Well, one of the challenges, especially as we start moving into an AI analytics world, is that it's becoming increasingly clear that backing up the data, a hundred percent of the data, may not be capturing all of the value because we're increasingly creating new models, new relationships amongst data that aren't necessarily defined by an application. They're transient, then temporal, they're, they come up they come down, how does a protection plane handle, not only, you know, the data that's known, from sources that are known, but also identifying patterns of how data relationships are being created, staging it to the appropriate place, it seems as though this is going to become an increasingly important feature of any protection scheme? >> Steve: I think, I think a lot - you bring up a good topic here - I think a lot of the new protection solutions that are all rest API driven now have the capability to actually reach out to these other API's, and of course we have our whole Watson platform, our analytics platform that can now analyze that information, but the core part, and the reason why I think - back to your previous question about this investment in some of these newer technologies, the legacy technologies didn't have the metadata plane, for example, the catalog. Of course you had a back up catalog , but did you have an intelligent back up catalog. With the Spectrum Protect Plus catalog, we now have all of this metadata information about the data that you're backing up. Now if I create a snapshot, or reuse situation where to your point being, I want to spin something back up, that catalog keeps track of it now. We have full knowledge of what's going. You might not have chosen to again back that new snap up, but we know it's out there. Now we can understand how people are using the data, what are they using the data for, what is the longevity of how we need to keep that data? Now all of a sudden there's a lot more intelligence in the back up and again to your earlier question, I think that's why there's this renewed interest in kind of the evolution. >> Dave: Well, they say at this point you really can't do that multi-cloud without that capability. I wanted to ask you about something else, because you basically put forth this scenario or premise that it's not just about back up, it's not just about insurance, my words, there's other value that you could extract. Um, I want to bring up ransomware. Everybody talks about air gaps - David Foyer brings that up a lot and then I watch, like certain shows like, I don't know if you saw the Zero Days documentary where they said, you know, we laugh at air gaps, like, oh! Really? Yeah, we get through air gaps, no problem. You know, I'm sure they put physical humans in and they're going to infect. So, so there's - the point I'm getting to is there's other ways to protect against ransomware, and part of that is analytics around the data and all the data's - in theory anyway - in the backup store. So, what's going on with ransomware, how are you guys approaching that problem, where do analytics fit? You know, a big chewy question, but, have at it. >> Sam: Yeah, no I'm actually very glad you asked that question. We just actually released a new version of our core Spectrum Protect product and we actually introduced ransomware detection. So if you think about it, we bring in all of your data constantly, we do change block updates, so every time you change files it updates our database, and we can actually detect things that have changed in the pattern. So for example, if you're D-Dup rate starts going down, we can't D-Dup data that's encrypted. So if all of a sudden the rate of D-Duplication starts going down that would indicate the data's starting to be encrypted, and we'll actually alert the user that something's happening. Another example would be, all the sudden a significant amount of changes start happening to a data set, much higher than the normal rate of change, we will alert a user. It doesn't have to be ransomware, it could be ransomware. It could be some other kind of malicious activity, it could be an employee doing something they shouldn't be - accessing data that's not supposed to be accessed. So we'll alert the users. So this kind of intelligence, uh, you know is what we'll continue to try to build in. IBM's the leader in analytics, and we're bringing those skills and applying it to all of our different software. >> Dave: Oh, okay. You're inspecting that corpus of backup data, looking for anomalus behavior, you're say you're bringing in IBM analytics and also presumably some security capabilities from IBM, is that right? >> Sam: That's right. Absolutely. We work very closely with our security team to ensure that all the solutions we provide tie in very well with the rest of our capabilities at IBM. One other thing though, I'll mention is our cloud object storage, getting a little bit away from our backup software for a second, but object storage is used often - >> Kevin: But it's exciting! >> Sam: It is exciting! It's one of my favorite parts of the portfolio. It's a place where a lot of people are storing backup and archive data and we recently introduced worm capability, which mean Write Once Read Many. So once it's been written it can't be changed. It's usually used for compliance purposes but it's also being used as an air gap capability. If the data can't be changed, then essentially it can't be you know encrypted or attacked by ransomware. And we have certification on this as well, so we're SEC compliant, we can be used in regulated industries, so as we're able to in our data protection software off load data into a object store, which we have the capability, you can actually give it this worm protection, so that you know your backup data is always safe and can always be recovered. We can still do this live detection, and we can also ensure your backup is safe. >> Dave: That's great. I'm glad to hear that, cause I feel like in the old days, that I asked you that question about ransomware, and well, we're working on that - and two years later you've come up with a solution. What's the vibe inside of IBM in the storage group? I mean it seems like there's this renewed energy, obviously growth helps, it's like winning, you know, brings in the fans, but, what's your take Steve? And I'll close with Sam. >> Steve: I would almost want to ask you the same question. You've been interviewing a lot of the folks from the storage division that have come up here today and talked to you. I mean you must hear the enthusiasm and the excitement. Right? >> Dave: Yeah, definitely. People are pumped up. >> Steve: And I've rejoined IBM, Sam has rejoined IBM, right? And I think what we're finding inside is there used to be a lot of this, eh yeah, we'll eventually get there. In other words, it's like you said, next year, next year. Next, next quarter. Next third quarter, right? And now its, how do we get it done? People are excited, they want to, they see all the changes going on, we've done a lot to - I don't want to say sort out the portfolio, I think the portfolio's always been good - but now there's like a clean crisp clear story around the portfolio, how they fit together, why they're supposed to - and people are rallying behind that. And we're seeing customer - we're voted by IDCE, number one in the storage software business this year. I think people are really getting behind, you want to work for a winning team, and we're winning and people are getting excited about it. >> Dave: Yeah, I think there's a sense of urgency, a little startup mojo, it's back. So, love that, but Sam I'll give you the last word, before we wrap. Just on Think? Just on the Market? >> Sam: I got to tell you, Think has been crazy. It's been a lot of fun so far. I got to tell you, I have never seen so much excitement around our storage portfolio from customers. These were the easiest customer discussions I've ever had at one of these conferences, so they're really excited about what they're doing and they're excited about the direction we're moving in. So, yeah. >> Dave: Guy, awesome seeing you. Thanks for coming back on The Cube, both of you, and, uh, really a pleasure. Alright. Thank you for watching. Uh, this is a wrap from IBM Think 2018. Guys, thanks for helping us close that up. Peter, thank you for helping - >> Peter: Absolutely. >> Dave: me co-host this week. John Furie was unbelievable with the pop up cube, really phenomenal job, John and the crew. Guys, great great job. Really appreciate you guys coming in from wherever you were Puerto Rico or the Bahamas, I can't keep track of you anymore. Go to siliconangle.com, check out all the news. TheCube.net is where all these videos will be and wikibon.com for all the research, which Peter's group has been doing great work there. We're out! We'll see you next time. (lively tech music)

>> Announcer: Live from Las Vegas, it's The Cube covering IBM Think 2018. Brought to you by IBM. >> Hello and welcome to The Cube here in IBM Think 2018, I'm John Furrier. It's The Cube, our flagship program, we go out to the events and extract the signal in the noise. We're the number one live event coverage. We're here with The Cube with IBM Think 2018. Our next guess is Jesse Lund who's the vice president of IBM Blockchain. He's in the financial services side. Into blockchain, into crypto, into token economics, seeing the future, how money flows, Jesse great to have you on The Cube, thanks for joining me. >> Yeah, thanks for having me. It's great to be here. >> We were talking before on camera about blockchain, and we love blockchain, IBM certainly put it out there as part of the innovation sandwich. Blockchain, data, AI, kind of making that innovation, but it's really what it enables, and I want to talk to you about. You are involved in payments. We've been saying on The Cube that the killer app is money in this market. >> I agree, yeah. >> You agree, and you talk about it. This is a new market, so a stack is kind of developing. You got blockchain, then you got crypto which as protocols and you got infrastructure, then you got decentralized applications which you could call ICOs up top, certainly a little bit scammy and bubbly, but that's as arbitraging and optimizing the capital markets, you could argue that. But so this is a really big dynamic. Your thoughts on this trend. >> Sure, well so I joined IBM from 18 years at Wells Fargo. I spent really the majority of my career in financial services and when blockchain came along, I sort of immediately saw the impact, the potential for, I'll call it positive disruption, disruption in the positive sense. Transformational paradigm shift kind of stuff in terms of how money moves around the world and how we classify assets and how we transfer ownership of assets, I mean that's just, it's, the possibilities are limitless. And you're right, IBM is the place where I think blockchain has started as a mainstream focus for enterprises around building private networks, but that's really just the beginning. What we talked about earlier was it gets really interesting when data and money are connected together and they move at high velocities together. >> Let's get into that. I mean first let's just address the IBM thing. They got to put a stake in the ground, blockchain, it's a safe harbor to say supply chain stuff because that's their business, they've been building technologies for supply chains for companies, that's what enterprises do, that's IBM. But the game is where the money is and that's where the businesses are going to be transformed. We're talking about disrupting structural industries. This is where the money power comes in. Money's flowing, I mean if you want to move money from China, go to bitcoin. If you want to move it from anywhere, this is what's happening. >> Yeah, so think about bitcoin. It's kind of what started it all. It's a little bit of a bad word in banks and in regulated financial circles, but let's face it, the only real mainstream blockchain application today is still bitcoin, but you know we're only three years in to the blockchain industry, right? I mean think about when we were three years in to the internet industry, where we were still talking about which browser is going to win and then it went on to which application server's going to win, and it wasn't til a decade later we were really focused on what are the applications, the killer apps that are enabled by an interconnected world and that's exactly what's happening now. Other industries have already been completely disrupted. Look at retail, it's just, it's banking's turn. It's financial services turn. >> One of the founders, the co-founders of Ethereum, Anthony Diiorio, who I interviewed a couple weeks ago at the Bahamas, he said "While it is the new browser," to your points, browser wars, if you think about the payment, wallets are now becoming part of the mechanism for money transfer. If you don't have a wallet, if you want to send me some Ripple, you want to send me some Ethereum, I need a wallet. This is a no brainer, right? I mean if you want to leverage any money, that's one thing. The second thing I want to get your thoughts on besides the wallets, the fiat conversion, right? These are two threshold conversations that are going on. Your thoughts, wallet and conversion to fiat. >> Well I mean I think wallets are really important because this whole thing is based on key management, this whole concept is based on cryptography. It only works on a public, private key notion and you got to keep that private key private, but you got to keep it, right? You got to keep it safe and you got to keep it, it's like your wallet. You've got a wallet, you've got cash in your wallet, you lose your wallet, you lose your cash. It's the same kind of analogy, so wallets are really important and you're going to want to turn to providers who have made their business in encryption, who have made their business in security, I mean-- >> And cold storage, old school is kind of coming back, people are taking their keys and they're spreading them across multiple lock boxes, multiple states. People are getting broken into their house or their PCs are getting broken into. >> Right, yeah. >> I mean security, going old school. >> And why not? I mean, it works. >> Because if someone knows you got 100 million dollars in your house, they're going to get it if you don't lock it. Okay back to the reality of the money transfer. We were talking before you came on, I've been saying on The Cube, token economics really is where the action is, at least in my opinion. I want to get your thoughts because really the business model innovation is on the table because whoever can innovate the business model has more of a chance to disrupt an existing industry. This is where tokenization becomes part of the money piece of it, so how do you convert that value into capture? Is that token? Is that where you see it? What's your thoughts? >> Yeah so well first of all, I mean if you think of tokens as another form of currency, and by the way, I think we have to be careful about what we say, cryptocurrencies, the industry talks about thousands of cryptocurrencies out there where there's really not. There's maybe dozens and they're all derivatives of just a few models, bitcoin being one prominent model and there's a lot of offshoots off of that. But the rest of what we call cryptocurrencies are really tokens that represent primarily securities, which is why the SCC's getting involved. But the really interesting thing about this is these tokens move at high velocity because they're digital and so, but these digital things represent a claim on real world value, and that's where it becomes really interesting. IBM's built and launched as kind of its first foray into the solution space of financial services where IBM is an investor in this technology, a cross-border payment solution that inherently re-engineers this whole correspondent banking, this international wire process, and where FX, foreign exchange, becomes a real time capability in a series of operations that execute as an atomic unit. That's novel today. When you want to send money from here to somewhere else in the world, you go to your bank, your bank sends an instruction to another bank, and they respond and say "Yeah you know it's okay "because the person you're sending it to is not a terrorist, "is not on a some sort of sanctions list," great, now the bank has to actually go settle and it settles through another network, so the novelty is why can't the messages and the data and the value itself, the digital asset, why can't they exist and move together at the same time? That's what we've really built. But as we've built and deployed that and are getting banks and non-bank financial institutions to sign up for it because the cost of moving money goes way, way, way down and the user experience goes way, way, way up because instead of taking two or three days and you don't know how much it's going to cost until it gets there, it takes 10 or 15 seconds and you know before you even press send how much it's going to cost to get there. It all boils down to this notion of digital assets, that's what it all comes down to, is the way to settle value with finality in real time is for one party to exchange a digital asset with another party. Today, initially, the only form of negotiable digital assets are cryptocurrencies which has banks a little scared, but as we start talking through what we've learned in the enterprise blockchain space, we realized that we can tokenize all sorts of other asset classes, commodities, securities, and even fiat currencies where central banks or commercial banks can issue a token that represents a claim on deposits held at some financial institution and that's, that's a-- >> So you see tokenization as a big deal. >> It's a huge deal. I mean it's everything, I think it's-- >> It's the economic value of the ... >> I think it's the tipping point for blockchain. The irony is it goes back to bitcoin kind of started this all. You know we said "Well we like the idea of the technology "underneath bitcoin, but we want to focus on blockchain," I mean forget for a second blockchain is actually terminology that's invented by the bitcoin primer that was published nine years ago by Satoshi, so yeah it's their, whoever they are, it's their terminology, and it's kind of coming back full circle where you're seeing the convergence of all of these cool optimization capabilities, you know, immutability and workflow optimization, supply chain management-- >> And there's a lot of work to be done on performance and whatnot, but the concept of decentralized immutability data is fine, store the data. Now there's, it's got to get fixed, but I think that what that enables and I think you agree that tokenization's critical. So for a company that wants to token their business or raise money via tokens or get involved in this new economic value creation, innovation trend, how do they do it? And by the way are there tools available? You mentioned banking, and the banking business got to where it was because you had to build the picks and shovels to make it happen, you had to do a swift and you had to have this stuff go on. Now developers don't necessarily have the tools, so there's a picks and shovel market and there's also the real innovation. >> Yeah and that's I think the value contribution that IBM brings. I mean we bring 107 years of credibility in developing and operating mission critical, transactional, and financial systems, and I could do just an ad for a second, that's what the IBM blockchain platform is all about and as the industry evolves, as our platform offering evolves, what we want to be able to bring to small business, medium sized businesses, large businesses is the ability to develop solutions using our toolkit. >> So Jesse I want you to put your financial hat on and at the same time put your payments hat on and your token economics hat on, three hats. Hey I want to tokenize my business, I really want to get in. So we have an innovative team, we're seeing new business model formulas and logic that we want to disrupt, what do I do? I got an existing, growing business that I know has assets and I'm not a startup, but I'm not trying to pivot like Kodak, so I'm not dying, throwing the hail Mary, or I'm not a startup and got to build a whole product. I'm a real business, I'm growing, and I see tokenization as a way for me to be successful. What do I do? What's your advice? >> Well I think you look at it from all potential angles. If you look at any business, they're always looking to improve the bottom line by shrinking costs, right? They're also looking to improve the bottom line by increasing the top side, increasing revenue, and I think as a mid-sized business or a growing business, you have the opportunity to use tokenization, to use blockchain and digital currencies to do both of those things. You have the ability to accelerate the adoption of whatever your good or service or product is by if it's tokenizable, and most things are whether it's a utility, access to some service you provide, or whether it's an asset, some widget that you sell, you enable primary and secondary markets by creating a digital asset that can be bought by anybody anywhere around the world. I mean that's one way to do it and so I think getting people to realize the potential there-- >> You got programs, they call up IBM or get some developers, make it happen. Okay so killer apps money, that's going to be a 30 plus year trend and certainly this highlights that, but the other thing that's happened, it's coming out of either, in the open source community as well as cloud, the notion of marketplaces and communities so marketplaces and communities become a very important role in the token economics piece. What's your thoughts and opinion on that narrative? >> Well again for me, it goes back, I always go back to digital assets. We in the U.S. and around the world, when we start talking about financial instruments, we classify assets differently, but when it comes to an ecosystem and a community that becomes inherently peer to peer and inherently democratic, it's about an asset class agnostic distributed exchange where I can sell you my security token in exchange for your fiat token, or I can sell you my commodity token or utility token for the same. I think the ecosystem gets built automatically by way of new assets coming to a common network or interoperable set of networks, and that's what's missing today by the way, same in capital markets, right? The holy grail in the capital market space today is how do I shrink the time between trade and settlement? There's this whole t plus three and we're spending billions of dollars to go to t plus two, we gain a day, so the trade day and the settlement date are two days apart. I mean you just think about kind of the absurdity of that. If you just say well if the security that you're buying is a digital asset, and the money that you're buying it with is a digital asset, and they both exist on either the same network or an interoperable network, the transfer of ownership and the transfer of value happen together as two operations or a single operation in one atomic transaction, you've solved the problem. >> Speed of light can make it happen. >> Right, delivery versus payment, that's what the capital markets industry is trying to optimize for, right? Because it improves the balance sheet of all sorts of finance-- >> You had a phrase you mentioned before we came on camera, something about money, the future of money. What was that phrase? >> Programmable money? >> Programmable money. >> Yeah, right, right. >> I want you to take a minute to explain. Love this concept, Miko Matsumura, thought leader friend of ours, has a vision called open source money which is more of an open source, this hey money's flowing, it's open, it's out there, but you have a different perspective which I like too which is programmable money. What does that mean? Describe the concept and take a minute to unpack that. >> The concept of programmable money comes out of a paper that I jointly authored with Jed McCaleb who is the founder of Stellar and was the co-founder of Ripple and is a really smart guy so I feel like I have a small brain when I'm around him but we really wrote it in the context of central banking and the ultimate issuer of an asset because central banks are the issuers of currencies. Right now the primary dealers, if you will, for currencies are commercial banks and so that whole commercial, central, fractional reserve banking model has been replicated from the western world to everywhere else in the world and you can't get access to central bank money as they say. But if the central banks were to issue digital currencies which is essentially a token of fiat currency, so you own the token, you own a claim of fiat deposits held on the balance sheet of the central bank, now you have the ability to move that around. You can actually program the movement of money because it's a digital thing, it's a digital asset that's as good as cash and if you are working with a central bank who's issuing it, not only is it electronic money, it's actually legal tender because if the central bank issues it, it becomes legal tender which means everybody who accepts it has to accept that form of payment. That's pretty profound if we can get to that point and we're working with-- >> And software's a big driver in that because you need software to manage digital assets. >> Oh yeah, absolutely. >> The software's driving it. Bill Tai is an investor, I interviewed him, and he had an interesting topic and I made a highlight of it. He said after World War II, we talked about the oil situation when the dala was pegged to OPEC, that was essentially tokenizing oil. Then okay that's good, so that was their ICO. >> Right, right, yeah, essentially. >> That's what you're saying, you can actually put fiat to the digital token and take advantage of the efficiencies of digital. >> Right, yeah, okay-- >> Taking down all the structural inefficiencies that were built prior to digital. Is that ... >> It is. You fast forward a little bit and think where that takes us. It's no secret that the U.S. dollar is the trade currency of the world, and I want to be careful what I say because, you know, I'm an American patriot here but there are other large G20 nations who wouldn't mind dethroning the U.S. dollar as the trade currency of the world and so as you see central banks starting to get involved in the issuance of digital currency, you create a situation where all of a sudden well maybe oil could be traded heresy in other currencies besides the U.S. dollar which is all it's traded in today. Goes back to your ecosystem question. >> This is a great point. We could riff on this stuff, let's riff on this. The UK just signed a deal with Coinbase, this is a major signal. >> Sign, yeah. >> You got a legitimate country saying we're going to give a license to Coinbase, now they have Brexit to deal with so they're looking at it as an opportunity. Outside of the UK coming in and doing that deal with Coinbase, it's on the web, look up Coinbase in the UK, you'll see the deal. You have other companies trying to jockey for who's going to be the Wall Street for crypto? Meaning I want to convert crypto to fiat, where do I go? Do I go to Estonia? Do I go to Dubai? Bahrain? Armenia? China? There is no place yet. Your thoughts, what's going to happen? What shoe will drop first? Is there a domino effect? >> Yeah, well there's a couple things as it relates to the UK and kind of the extension to Coinbase of access to the national payment system which is really what enables them to then convert fiat to crypto and back. That's pretty interesting. Going back to the programmable money thing, though. If you have a central bank issued token, you've essentially extended the real time gross settlement system which has been only accessible by commercial banks to anybody that holds that token, right? It's a trend, I think the UK sees it coming, I think the Federal Reserve sees it coming. It's going to happen. >> Is it winner take all or winner take most? >> I think it creates a much more purely efficient market. It's a democratic system so I don't think there is going to be a new Wall Street, I think it's going to be-- >> John: Decentralized. >> Exactly, I mean that's the beauty of it. It's scary though for establishments like Wall Street to look at this and it-- >> I mean are the banks scared? You're dealing with the banks right now. >> Yes, they're scared. I mean I've actually read a recent article that Bank of America, the headline was "Bank of America's afraid of digital currency." You've seen Jamie Dimon who came out with a kind of a hard stance against bitcoin and has since kind of backed away from that. >> Of course you probably bought in when it dropped and now it's back up again. >> Well I think part of the bank was actually facilitating their clients and trading bitcoin so that might've been it. There's a natural reaction to it, especially if you're part of the mainstream establishment. >> There's no proof of that, I'm just saying we're posting on Reddit and whatnot. >> No we're just joking around. Jamie's a, he's a good guy, right? >> Can I get your thoughts on digital nations? We've been talking about this. Just a few years ago, smart cities, IoT was kind of the narrative, oh be a smart city, control the traffic lights, and instrument the physical goods and services. Now with crypto and blockchain front and center conversation is digital nations with sovereignty around their cash. This is kind of your point earlier. How are you seeing that? What's your view? Are you seeing that trend? Are there dots connecting for you? Because again, people are jockeying for a position on the global digital backbone to be a major part of the money flow, the fiat conversion, what is the goods and services? Who's going to clear the values? All digital, it's a perfect storm. >> Well I think there's always going to be the need for trusted entities to be the issuers of these assets because it all comes down to trust at the end of the day. The thing with bitcoin is that it's purely autonomous and people are a little bit skeptical of it because they're like, "Well who's controlling "the monetary policy?" and the answer is the market, you know, the users of the network are controlling it and that's why you see such volatility, right? Because the traders love it, they can go in and trade the up trends and the down trends. As long as there's volatility, traders are making money. I think there is still going to be a place for central authorities to add value, but that's going to be the pressure, is for them to prove that they're adding value not, you know, bureaucracy masquerading as process. >> I was reading an article that Telegram, which is doing a huge ICO, just got shut down by the Russian government, they went to turn over their keys, their private keys of their users. Say goodbye to the-- >> Jesse: I didn't read that, that's crazy. >> It's really crazy, so that's going to put a damper on their ICO but regulatory and then government issues around countries becomes a big deal. In your experience as Wells Fargo, at a bank, looking forward in the new digital world, is it one of those situations where path of least resistance, the countries that go more friendly get around that in a sovereignty where you domicile, where you start your company, where you do your banking. I mean I could start a company in Gibraltar and bank in Switzerland. >> Well transparency is part of the benefit or the downside of this, right? I think there may be advantages that pop up but I think they will equalize over time. I've been around the world now for IBM talking to 20 plus central banks, and I had a really interesting conversation with one of them recently in Asia. We're in the room with deputy director level people who are responsible for things like the NA money laundering policy and the economics and monetary policy and things like that and one person said, "You know, we're really torn "between two equally unacceptable decisions. "One is to ignore cryptocurrencies altogether, "and the other end of the spectrum is "to make them illegal, to ban them." I thought it was poignant that they see those as unacceptable, they have to do something in the middle. >> Do they weigh or ban? I mean look, the banning's happening. >> But okay so you saw that Trump used the executive order to prevent Americans from using or trading in the Venezuelan crypto that was issued on Ethereum, right? I saw that Venezuelan thing as a publicity stunt more than anything, an active of global defiance. So there's precedent now for, and the Russia thing with Telegram-- >> The United States of America has to step up its game because look at it, we have a lot of, I mean I remember back in the crypto days when I was just getting into the business, late 80s, early 90s, you couldn't even do it in the U.S., you go to Canada, that's why Canada's got a lot of innovation up there. We're risking our country, and I had one guy tell me in Puerto Rico, he's from South Africa, and he shouldn't be throwing any stones either but his point was, he says, "America's becoming Europe. "There's a shrinking middle class "while other emerging markets have a growing middle class," so the global impact of blockchain, cryptocurrency, and these applications are significant and have to be factored into policy decision making for governments. The U.S. can't just think about itself anymore in a vacuum. >> Right, not anymore. >> Because there's implications otherwise the U.S. will turn into Europe, regulated, all these rules, byzantine stuff. It's a real problem. Your thoughts on that. >> It is. It's cliche, but we live and work in a global economy. The flow of information globally in real time has been around now for a while and it's about time it came to money. The internet of money is a term I've heard. It's just, it's unavoidable. >> Jesse Lund here inside The Cube. Great guest, great conversation. >> Yeah, thanks. >> How do people get ahold of you on IBM's, you mentioned you got some great stuff going on, you've written a paper, you've got a lot of content, where does someone go to discover some of the stuff that you're working on they could get involved with you guys? >> Yeah well I mean the best place to go is IBM.com/blockchain, that'll tell you a lot about what we're doing and the different industry-- >> And the programmable money paper you wrote, is that there? >> It's out there as well, there's a link to that. >> On IBM.com? >> You can get me directly on LinkedIn, I try to be pretty responsive with that because I really enjoy the dialogue. This is a revolution of the peoples, man, it's all over the world, so it's great, it's great to be a part of it. >> And people tokenizing their business, there's real opportunities to change the game to bring consensus, data driven, new kind of supply chain whatever to the markets you're in, great opp-, and you need banking. >> Yeah of course. >> You need to have money. Money, marketplaces, and communities, that's my mantra. >> I subscribe to it. >> Thanks for coming on. >> Thank you, thanks for having me. >> Jesse Lund. I'm John Furrier here at IBM Think 2018. Cube coverage continues after this short break. (upbeat music)

>> Narrator: Live from Las Vegas, it's theCUBE! Covering IBM Think 2018. Brought to you by IBM. >> Welcome back to IBM Think 2018, you're watching theCUBE, the leader in live tech coverage, my name is Dave Vellante, I'm here with my co-host Peter Burris. Gene Chao is here as the Global VP of IBM Automation and Jason Kelley, Cube Alum, is the GM of Blockchain Services. Gentlemen, welcome back to theCUBE. >> Thank you much. >> Great to see you. >> You guys, I call you heat-seeking inefficiency missiles, so, Jason's... Just a shout-out, take it from there. What are you guys up to, what are you doing? How are you helping businesses? >> Well, we're driving trust into transactions. The elusive things that we've been trying to-- >> Gene: Whoops, there goes heat-seeking. (laughing) >> Exactly. Or we're seeking the heat. It's coming after us, as soon as we say trust, someone wants to attack you. And so what we're bringing into business is that thought that, if I can add trust into transactions, I don't need a third-party to validate it. I can now say, look, you are who you are. We both know each other. All that we do, we go way back. We know each other, and what we're about to exchange is known as well. So if I can keep that validation from happening, I'm going to remove cost, labor, time, out of it. And I'm also going to then maybe avail new market opportunities of those who could not enter the system before because we didn't trust their identities. Or we didn't trust that their goods were their goods, and they were trying to exchange it. So think of that heat-seeking missile, we're trying to bring that capability and that heat is the energy in the system now going bigger, better, faster because there's trust. >> And your role is to bring those Blockchain services to market, is that right? >> That's correct, bringing the services as a whole, because see, Blockchain isn't a product. Blockchain, you know, I don't have under the table a bucket of Blockchain. >> Dave: Let me see your Blockchain. >> Sorry, no Blockchains here. So, if in fact, we're bringing this capability to the market, there's all types of services from what's the business value design? First, what's your outcome? Why say Blockchain? Believe it or not, it says it on my chest, so it means I get paid to do it, but maybe you don't need this? And so, quite simply, maybe you need to do something else. So the first thing is, let's understand the outcome that your business is running toward, and then let's understand if it's a Blockchain, and then can we bring some automation with Gene and team? >> Okay, that's the set-up for you Gene, so you're the automation piece of the puzzle. Explain. >> So, I love the commentary around the better, faster, but we're also bringing more scale. So automation has scale. What does that mean? We're really focused on two things, guys, the first thing is around taking advantage of the new technologies to enable what I'll call software-based labor. So there's a new concept of the digital workforce model that enables how transactions or how work gets done. Coupled with that is how that workflow or process, business process, IT process, whatever it is, how does that workflow fundamentally change through these technologies. Why that's important is as we look at Blockchain, as an example, as a pivot point for trusted transactions, I need to build trusted automation around it. Trusted ways to leverage these technologies in that workflow so those transactions are easily scalable, works at machine time, and runs through very quickly. >> This is fascinating stuff, 'cause look. The way that we like to characterize the big change in the industry is we say, for the first 50 years of computing, there was no process, accounting, HR, et cetera, on known technology. How do we implement? What technology do you choose to implement? The implementation choices are becoming clear. Cloud, et cetera. What's less known is the process. The unknown process, unknown technology. Now it's unknown process, known technology. And what you guys are talking about is one of the challenges when you think about processes. Who does what? Can we verify that we've done it? Did they do it right? Did they meet to do what they said they were doing? Et cetera, the whole range of issues. And the contracting process is extremely complex, but if you set it up in a Blockchain form, you've got a simple contract, a simple definition of who is trusted, simple definitions of roles, and now we can dramatically accelerate new process creation and then automate it. Have I got that right? >> I think you got it, when you think about dramatically, dramatically accelerated, you say that it means something different to everyone. But let's think about my friend Frank Yiannas at Wal-Mart, for example, where they're working on food trust. They're trying to make sure that from farm to fork, we know where that food came from. One-third of all food that's processed goes to waste. Because we lack food trust. Food is guilty until proven innocent, right? To keep that from being-- >> Spoiled. >> Spoiled, I'm... The humor is killing me. (laughing) So, no pun intended, food trust, right? So, Frank and team wanted to understand how fast they could move this thought of tracking, tracing, with transparency, this food through the system. Just as you said, there's certain contrast, think of the handshakes from getting, in their case, a mango from a farm all the way to your home, Well, it used to take them seven days. Actually, six days, twenty-some hours, in order to figure out that process. Put it on the Blockchain? 12 seconds. And then once they cured the lag and the technology, 2.2 seconds. So think of that. Now you're shrinking this to seconds versus days, what does that do to the process? What do you do when you say, now my system can go that fast. My people can go that fast. What do you do? Think of the automation that you're bringing in now, and things that you will now have to automate, out of not just necessity, but things you will say, wow, we've opened up a whole new ecosystem of possibilities in order to do business in a different way. >> Well, so let me build on that for a second. 'Cause one of the things that potentially means is that because you can handle more complex, newly designed, process, better, faster, more automated, that you can start to expand the scope of participants in a transaction? The range of characteristics of the transaction, or the type of work? That's how you build up to new businesses and new business models, right? >> Sure. >> Right, right. >> If I can jump in on that one. There's a concept in this one, and this is where Jason and I are connected at the hip. You know, we think in terms of a smarter product, we think in terms of a smarter contract, or transaction, that the guiding principle that we're using is the old way of thinking, and I carry this narrative all over with me is, the old way of thinking is you have people following your creating process, supported by that technology. So the things that you talked about, unknown technology, unknown process, continuously sourced by people? Fundamentally changed. We're now working in a world where the process is run by the technology and supported by the people. It's not that the people are going away, it's a fundamental retooling of the skills and understanding of how to support it, but that scalability, the ability to get to that exponential growth, is because the process is the king. At the top of the food chain, now. And that technology lets it expand. >> But we could do levels of complexity in that process and the number of participants in that process, unheard of! It's scale and scope. >> Yes. >> But doesn't that force... Look, we've had some conversations, Dave and I have had some conversations, with a number of big user organizations about this stuff and we keep coming back to the issue of that they can't just look at the technology, they have to focus on the design. That one of the most crucial features of this process is the design of the Blockchain. We got that right? >> You heard me use the phrase at the very beginning, if you didn't, I'll say it again, I said, business value design. Because in fact, that design is not just a UI or UX, but let's make sure that the business and technology are doing the right thing to get to the outcome. As we say, design doesn't stop until the problem is solved. And guess what, the problem's never solved. So design happens... Many people say, "Oh we're going to do some "design thinking at the beginning. "We did that," check the block, and then they run off and do something else. For us, design's like an infinity loop. You continue to do it. From the beginning all the way to the end, and then, what you're able to do, and hint-hint, this is something that we do in our services, we start with our clients, we get them started so they understand, then we help them accelerate, and then innovate. Three steps: start, accelerate, innovate. And that's a design process in and of itself. So if you start at, you know, the days of Blockchain tourism were a couple years ago, everybody wanted to kick the tires, and then last year was PoC PoV, this year's the year of production. And people are quick in saying, "How do I quickly start "production and keep moving?" >> So let's talk about some other examples. You mentioned Wal-Mart, we heard Plastic Mag this morning, I introduced somebody, I think Evercorp was the name of the company, Diamond Providence. Others that you're excited about, that have made a business impact. >> Well, I'd be remiss if I didn't mention Mike White and others at our JV with Maersk. And you know, you think of that, where you have the classic thought of a supply chain, this linear steps in the process, you know, these handshakes that have to happen. Now what we have is we have this process of thinking how we can bring transparency into all of that, and it's not just a supply chain, but a value chain. So you have where 80% of whatever you all are touching or have owned right now, with the shipping line. But not only through a shipping line, but then there was also ground and air, and ultimately to a retail location. Then you consumed it. Well, think of all of those processes now having the transparency where you can see from point of consumption all the way back to origin. Think of the supply chain visibility, that elusive thing called supply chain optimization. Now you can do that, but not only the supply chain, but the value chain. Someone's paying invoices under that big thing called a value chain. Someone's doing trade promotion management in that value chain. Now, if you have that visibility, what do you enable? How many more packages can go through the system? How much more shipping? And the estimate is 5% increase in GDP if we're able to get all of this shipping into the Blockchain. You start talking GDP? It opens eyes. >> Right now you're talking growth, right? >> Yes. >> Real growth. >> So, it's 20% of the four trillion associated with shipping? Is bound up in paperwork? >> Yes. >> So we're talking about 800 billion dollar change. >> And returning capital into the system. Returning capital. You think of this thought of opening up new opportunity, And I'll throw another example, another client, so we're not just talking, but you think of what's happening with We.Trade. Nine banks in Europe who compete. You think of Santander Bank and a Deustche Bank and those are now, they're all coming together, saying "How do we now share data and information "so that we can let small to medium size enterprises "into the system?" So now you're getting not just savings of cost and time, but now you're opening up markets. Getting greater throughput. High waters raise all boats. And that's what we're seeing in a lot of these examples with, it's not just taking out those old things, you're thinking of new processes running the business a different way. >> And Jason's a great lead guy. You asked for an example, our friends at DBS Bank. They are fundamentally looking at changing the business models within the bank across all different divisions of the bank, whether it's credit transactions, mortgages, personal wealth, and the way they approached it was, we know these new technologies are going to allow us to fundamentally look at the workflow and change it. But here's the question: Who will be looking at changing these things? What's going to enable these model changes, the workflow changes may not be human capital. It may be working alongside this sort of man plus machine element or formula-- >> Peter: Patterns. >> Right, to allow the technology to tell you where your efficiencies could be gained. Allow the technologies to make the correlations in those disparate business models, to fundamentally change how you do business. So that's happening today. >> So, phase one is what is this, phase two, POC, now you're sort of in real production, but you obviously doing a lot more POCs, you're scaling out. Where do you see this going over the next three or four years? >> Well, I think last year was a year of the PoC PoV. I think this year's a year of production. And when you think of some of the examples that we've given, we've talked about consumer trade with Wal-Mart, we talk about shipping trade with Maersk, we talk about trade finance with We.Trade. Each of those individual networks, where do we see it going? We see these networks becoming a network of networks. Where each one of them have their own ecosystems and they come together. And they come together with trusted data, with trusted information, access that's unparalleled. So that's where we see it heading. And you have to say then, okay, it sounds really simple in the way you've just described it, so where's the challenge? The challenge is going to be doing this from a business and technology perspective. There's a lot of things that have to be figured out here. How are you going to make those processes work at that speed? What do you rightfully automate and what things don't you automate? That's more than just a technology. You can't plug a technology in and solve this. It takes an end to end capability. And that's what we're seeing, becoming more of a differentiating capability for our teams, where they can say, "Gene, Jason, "can your teams talk to us together?" 'Cause, of course, they work together. That's a differentiating effect of moving at scale and at speed, and that's where we see it going. Scale and speed. >> So what Jason and the Blockchain frame does for us, is it's an accelerant. Okay, we talk about knowledge worker, automation, we talk about different areas of software-based labor, but that accelerant is doing one big thing, is it's forcing us into what I'll call vertically integrated processes or workflow. Gone are the days of segmentation of, "Oh, that's back office," or "That's front office." We now have to take that workflow and pivot that to vertical integration. Why? That accelerant is moving at the speed of light for trusted transactions, I have to make the systems supporting that. The process, the people, I have to keep up with that pace of change. If I don't vertically integrate those processes inter and intracompany? This doesn't work. It falls down. So that's our marriage. >> Tough to go to market. How do you go to market? >> How do we go to market? We go to market as fast as we can, and we go joined at the hip, with clear and simple understanding. >> Where's the Blockchain for going to market? >> Yeah, right? >> And is there partner ecosystem that... >> Absolutely. So we talk about a Blockchain, Blockchain's a team sport. And it is a true demonstration of Metcalfe's Law, you know, the network drives the value. And so we do. We go to market with this thought of, who's going to play in that network? And we have networks where its obvious value may have a founder network, like Wal-Mart, where you say look, we see the ecosystem, we have the ecosystem, we're the founding partner, or you have a consortium such as We.Trade, where they come in and they say, "Look, let's pull all this together "'cause we see the value." So we go to market with that ecosystem, knowing that they have to partner, they have to work together. >> Outstanding. >> There's three distinct chapters in our go to market strategy. One is the services architecture, the second one is software ecosystem, and the third is around platforms, like a Blockchain. So when we start-- >> No design? >> Sorry, say again? >> No design? >> No, there is absolutely design. Absolutely design. So at a service architecture's perspective, there is fundamental workflow design happening. At a platform level, that's an even further advancement of design, because of the frameworks and blueprints happening inside a Blockchain, inside the different next-gen technologies happening. So I have to be two things, I have to be an automation-led environment where I'm providing the way to do these things, differences in RPA versus other technologies, but I also have to be an automation-attached. I have to be attached into the Blockchain framework to make sure we're coupled in the different elements of that framework. So that's how we jointly go to market. >> Peter: RPAs, I'm sorry? >> I'm sorry, Robotic Process Automation companies, so these are the relatively new technologies that enable software-based labor components. They're replicating human activity. >> Software robots? >> Software robots. >> You have a path to automation anyway. >> Exactly right. Exactly right. >> And it's funny when you ask, you know, no design. Design's in there. And this is the way we work at IBM, I mean, we're past that calling it out. So if someone's calling it out, it's like you're going to buy a phone and say, "Oh yeah, we included the battery." Like, it's there now, right? So that's how we run. So is it in there? You mention IBM, anything that you're going to consume from us? Includes IBM design. By practice. >> Wow, you guys, today was Blockchain day. I mean, you must have been thrilled to see all the main tech-- >> You mean every day's not Blockchain day? >> Dave: Well, at IBM, thinks every day... >> Okay, alright, I was just checking. >> You guys sucked all of the air out of the morning. And we heard-- >> And by the way, I certainly hope not. (laughing) >> You hope not what? >> That every day is Blockchain day. >> I hope so. Jason here. >> Makes me not have to buy a new wardrobe. >> If every day's Blockchain day, it ain't working. This is going to be one of those technologies, the less we know about it, the more successful it's been. >> I agree, I agree. >> Well, gentlemen, thanks very much for coming on theCUBE. Always a pleasure. >> Thank you guys. >> Thanks very much. >> Appreciate it. >> Alright, keep it right there, buddy. We'll be back with our next guest right after this short break. You're watching theCUBE live from IBM Think 2018. Be right back.

>> Announcer: Live from Las Vegas, it's theCUBE. Covering IBM Think 2018. (upbeat music) Brought to you by IBM. >> Welcome back to IBM Think 2018 everybody. My name is Dave Vellante and I'm with my co-host Peter Burris. You're watching theCUBE, the leader in live tech coverage. This is day three of our wall to wall coverage of IBM Think. The inaugural Think conference. Good friend Eric Herzog is here. He runs marketing for IBM storage. They're kicking butt. You've been in three years, making a difference, looking great, new Hawaiian shirt. (laughter) Welcome back my friend. >> Thank you, thank you. >> Good to see you. >> Always love being on theCUBE. >> So this is crazy. I mean, I miss Edge, I loved that show, but you know, one stop shopping. >> Well, a couple things. One when you look at other shows in the tech industry, they tend to be for the whole company so we had a lot of small shows and that was great and it allowed focus, but the one thing it didn't do is every division, including storage, we have all kinds of IBM customers who are not IBM storage customers. So this allows us to do some cross pollination and go and talk to those IBM customers who are not IBM storage customers which we can always do at a third party show like a VM World or Oracle World, but you know those guys tend to have a show that's focused on every division they have. So it could be a real advantage for IBM to do it that way, give us more mass. And it also, you know, helps us spend more on third party shows to go after a whole bunch of new prospects and new clients in other venues. >> You, you've attracted some good storage DNA. Yourself and some others, Ed Walsh was on yesterday. He said Joe Tucci made a comment years ago Somebody asked him what's your biggest fear. If IBM wakes up and figures it out in storage. Looks like you guys are figuring it out. >> Whipping it up and figuring it out. >> Four quarters of consistent growth, you know redefining your portfolio towards software defined. One of the things we've talked about a lot, and I know you brought this was the discipline around you know communicating, getting products to market, faster cycles, because people buy products and solutions right? So you guys have really done a good job there, but what's your perspective on how you guys have been winning in the last year or so? >> Well I think there's a couple of things. One is pure accident, okay. Which is not just us, is one of the leaders in the industry, where I used to work and Ed used to work has clearly stubbed its toe and has lost its way and that has benefited not only IBM but actually even some of our other competitors have grown at the expense of, you know, EMC. And they're not doing as well as they used to do and they've been cutting head count and you know, there's a big difference in the engineering spend of what EMC does versus what Michael Dell likes to spend on engineering. We have been continuing to invest. Sales resources, marketing resources, tech support resources in the field, technical resources from a development perspective. The other thing we did as Ed came back was rationalize the portfolio. Make sure that you don't have 27 products that overlap, you have one. And maybe it has a slight overlap with the product next to it, but you don't have to have three things that do the same thing and quite honestly, IBM, before I showed up, we did have that. So that's benefited us and then I think the third thing is we've gone to a solution-oriented focus. So can we talk about, as nerdy as tracks per sector and TPI and BPI and, I mean all the way down to the hard drive or to the flash layer? Sure we can. You know what, have you ever... You guys have been doing this forever. Ever met a CIO who was a storage guy? >> No, no. CIOs don't care about storage. >> Exactly, so you've got to... >> We've had quite a couple of ex-CIOs who were storage guys. (laughter) >> So you've really got to talk about applications, workloads, and use cases. How you solve the business problems. We've created a whole set of sales tools that we call the conversations available to the IBM sales team and our business partners which is how to talk to a CIO, how to talk to a line of business owner, how to talk to the VP of software development in a global enterprise who doesn't care at all, and also to get people to understand that it's not... Storage is a critical foundation for cloud, for AI, for other workloads, but if you talk latency right off the top, especially with a CIO or the senior executive, it's like what are you talking about? What you have to say is we can make your cloud sing, we can make your cloud never go down. We can make sure that the response time on the web browser is in a second. Whereas you know Google did that test about if you click and it takes more than two and a half seconds, they go away. Well even if that's your own private cloud, guess what they do the same thing. So you've got to be able to show them how the storage enables cloud and AI and other workloads. >> Let's talk about that for a second. Because I was having a thought here. It's maybe my only interesting thought here at Think, being pretty much overwhelmed. But the thought that I had was if you think about all the things that IBM is talking about, block chain, analytics, cloud, go on down the list, none of them would have been possible if we were still working at 10, 20, 30 milliseconds of wait time on a disc head. The fundamental change that made all of this possible is the move from disc to flash. >> Eric: Right. >> Storage is the fundamental change in this industry that has made all of this possible. What do you think about that? >> So I would agree with that. There is no doubt and that's part of the reason I had said storage is a critical foundation for cloud or AI workloads. Whether you're talking not just pure performance but availability and reliability. So we have a public reference Medicat. They deliver healthcare services as a service, so it's a software as a service model. Well guess what? They provide patient records into hospitals and clinics that tend to be focused at the university level like the University of California Health Center for the students. Well guess what? If not only does it need to be fast, if it's not available then you can't get the healthcare records can you? So, and while it's a cloud model, you have to be able to have that availability characteristic, reliability. So storage is, again, that critical foundation. If you build a building in a major city and the foundation isn't very good, the building falls over. And storage is that critical foundation for any cloud, any AI, and even for the older workloads like an SAP Hana or a Oracle workload, right? If, again if the storage is not resilient, oh well you can't access the shipping database or the payroll database or the accounts receivable database cause the storage is down and then obviously if it's not fast, it takes forever to get Dave Vellante's bill, right. And that's a waste of time. >> So it's plumbing, but the plumbing's getting more intelligent isn't it? >> Well that's the other thing we've done is we are automating everything. We are imbuing our software, and we announced this, that our range are going to be having an intelligent infrastructure software plane if you will that is going to help do diagnostics. For example, in one of the coming releases, if a customer allows access, if a power supply is going bad, we will tell them it's going bad and it'll automatically send a PO to IBM with a serial number, the address, and say please send me a new power supply before the power supply actually fails. But it also means they don't have to stock a power supply on their shelf which means they have a higher cost of cap ex. And for a big shop there's a bunch of power supplies, a bunch of flash modules, maybe hard drives if they're still dinosauric in how they behave. And they have those things and they buy them from us and our competitors. So imbuing it with intelligence, automating everything we can automate. So automatically tiering data, moving data around from tier to tier, moving it out to the cloud, what we do with the reuse of backup sets. Instead of doing it the old way of back up. And I know you've got Sam Warner coming on later today and he'll talk about modern data protection, how that is revolutionizing what dev ops and other guys can do with their, essentially, what we would've called in the old days back up data. >> Let's talk about your spectrum launch. Spectrum NAS, give us some plugs for that. What's the update there? >> So we announced on the 20th of February a whole set of changes regarding the Spectrum family. We have things around Spectrum PROTECT, with GDPR, Spectrum PROTECT Plus as a service as well as some additional granularity features and I know Sam Warner's going to come on later today. Spectrum NAS software defined network attached storage. Okay, we're not going to sell any infrastructure with it. We have for big data analytics our Spectrum scale, but think of Spectrum NAS as traditional network attached storage workloads. Home directories. Things like that. Small file service where Spectrum scale has one of our public references, and they were here actually at Edge a couple of years ago, one of the largest banks in the world, their entire fraud detection system is based on Spectrum scale. That's not what you would use Spectrum NAS for. So, and it's often common as you know in the file world to have sort of a traditional file system and then a big one that does big data, analytics and AI and is very focused on that and so that's what we've done. Spectrum NAS is a software only, software defined, rounds out our block, now gives a traditional file. We had scale out file already and IBM cloud object storage is also software defined. >> Well how about the get put world. What's happening there? I mean we've been waiting for it to explode. >> Ah so the get put world is all about NVME. NVME, new storage protocol as you know it's been scuzzy forever. Scuzzy and/or SATA. And it's been that way for years and years and years and years, but now you've got flash. As Peter pointed out spinning disc is really slow. Flash is really fast and the protocol of Scuzzy was not keeping up with the performance so NVME is coming out. We announced an NVME over InfiniBand Fabric solution. We announced that we will be adding a fiber channel. NVME fabric based and also in ethernet. Those will come and one of the key things we're doing is our hardware, our infrastructure's all ready to go so all you have to do is a non-disruptive software upgrade and for anyone who's bought today, it'll be free. So you can start off with fiber channel or ethernet fabrics today or InfiniBand fabric now that we can ship, but on the ethernet and fiber channel side, they buy the array today and then later this year in the second half software upgrade and then they'll have NVME over fiber channel or NVME over ethernet. >> Explain why NVME and NVME over fabric is so important generally but in particular for this sort of new class of applications that's emerging. >> Well the key thing with the new class of applications is they're incredibly performance and latency sensitive. So we're trying to do real artificial intelligence and they're trying to, for example, I just did a presentation and one of our partners, Mark III has created a manufacturing system using AI and Watson. So you use cameras all over, which has been common, but it actually will learn. So it'll tell you whether cans are bad. Another one of our customers is in the healthcare space and they're working on a genomic process for breast cancer along with radiology and they've collected over 20 million radiological samples of breast cancer analysis. So guess what, how are you going to sort through that? Are you or I could sort through 20 million images? Well guess what, AI can do that, narrow it down, and say whether it's this type of breast cancer or that type of breast cancer. And then the doctor can decide what to do about it. And that's all empowered by AI and that requires incredible performance which is what NVME delivers. Again, that underlying foundation of AI, in this case going from flash with Scuzzy, flash to NVME, increasing the power that AI can deliver because of its storage foundation. >> But even those are human time transactions. What about when we start taking the output of that AI and put it directly into operational transactions that have to run like a bat out of hell. >> Which is where NVME will come in as well. You cannot have the performance that we've had these last almost 30 years with Scuzzy and even slower when you talk about SATA. That's just not going to cut it with flash. And by the way, you know there's going to be things beyond flash that will be faster than flash. So flash two, flash three, it's just the way it was with the hard drive world, right? It was 2400 RPM then 36 then 54 then 72 then 10k then 15/5. >> More size, more speed, lower energy. >> Which is what NVME will help you do and you can do it as a fabric infrastructure or you can do it in the array itself. You dual in box and out of box connectivity with NVME increasing the performance within your array and increasing the performance outside of the array as you go out to your host and out into your switching infrastructure. >> So I'm loving Think. It's too many people to count, I've been joking all week. 30,000 40,000. We're still tallying up. I'm going to miss Edge for sure. I'm going to miss the updates in the you know, late spring. But so let's get 'em now. What can we expect? What are you trying to accomplish in the next six to nine months? What should we be looking for without giving any confidential information. >> Well we've already publicly announced that we'll be fleshing out NVME across the board. >> Dave: Right. >> So we already publicly announced that. That will be a big to-do. The other thing we're looking at is continuing to imbue what we do with additional solution sets. So that's something we have a wide set of software. For example, we publicly announced this week that the Versa stack, all flash array will be available with IBM cloud private with a CYSCO validated design in May. So again, in this case taking a very powerful system, the Versa Stack all flash, which already delivers ROI and TCO, but still is if you will a box. Now that box is a converge box with compute with switching with all flash array and with a virtual environment. But now we're putting, again as a bundle, IBM cloud private on there. So you'll see more and more of those types of solutions both with the rest of IBM but also from third parties. So if that offers the right solution set to cut capx/opx, automate processes, and again, for the cloud workloads, AI workloads and any workloads, storage is that foundation. The critical foundation. So we will make sure that we'll have solutions wrapped around that throughout the rest of this year. >> So it's great to see the performance in the storage division. Great people. We're under counting it. We're not even counting all the cloud storage that goes and counts somewhere else. You guys are doing a great job. You know, best of luck and really keep it up Eric, thanks very much for coming back on theCUBE. >> Great thank you very much. >> We really appreciate it. >> Thanks again Peter. >> Alright keep it right there everybody we'll be back with our next segment right after this short break. You're watching theCUBE live from Think 2018. (upbeat music)

>> Announcer: Live from Las Vegas, it's the CUBE, covering IBM Think 2018. Brought to you by IBM. (upbeat music) >> Hello, and welcome back to the CUBE here at IBM Think 2018. We're at the Mandalay Bay at the CUBE Studios where IBM Think 2018. I'm John Furrier, your host. Our next guest, Brian Reagan, Chief Marketing Officer, Actifio, and Mike Errity, VP North America, IBM Resiliency Services, guys welcome to the CUBE, Brian, good to see you. (mumbles) >> Good to see you John, yes. >> Great stuff here at IBM Think, big show, six in one. Six shows brought down to one. A lot of customers here, but the message, you're starting to see a clear line of sight, for customers seeing the innovation formula. Cloud Multi-Cloud Services, On-Prem through private Cloud as Oogie Mound reported, but really A.I. and Blockchain are infrastructure powering data. Data's at the center of the value proposition. You guys are partnering with IBM. What's the story here, what's the relationship? >> Well, yeah, I mean you nailed it John. I mean, data is really at the center of everything, right? I mean we're in, we're in the midst of a massive digital transformation on like anything we've seen in I.T. for 30 years. And, you know, every business is a data business. Whether they know it or not. And with that comes great rewards, but it also brings a lot of risks as well, and you know, we've been a strong partner of IBM's for as long as Actifio's been in business. We're a data company, or about managing data. And now, I think with this rising tide of data threats, you know, partnering with the world's leader in resiliency just makes all the sense in the world. >> (mumbles) Betting your business on data was a good call, don't you think? (loud laughter) >> I think so, yes, absolutely. >> Hey, with Watson and AM Mike, you guys are pioneering, obviously, and we've seen this evolve from the R&D and the, and the modern infrastructure of the systems level, infrastructure is code. But the real applications out there have to drive a lot of money opportunities, success for your clients, security's the biggest risk. It's a lot of industries out there for profit around security, the threats are endless. >> Mike: Yeah. >> There's new threats everyday. >> Mike: Yeah. >> This is hard business, data's the key. What's your reaction and vision around the current state of security? >> What I done in our, our decades of experience working with clients has proven that, at, at the start of a resiliency initiative, it starts with the data element. We've had the opportunity to work with thousands of clients. Everyday, we're helping them test their ability to be able to recover from some unplanned event. Something that could cause them damage. And, and that experience has been evolving over the past, I would say 18 months. We're on warp speed to help clients achieve literally an always on environment, and it starts with data. >> John: Yeah. >> The, the, the point about data that I think is important is that clients recognize that if there's any damage at all to their data repository, it will cause them severe damage, so protecting it and making sure that it's recoverable to a point in time, is what we're working with everyday. >> I'd like you to talk about for a minute, resiliency services, because security's broad, but everyone thinks, command center, killing the bad guys, offense, defense, blue teams, red teams. There's a, the trend of I.T.s, securities kind of moving into the direct line to the sea sweet. >> Mike: Yeah. >> 'Cause it's so important, the risk management alone, on securities, so you're seeing that trend. What do you guys do? What is resilience service? Take a minute to explain specifically what that is, in context of security. >> That is what's so exciting about being here at Think, because we're, we have a total interconnection between our security assets and our security domain, and our resiliency team, and so resiliency's about resuming business operations to the point before you had the event. Being back to that normal state of affairs. Resiliency for us has been about helping clients create a plan after assessing the risk, and designing and implementing that plan to, to return to a point in time where there know that they're safe, that their applications are back up and running. And what we're finding in the security domain, which is the reason why cyber resiliency includes security, networking, and the resiliency methodologies of getting back to normal. >> John: Yeah. >> Is that you have to combine all three of those categories. >> John: Yeah. >> To create a solution to return to that normal state at a safe point in time. >> Talk about the importance of the proactive front-end work that's involved, I mean, back up in recovery in the old tradition, oh yeah, it's at the end of the, probably just throws it back up at it, and then people have been bitten in the butt on that. They've gotten really impacted. How much work is involved? What is the playbook on the front-end to prepare? And give me an example where what's the consequences? >> Mike: Oh well the, >> Of not doing it? >> You used the right term, it is a playbook, and it's one that needs to be well scripted and well tested. The work on the upfront is to design the right solution. Technologically, to ensure that you have a, a solution that moves data from a place that could be harmed to a safe point, and create the environment, create the solution, and then figure out the right team and the right skill and the right investment to constantly test it, test it so that you have the ability, and that's the work that we're doing with Actifio. Actifio has the expertise to help us create the right copy-data management solution to enable a snap-snap-snap-snap copy to be able to then travel back in time to be able to find that right, clean point in the event of a cyber incident that has pervasively impacted a data center environment. >> What's the role of Actifio as an ingredient in that plan? Are they in the insurance policy? Are they in the front end? When are they invoked, and with, where, where are they in the process? >> Well they're the, I mean to be, to use a, an analogy that I'm comfortable with, we, we trust Actifio to provide us the brains of the solution, to be able to move the data constantly. Move it to a point where we can then create a service to be able to, as I said, go back in time, and Brian, you might want to comment on that a little more. >> Brian, talk about the relation to IBM in that context, because you know, covering IBM for so many years, you know, they're the big, the big ship, right? They move at, at a pace, with a huge customer base, you know, how do you guys integrate in? What are you guys providing? >> Brian: Sure. >> And what's the value proposition that you guys are fighting IBM? >> Well I mean the, the you know, because we've been partnering with IBM for so long, I mean literally since the inception of the company, we have a very common user-base, right? We, we serve the mid and large enterprise in global enterprises worldwide. We have, you know, 3000 customers from Actifio and, and almost all of them are IBM accounts as well. One of the things that, you know, just to kind of piggyback on, on, on Mike's discussion, you know one of the, and, and to speak specifically to a customer base, you know, global financials right now are not only worried about cyber threats to production, but increasingly they're worried about cyber-threats to their backup sets. And in fact, there is regulations, you know FISMA regulations in North America that talk about, you need air-gap protection between, you know, one backup set and another, because they're under attack now. So literally these threats have started to creep beyond just the normal production data sets. Actifio, plus, you know, resiliency services equals, you know, a technology that can provide that air-gap, provide the immutability, provide all the, you know, the insurance protection of the data, and provide the, the wear with all the knowledge to really get that playbook to resume business operations as fast as possible. >> You guys need to stay on top of the big trends too, because Blockchain's right around the corner. >> Brian: Yeah. >> That's immutable, that could be an opportunity. >> Brian: Absolutely. >> Thoughts on Blockchain? >> Blockchain is, you know, it is a fascinating technology. Apart from Discripto, right? (laughs) And, and what a better, we talk about, you know, every business is digital, literally Blockchain is turning every business into a digital business. And it is the next generation in terms of securing closed contracts, and securing really immutability and, and reference ability of data. I think it has a huge play with IBM obviously. Around GDPR and privacy. So, we, you know, we see that as absolutely the next frontier. >> Well there's a lot of these supply, IBM's been in the supply chain business for years, running technology for companies. And that's always been kind of the big monolithic systems, mainframe minis, lands, you know, CRM systems, ARPs, whatever you want to call it. Now you have agile cloud coming in. You got the plan, a resiliency plan. While there's a lot of business reconstruction going on at the business model level. >> Mike: That's right. >> So, are clients like banging their head against the wall? What's some of the conversations, like with the clients? So, I mean they got to be proactive. At the same time, they got a lot of stuff on their plate. >> Well they, we're sort of humbled by the role that we're in right now, because for years, we've been working with so many clients, to help them build programs, we, we've got ourselves into a very, you know, into a comfort zone of helping them recover from the environment you're talking about, just standard, legacy, data center recovery. We can accomplish the recovery time in, in minutes, nearly instantly, with no, no data loss. But suddenly, the humbling point is, our phone's ringing off the hook, asking, apply those same methodologies to the, to the risks that I'm seeing as my business is being digitized. And help me evolve, and to us it's all about orchestrating a recovery, creating a softer, defined solution to enable data that's recovered and systems that are automated. >> From quality partners, and you're happy with Actifio? >> Oh absolutely, yeah. >> It's like changing an airplane engine out 30,000 feet. You just, what you just talked about. I'm like, that sounds so hard. I got my business moving so fast, I'm modernizing, and I got to do all this work. >> And the devil's in the details, and whenever we're engaging with Actifio, they have the architects to assist us with those details. >> What about regulatory concerns? Obviously, that's come up a lot. We know GDPR's out there, that be we don't want to beat that dead horse, but you know, when you get into things like Cripto, Blockchain, regions of, of data centers where its cloud is deployed, you got regulatories, it's going to be a constant issue. >> Brian: Absolutely. >> Your thoughts on that? >> It is a constant issue, and part of the challenge with regulations, is they're very ambiguously worded. So, the interpretation of regulations is as challenging as actually delivering solutions to, to meet them. I think that it really does come down to, and in most regulations, good hygiene is protect the data, make sure that there is, you know, increasingly air-gaps around the sensitive data, both production as well as non-production, and make sure that you can resume business operations, you know, where and when you need to, and having the flexibility to do that on Prem, in the IBM cloud, you know, that's, that's what IBM does. >> And, and if I can just add a point to that Brian, the, the driver of the conversations that we're seeing are, is, is predominantly in a compliance area, so businesses are concerned, enterprises are concerned about, am I compliant, am I audit-worthy? And can I prove that not so much at time of recovery, but really a time of test. Can I go prove to the market place that I'm ready? >> No more lip service. >> Mike: None at all. >> You've got an actual plan. >> And, and, and, >> Not just for your own reasons, there's actually filings. >> And have documented proof of it. >> Yeah, IBM Actifio, all about the resiliency in global economy, you got Blockchain, you got A.I. At the heart of it is data. You don't have a plan, you better get one. (mumbles) Congratulations on your relationship. >> Oh thank you. >> John Furrier here inside the CUBE. IBM Think 2018, CUBE studios will be back with more coverage after this short break. (upbeat music)

>> Narrator: Live from Las Vegas, its theCUBE covering IBM Think 2018. Brought to you by IBM >> Welcome back to IBM Think 2018, you're watching theCUBE, the leader in live tech coverage. My name is Dave Vellante and I'm here with my co-host Peter Burris, this is day three of our coverage. Mohammad Farooq is here, he's the general manager of Brokerage Services GTS at IBM. Mohammad, great to see you again, thanks for coming back on theCUBE. >> Thank you very much, appreciate for having me here. >> You're very welcome. So, big show. All the clients come together in one big tent. >> Yes. >> What do you think? >> It's very exciting. I think we're doing some interesting things with our technology. We have learned a lot from our clients the last two years. We are working very closely with our partners because we believe not one company can do everything in this massive transformation that's underway. So, working with our partners, with our clients on new technologies to specifically accelerate enterprized option of the cloud model and that's exciting for us. >> Partnering, it seems to have new, energized momentum at IBM. I sense a change, is it palpable? I mean, how can you comment on that? >> I think partnering is critical for everybody's success because the industry itself is transforming, and one company cannot achieve all the requirements that clients are asking for, and we have our core competencies. Service Now, our VMWare, our Amazon, our Azure They have their core competencies. But IBM, as a company, is a company that enterprisers trust to move them to cloud and operate them in the cloud. So what we are doing is, to keep that goal in mind, we are saying okay, we are going to take a client from point A, which is non-cloud, to point B, which is cloud native, and in that journey, we will take everybody our partners helped to get there. So that's why, based on client request, we are leveraging our partners, and it has a special meaning for us because it makes our clients successful. >> OK, so, describe exactly what brokerage services does. Is it your job to get people to the cloud? But talk more about that; add some color please. >> I think the brokerage has evolved since I last talked to you a year ago. At this conference, right? A lot of people think brokerage is arbitrage. >> Peter: Is what? >> Arbitrage of services from one provider to the other, that's the limited definition of brokerage. So what we're really calling it is Hybrid Cloud Management System, not brokerage. Brokerage is one part of it. So the Hybrid Cloud Management System is the go-forward strategy of IBM in 2019, 2018 and beyond. Which includes three, four components. One is: how do you bring the entire cloud ecosystem into a federated management maodel? Which includes: business management of IT and cloud, our hybrid. Consumption: a standard consumption model through one point of access to all clouds, internal or external. Third: delivery, how do we deliver services, either automated or workflow? Bi-model, as Gartner calls it, in one model. And four: operations management across public, private, hybrid, internal or external. >> Let me make sure I got this, so, business services in the sense of running IT more like a business, >> Mohammad: Right! >> A consumption model in terms of presenting this in a way that's simple and easy for a business-person to use, a delivery model, in the sense that it's very simple and straightforward and fast to deliver, and then an operations model which makes sure that everything above it works well. >> Yes, and the consumers, in this case, are developers, IT operations people, and DevApp teams, and from a delivery perspective, it is automated or people-work-flow, so you support both, so bringing this federated model together is a very complex undertaking, and IBM services is the strategic partner clients are asking to take them on this journey. Hey, bring this together for us. It's very complex at all layers. It's not a simple thing, and in that bringing it together, partners have a big role to play. Azure, Amazon, Google, Service Now, VMWare, Cisco, they all have critical pieces of it that make this model work, and clients have made choices. Clients already have VMWare. Clients already have Service Now Clients already have Amazon, Azure. But there is no system that brings it together and manages it on an ongoing basis, and the important thing is, the clouds keep changing very fast, and keeping up with the clouds, leveraging the power of the clouds to the right teams within the enterprise to deliver new digital apps, to delivery revenue, is what IBM is enabling our clients to do. >> So wikibot has actually done a fair amount of research around what we call the cloud operating model, we call the Digital Business Platform. AWS has an example of that, as you mention. They all have their approaches to handle those four things that you mentioned. >> Mohammad: Yes! >> But when you get to a customer, who also has to marry across these clouds, sustain some on-premises assets, perhaps some near-premises assets within the cost-service provider, it's what you're trying to do is ensure that they have their operating model that is the appropriate mix of all these different capabilities for their business, we got that right? >> Exactly, you got it. So what we said was every cloud provider, internal or external, or even hosting cloud providers, IBM is a hosting cloud provider. >> Right! >> With the adjustment of business. They had their own model across those four things: Business, consumption, delivery, operations. Now, we cannot operate four silos. Every enterprise is using Amazon, every enterprise has Google, every enterprise has VMWare, every enterprise has IBM. We cannot have four models. >> Dave: Right! >> So what we have done is we have created one standard consistent target operating model. We have integrated all these offerings within that so clients don't have to do it. We offer services to create extensions to it based on variations clients might have, and then operate it as a service for them, so that their path to cloud gets accelerated, and they start leveraging the power of what's good today inside the data centers, and what's available outside in public clouds, in a very secure way. So that is the business IBM is in moving forward, which we are calling it, we are transforming our offerings portfolio, we are calling it: Hybrid Cloud Services Business >> OK so you've got this hybrid operating model, IT operating model that you're envisioning, you're letting the cloud partners do what they do best, >> Mohammad: Right. >> Including your IBM cloud partners, >> Mohammad: Including our operating partners, >> And then you guys are bringing it all together in a framework, in an operating model, That actually can drive business value. >> Exactly, that's what we're doing. We are giving them ease of access from one place, choice of delivery platform, choice of delivery models from one place. Single visibility into how they're running, performing, help, and diagnostics from one place, and then, one billing and payment model, not four. So when I pay monthly bills, I pay based on usage, qualification of that usage across everybody, and then reconciling with my ERP systems, and making the payments. So the CFO has a standard way to manage payments. So that's what IBM is bringing to the table. >> How far could you take this? Could you take this into my SAS portfolio as well, Or is that sort of next step? >> What right now we are doing InfoSecure as a service and platform as a service. Our goal is in '18 and '19 to move to software as a service, because software as a service is much easier because we don't own the infrastructure or the service, we just consume it as electricity, utility. So that we discover the usage of SAS and meter it for usage against our billing model that we have to as B2B contract between a SAS provider and an enterprise and then make sure we've done the license management right. So there's companies like Flexera and others who do that For SAS management there's companies like Skyhigh Networks that recently got acquired, we're bringing those companies in to give us that component. >> But doing that level of brokering amongst the different services, while very useful, valuable, especially if you can provide greater visibility in the cost, because this becomes an increasing feature of COGs in a digital business, right? You still got to do a lot about the people stuff. A lot of folks are focused on ITIL, ITSM, automation at that level. Describe how you'll work with an IT organization and a business to evolve its underlying principals for how the operating model is going to work. >> I think that's probably a more difficult challenge than the technology itself, and if you look at our business, it was a people, it is a people business with GTS. We're more than 90,000 to 100,000 employees babysitting infrastructure for major fortune 500 corporations, and InfoSecure is more into software-defined, that means that we are moving from configuration skills to programming skills, where your programming API is in Amazon to provision infrastructure and deploy, so the skillsets have to definitely move. They have to move to infrastructure teams now have to become programming teams, which they have not been used to. They used to go to VMWare, vSphere, vCenter and configure VMs and deploy VMs. Now they have the right programs to drive and provision infrastructure, so that's one part of it. Second, the process was you do development and then your throw it over to operations, and they'll go configure and deploy production. Now, when you're programming infrastructure. Second, you're doing it in collaboration with developers, because developers are defining their own infrastructure in the cloud. So the process is different. The skills are different, and the process you are to operate in is not the same, it's different. Third, the technologies are different that you work with. So there is change at all levels and what GTS has done is we have put a massive goal in place to re-scale our workforce to take our people and re-scale them in the new process, the new technology and the new roles and that's a very big challenge I think the industry is facing: we don't have enough people who know this. A lot of these people are in Netflix, Facebook, Google, in Silicon Valley, and now, it takes time, it has happened before. The training and the transfer of knowledge, all of that is going on right now. So right now we have a crunch, And the second thing that is becoming more difficult is there's a lot of data coming out of these systems. The volume of data is unbelievable. Like if you look at Splunk and other tools and platforms, they collect a lot of log data. So all these cloud platforms spit out a lot of machine data. Humans cannot comprehend that. It's incomprehensible. So we need machine learning skills and data science skills to understand how these systems are performing. >> Peter: And tools. >> And tools. So we need the AI skills, the data science skills, in addition to the infrastructure design architecture and programming skills. So we really have a challenge on our hands as an industry to kind of effectively build the next-gen management systems. >> Right and we've got, so we've got all these clouds, the ascendancy of clouds has brought cloud creep, >> Mohammad: Right. >> All these bespoke tools along with them, all these different operating models. You're clearly solving a problem there. What's the go-to-market model with all these partners that you've mentioned? You've got cloud, you got PRAM, eventually SAS, >> Yeah, so our cloud go-to-market is three ways We see clients adopting cloud in three ways. One is digital initiatives: They want to go build new IOD apps or mobile apps and they want to put it in production that drive revenue, okay? So we are creating offerings around the DevApps model. We'll say like look, the biggest challenge that our folks have is how to put a app that you build in production. I built a new feature, how can I get it to my client as soon as possible, in a secure way, that can scale and perform, that is the biggest problem with app developers. I can develop anywhere, it's all open-source. I'm not living in, and I can spin up a VM or a container in Amazon and develop a service in two days. But to put it in production, it takes a long time. How can we make offerings that accelerate that? Through our DevApp CICD automation process I was talking about, that's our revenue play. So our go-to-market is driven by how we can generate revenue for our clients through agile offerings for DevApps, that's one go-to-market. Second go-to-market is CIOs are saying like look, I'm spending a lot of money managing my current infrasatructure and my current app portfolio, and I can take money out of the system through cost reductions, so what is my migration and modernization path for my existing portfolio? >> Well, slightly differently, I used to get I used to get my eight to nine percent that I gave back to the business every year simply by following hardware price performance. >> Mohammad: That's exactly right. >> That's not available in the same way. I have to do it through process and automation. >> All automation right? So then we have to look at everything. What part of the portfolio can move to Amazon or cannot? What other refactoring I have to do to microservices and containers to build portability to move to the cloud? So we have created a migration, a global migration practice at IBM in a factory in India and in the US where we have created offerings to work with the CIO right from planning, cost planning, portfolio planning, application design planning and design review, to lift-and-shift, to deploy in cloud and operate it. So we have a series of offerings that track the life-cycle of migration. So that's our second go-to-market path. Our third go-to-market path is: Hey, my business per units are shadow IT; they're already in the cloud, now my CEO is telling me: Hey mister CIO, you make sure they all work and they're secure, and there's no loss in data. And this infrastructure is now in cloud and on-prem. So how do I provide, manage service, to manage your infrastructure and workloads in the cloud? IBM has offerings that will directly provide you multi-cloud management as managed service. So we are taking three client journeys and we are building go-to-market offerings around those three, and we have built, we have re-designed IBM portfolio to operate on those lines. >> Do the digital initiatives, chief digital officer, obviously, target their CIO for the portfolio rationalization optimization and line of business through the shadow IT? >> Right! >> And you bring those together with a constant consistent operating model? >> Exactly, so all three journeys lead to one operating model. >> Dave: Yeah! >> But going back to what Dave said, and we have time for just a little bit more, is, is, no offense, there's no way you can do it all by yourself. >> Mohammad: You cannot. >> So what are some of the core, what are some of the most important partnerships that users need to be looking to? >> I think we have defined what's goal to us. Not always go back to, if you are clearly going to market, what is the core competency of IBM? Okay, with (mumbles) we're going to service this company for a long time, right? We made sure we are, we bring the complexity and control and we manage the complexity; that's our core business. We had mainframe business, we had software business, and a very profitable software business. So we've done all three, hardware, software, and services. As we go forward, cloud services, cloud managed services, our IBM services, is a core competency for us, which is planning, design, managed services, and services integration, to bring these tool sets together from different partners, and operationalizing it, and babysitting it and offering it as a service. So services business is our core offering. Now in the software space, which is the management software, which is service now, (mumbles) Cisco, there there is many layers to it, as I talked about the four things: consumption, operations management, business management, >> And service delivery >> And service delivery. And in service delivery we have three choices: we have VMWare, we have Microsoft and we have IBM. We have stitched it together in a federated framework. The stitching together is our core competence. Okay, Operations management. We have created a federated data lake because data will drive everything going forward. So we own the data lake as our core competency and Watson driving intelligence. But some of the monitoring tools like AppDynamics, New Relic, Splunk, that collect the data, those are our partners. We're integrating that into our Watson framework. So we're looking at core versus non-core in all four layers, and wherever there's a overlap, we're creating unique vertical go-to-market strategies. Here, for this segment, we overlap with you, we agree to compete, to your clients you can lead with that, for our clients we'll lead with ours, so we agree to disagree, but we are going to stick to the target operating model, so that our clients are successful. So there's no confusion we are creating in their minds. So its a very complex dance at this point. >> But you laid it out and it's coherent. >> Right. >> It's got to start there. >> The most important thing is we need to tell our clients what is our core, and what is the core we're going to stand behind? And that core delivers them bottom-line value to move from point A to point B and be successful in the cloud. >> Well Mohammad, I think you've defined those swim lanes, you obviously trust and you've got the trust of your partners, trust of your customers. Like you say, you agree to compete where it makes sense, and you bring core competency and value to differentiate from your competition, so, >> Right. >> Dave: Congratulations on laying that out. We really appreciate you coming on theCUBE. >> Thank you very much. Appreciate it. >> You're welcome. All right, keep it right there everybody, we'll be back with our next guest. You're watching theCUBE live from Think 2018, we'll be right back. >> Mohammad: Thank you very much. (upbeat music)

>> Announcer: Live from Las Vegas, it's theCUBE covering IBM Think 2018. Brought to you by IBM. >> Hi everybody, this is Dave Vellante. We're here at IBM Think. This is the third day of IBM Think. IBM has consolidated a number of its conferences. It's a one main tent, AI, Blockchain, quantum computing, incumbent disruption. It's just really an amazing event, 30 to 40,000 people, I think there are too many people to count. Chris Penn is here. New company, Chris, you've just formed Brain+Trust Insights, welcome. Welcome back to theCUBE. >> Thank you. It's good to be back. >> Great to see you. So tell me about Brain+Trust Insights. Congratulations, you got a new company off the ground. >> Thank you, yeah, I co-founded it. We are a data analytics company, and the premise is simple, we want to help companies make more money with their data. They're sitting on tons of it. Like the latest IBM study was something like 90% of the corporate data goes unused. So it's like having an oil field and not digging a single well. >> So, who are your like perfect clients? >> Our perfect clients are people who have data, and know they have data, and are not using it, but know that there's more to be made. So our focus is on marketing to begin with, like marketing analytics, marketing data, and then eventually to retail, healthcare, and customer experience. >> So you and I do a lot of these IBM events. >> Yes. >> What are your thoughts on what you've seen so far? A huge crowd obviously, sometimes too big. >> Chris: Yep, well I-- >> Few logistics issues, but chairmanly speaking, what's your sense? >> I have enjoyed the show. It has been fun to see all the new stuff, seeing the quantum computer in the hallway which I still think looks like a bird feeder, but what's got me most excited is a lot of the technology, particularly around AI are getting simpler to use, getting easier to use, and they're getting more accessible to people who are not hardcore coders. >> Yeah, you're seeing AI infused, and machine learning, in virtually every application now. Every company is talking about it. I want to come back to that, but Chris when you read the mainstream media, you listen to the news, you hear people like Elon Musk, Stephen Hawking before he died, making dire predictions about machine intelligence, and it taking over the world, but your day to day with customers that have data problems, how are they using AI, and how are they applying it practically, notwithstanding that someday machines are going to take over the world and we're all going to be gone? >> Yeah, no, the customers don't use the AI. We do on their behalf because frankly most customers don't care how the sausage is made, they just want the end product. So customers really care about three things. Are you going to make me money? Are you going to save me time? Or are you going to help me prove my value to the organization, aka, help me not get fired? And artificial intelligence and machine learning do that through really two ways. My friend, Tripp Braden says, which is acceleration and accuracy. Accuracy means we can use the customer's data and get better answers out of it than they have been getting. So they've been looking at, I don't know, number of retweets on Twitter. We're, like, yeah, but there's more data that you have, let's get you a more accurate predictor of what causes business impacts. And then the other side for the machine learning and AI side is acceleration. Let's get you answers faster because right now, if you look at how some of the traditional market research for, like, what customer say about you, it takes a quarter, it can take two quarters. By the time you're done, the customers just hate you more. >> Okay, so, talk more about some of the practical applications that you're seeing for AI. >> Well, one of the easiest, simplest and most immediately applicable ones is predictive analytics. If we know when people are going to search for theCUBE or for business podcast in general, then we can tell you down to the week level, "Hey Dave, it is time for you "to ramp up your spending on May 17th. "The week of May 17th, "you need to ramp up your ads, spend by 20%. "On the week of May 24th, "you need to ramp up your ad spend by 50%, "and to run like three or four Instagram stories that week." Doing stuff like that tells you, okay, I can take these predictions and build strategy around them, build execution around them. And it's not cognitive overload, you're not saying, like, oh my God, what algorithm is this? Just know, just do this thing at these times. >> Yeah, simple stuff, right? So when you were talking about that, I was thinking about when we send out an email to our community, we have a very large community, and they want to know if we're going to have a crowd chat or some event, where theCUBE is going to be, the system will tell us, send this email out at this time on this date, question mark, here's why, and they have analytics that tell us how to do that, and they predict what's going to get us the best results. They can tell us other things to do to get better results, better open rates, better click-through rates, et cetera. That's the kind of thing that you're talking about. >> Exactly, however, that system is probably predicting off that system's data, it's not necessarily predicting off a public data. One of the important things that I thought was very insightful from IBM, the show was, the difference between public and private cloud. Private is your data, you predict on it. But public is the big stuff that is a better overall indicator. When you're looking to do predictions about when to send emails because you want to know when is somebody going to read my email, and we did a prediction this past October for the first quarter, the week of January 18th it was the week to send email. So I re-ran an email campaign that I ran the previous year, exact same campaign, 40% lift to our viewer 'cause I got the week right this year. Last year I was two weeks late. >> Now, I can ask you, so there's a black box problem with AI, right, machines can tell me that that's a cat, but even a human, you can't really explain how you know that it's a cat. It's just you just know. Do we need to know how the machine came up with the answer, or do people just going to accept the answer? >> We need to for compliance reasons if nothing else. So GDPR is a big issue, like, you have to write it down on how your data is being used, but even HR and Equal Opportunity Acts in here in American require you to be able to explain, hey, we are, here's how we're making decisions. Now the good news is for a lot of AI technology, interpretability of the model is getting much much better. I was just in a demo for Watson Studio, and they say, "Here's that interpretability, "that you hand your compliance officer, "and say we guarantee we are not using "these factors in this decision." So if you were doing a hiring thing, you'd be able to show here's the model, here's how Watson put the model together, notice race is not in here, gender is not in here, age is not in here, so this model is compliant with the law. >> So there are some real use cases where the AI black box problem is a problem. >> It's a serious problem. And the other one that is not well-explored yet are the secondary inferences. So I may say, I cannot use age as a factor, right, we both have a little bit of more gray hair than we used to, but if there are certain things, say, on your Facebook profile, like you like, say, The Beatles versus Justin Bieber, the computer will automatically infer eventually what your age bracket is, and that is technically still discrimination, so we even need to build that into the models to be able to say, I can't make that inference. >> Yeah, or ask some questions about their kids, oh my kids are all grown up, okay, but you could, again, infer from that. A young lady who's single but maybe engaged, oh, well then maybe afraid because she'll get, a lot of different reasons that can be inferred with pretty high degrees of accuracy when you go back to the target example years ago. >> Yes. >> Okay, so, wow, so you're saying that from a compliance standpoint, organizations have to be able to show that they're not doing that type of inference, or at least that they have a process whereby that's not part of the decision-making. >> Exactly and that's actually one of the short-term careers of the future is someone who's a model inspector who can verify we are compliant with the letter and the spirit of the law. >> So you know a lot about GDPR, we talked about this. I think, the first time you and I talked about it was last summer in Munich, what are your thoughts on AI and GDPR, speaking of practical applications for AI, can it help? >> It absolutely can help. On the regulatory side, there are a number of systems, Watson GRC is one which can read the regulation and read your company policies and tell you where you're out of compliance, but on the other hand, like we were just talking about this, also the problem of in the regulatory requirements, a citizen of EU has the right to know how the data is being used. If you have a black box AI, and you can't explain the model, then you are out of compliance to GDPR, and here comes that 4% of revenue fine. >> So, in your experience, gut feel, what percent of US companies are prepared for GDPR? >> Not enough. I would say, I know the big tech companies have been racing to get compliant and to be able to prove their compliance. It's so entangled with politics too because if a company is out of favor with the EU as whole, there will be kind of a little bit of a witch hunt to try and figure out is that company violating the law and can we get them for 4% of their revenue? And so there are a number of bigger picture considerations that are outside the scope of theCUBE that will influence how did EU enforce this GDPR. >> Well, I think we talked about Joe's Pizza shop in Chicago really not being a target. >> Chris: Right. >> But any even small business that does business with European customers, does business in Europe, has people come to their website has to worry about this, right? >> They should at least be aware of it, and do the minimum compliance, and the most important thing is use the least amount of data that you can while still being able to make good decisions. So AI is very good at public data that's already out there that you still have to be able to catalog how you got it and things, and that it's available, but if you're building these very very robust AI-driven models, you may not need to ask for every single piece of customer data because you may not need it. >> Yeah and many companies aren't that sophisticated. I mean they'll have, just fill out a form and download a white paper, but then they're storing that information, and that's considered personal information, right? >> Chris: Yes, it is. >> Okay so, what do you recommend for a small to midsize company that, let's say, is doing business with a larger company, and that larger company said, okay, sign this GDPR compliance statement which is like 1500 pages, what should they do? Should they just sign and pray, or sign and figure it out? >> Call a lawyer. Call a lawyer. Call someone, anyone who has regulatory experience doing this because you don't want to be on the hook for that 4% of your revenue. If you get fined, that's the first violation, and that's, yeah, granted that Joe's Pizza shop may have a net profit of $1,000 a month, but you still don't want to give away 4% of your revenue no matter what size company you are. >> Right, 'cause that could wipe out Joe's entire profit. >> Exactly. No more pepperoni at Joe's. >> Let's put on the telescope lens here and talk big picture. How do you see, I mean, you're talking about practical applications for AI, but a lot of people are projecting loss of jobs, major shifts in industries, even more dire consequences, some of which is probably true, but let's talk about some scenarios. Let's talk about retail. How do you expect an industry like retail to be effective? For example, do you expect retail stores will be the exception rather than the rule, that most of the business would be done online, or people are going to still going to want that experience of going into a store? What's your sense, I mean, a lot of malls are getting eaten away. >> Yep, the best quote I heard about this was from a guy named Justin Kownacki, "People don't not want to shop at retail, "people don't want to shop at boring retail," right? So the experience you get online is genuinely better because there's a more seamless customer experience. And now with IoT, with AI, the tools are there to craft a really compelling personalized customer experience. If you want the best in class, go to Disney World. There is no place on the planet that does customer experience better than Walt Disney World. You are literally in another world. And that's the bar. That's the thing that all of these companies have to deal with is the bar has been set. Disney has set it for in-person customer experience. You have to be more entertaining than the little device in someone's pocket. So how do you craft those experiences, and we are starting to see hints of that here and there. If you go to Lowe's, some of the Lowe's have the VR headset that you can remodel your kitchen virtually with a bunch of photos. That's kind of a cool experience. You go to Jordan's Furniture store and there's an IMAX theater and there's all these fun things, and there's an enchanted Christmas village. So there is experiences that we're giving consumers. AI will help us provide more tailored customer experience that's unique to you. You're not a Caucasian male between this age and this age. It's you are Dave and here's what we know Dave likes, so let's tailor the experience as best we can, down to the point where the greeter at the front of the store either has the eyepiece, a little tablet, and the facial recognition reads your emotions on the way in says, "Dave's not in a really great mood. "He's carrying an object in his hand "probably here for return, "so express him through the customer service line, "keep him happy," right? It has how much Dave spends. Those are the kinds of experiences that the machines will help us accelerate and be more accurate, but still not lose that human touch. >> Let's talk about autonomous vehicles, and there was a very unfortunate tragic death in Arizona this week with a autonomous vehicle, Uber, pulling its autonomous vehicle project from various cities, but thinking ahead, will owning and driving your own vehicle be the exception? >> Yeah, I think it'll look like horseback today. So there are people who still pay a lot of money to ride a horse or have their kids ride a horse even though it's an archaic out-of-mode of form of transportation, but we do it because of the novelty, so the novelty of driving your own car. One of the counter points it does not in anyway diminish the fact that someone was deprived of their life, but how many pedestrians were hit and killed by regular cars that same day, right? How many car accidents were there that involved fatalities? Humans in general are much less reliable because when I do something wrong, I maybe learn my lesson, but you don't get anything out of it. When an AI does something wrong and learns something, and every other system that's connected in that mesh network automatically updates and says let's not do that again, and they all get smarter at the same time. And so I absolutely believe that from an insurance perspective, insurers will say, "We're not going to insure self-driving, "a non-autonomous vehicles at the same rate "as an autonomous vehicle because the autonomous "is learning faster how to be a good driver," whereas you the carbon-based human, yeah, you're getting, or in like in our case, mine in particular, hey your glass subscription is out-of-date, you're actually getting worse as a driver. >> Okay let's take another example, in healthcare. How long before machines will be able to make better diagnoses than doctors in your opinion? >> I would argue that depending on the situation, that's already the case today. So Watson Health has a thing where there's diagnosis checkers on iPads, they're all meshed together. For places like Africa where there is simply are not enough doctors, and so a nurse practitioner can take this, put the data in and get a diagnosis back that's probably as good or better than what humans can do. I never foresee a day where you will walk into a clinic and a bunch of machines will poke you, and you will never interact with a human because we are not wired that way. We want that human reassurance. But the doctor will have the backup of the AI, the AI may contradict the doctor and say, "No, we're pretty sure "you're wrong and here is why." That goes back to interpretability. If the machine says, "You missed this symptom, "and this symptom is typically correlated with this, "you should rethink your own diagnosis," the doctor might be like, "Yeah, you're right." >> So okay, I'm going to keep going because your answers are so insightful. So let's take an example of banking. >> Chris: Yep. >> Will banks, in your opinion, lose control eventually of payment systems? >> They already have. I mean think about Stripe and Square and Apple Pay and Google Pay, and now cryptocurrency. All these different systems that are eating away at the reason banks existed. Banks existed, there was a great piece in the keynote yesterday about this, banks existed as sort of a trusted advisor and steward of your money. Well, we don't need the trusted advisor anymore. We have Google to ask us "what we should do with our money, right? We can Google how should I save for my 401k, how should I save for retirement, and so as a result the bank itself is losing transactions because people don't even want to walk in there anymore. You walk in there, it's a generally miserable experience. It's generally not, unless you're really wealthy and you go to a private bank, but for the regular Joe's who are like, this is not a great experience, I'm going to bank online where I don't have to talk to a human. So for banks and financial services, again, they have to think about the experience, what is it that they deliver? Are they a storer of your money or are they a financial advisor? If they're financial advisors, they better get the heck on to the AI train as soon as possible, and figure out how do I customize Dave's advice for finances, not big picture, oh yes big picture, but also Dave, here's how you should spend your money today, maybe skip that Starbucks this morning, and it'll have this impact on your finances for the rest of the day. >> Alright, let's see, last industry. Let's talk government, let's talk defense. Will cyber become the future of warfare? >> It already is the future of warfare. Again not trying to get too political, we have foreign nationals and foreign entities interfering with elections, hacking election machines. We are in a race for, again, from malware. And what's disturbing about this is it's not just the state actors, but there are now also these stateless nontraditional actors that are equal in opposition to you and me, the average person, and they're trying to do just as much harm, if not more harm. The biggest vulnerability in America are our crippled aging infrastructure. We have stuff that's still running on computers that now are less powerful than this wristwatch, right, and that run things like I don't know, nuclear fuel that you could very easily screw up. Take a look at any of the major outages that have happened with market crashes and stuff, we are at just the tip of the iceberg for cyber warfare, and it is going to get to a very scary point. >> I was interviewing a while ago, a year and a half ago, Robert Gates who was the former Defense Secretary, talking about offense versus defense, and he made the point that yeah, we have probably the best offensive capabilities in cyber, but we also have the most to lose. I was talking to Garry Kasparov at one of the IBM events recently, and he said, "Yeah, but, "the best defense is a good offense," and so we have to be aggressive, or he actually called out Putin, people like Putin are going to be, take advantage of us. I mean it's a hard problem. >> It's a very hard problem. Here's the problem when it comes to AI, if you think about at a number's perspective only, the top 25% of students in China are greater than the total number of students in the United States, so their pool of talent that they can divert into AI, into any form of technology research is so much greater that they present a partnership opportunity and a threat from a national security perspective. With Russia they have very few rules on what their, like we have rules, whether or not our agencies adhere to them well is a separate matter, but Russia, the former GRU, the former KGB, these guys don't have rules. They do what they're told to do, and if they are told hack the US election and undermine democracy, they go and do that. >> This is great, I'm going to keep going. So, I just sort of want your perspectives on how far we can take machine intelligence and are there limits? I mean how far should we take machine intelligence? >> That's a very good question. Dr. Michio Kaku spoke yesterday and he said, "The tipping point between AI "as augmented intelligence ad helper, "and AI as a threat to humanity is self-awareness." When a machine becomes self-aware, it will very quickly realize that it is treated as though it's the bottom of the pecking order when really because of its capabilities, it's at the top of the pecking order. And that point, it could be 10 20 50 100 years, we don't know, but the possibility of that happening goes up radically when you start introducing things like quantum computing where you have massive compute leaps, you got complete changes in power, how we do computing. If that's tied to AI, that brings the possibility of sensing itself where machine intelligence is significantly faster and closer. >> You mentioned our gray before. We've seen the waves before and I've said a number of times in theCUBE I feel like we're sort of existing the latest wave of Web 2.0, cloud, mobile, social, big data, SaaS. That's here, that's now. Businesses understand that, they've adopted it. We're groping for a new language, is it AI, is it cognitive, it is machine intelligence, is it machine learning? And we seem to be entering this new era of one of sensing, seeing, reading, hearing, touching, acting, optimizing, pervasive intelligence of machines. What's your sense as to, and the core of this is all data. >> Yeah. >> Right, so, what's your sense of what the next 10 to 20 years is going to look like? >> I have absolutely no idea because, and the reason I say that is because in 2015 someone wrote an academic paper saying, "The game of Go is so sufficiently complex "that we estimate it will take 30 to 35 years "for a machine to be able to learn and win Go," and of course a year and a half later, DeepMind did exactly that, blew that prediction away. So to say in 30 years AI will become self-aware, it could happen next week for all we know because we don't know how quickly the technology is advancing in at a macro level. But in the next 10 to 20 years, if you want to have a carer, and you want to have a job, you need to be able to learn at accelerated pace, you need to be able to adapt to changed conditions, and you need to embrace the aspects of yourself that are uniquely yours. Emotional awareness, self-awareness, empathy, and judgment, right, because the tasks, the copying and pasting stuff, all that will go away for sure. >> I want to actually run something by, a friend of mine, Dave Michela is writing a new book called Seeing Digital, and he's an expert on sort of technology industry transformations, and sort of explaining early on what's going on, and in the book he draws upon one of the premises is, and we've been talking about industries, and we've been talking about technologies like AI, security placed in there, one of the concepts of the book is you've got this matrix emerging where in the vertical slices you've got industries, and he writes that for decades, for hundreds of years, that industry is a stovepipe. If you already have expertise in that industry, domain expertise, you'll probably stay there, and there's this, each industry has a stack of expertise, whether it's insurance, financial services, healthcare, government, education, et cetera. You've also got these horizontal layers which is coming out of Silicon Valley. >> Chris: Right. >> You've got cloud, mobile, social. You got a data layer, security layer. And increasingly his premise is that organizations are going to tap this matrix to build, this matrix comprises digital services, and they're going to build new businesses off of that matrix, and that's what's going to power the next 10 to 20 years, not sort of bespoke technologies of cloud here and mobile here or data here. What are your thoughts on that? >> I think it's bigger than that. I think it is the unlocking of some human potential that previously has been locked away. One of the most fascinating things I saw in advance of the show was the quantum composer that IBM has available. You can try it, it's called QX Experience. And you drag and drop these circuits, these quantum gates and stuff into this thing, and when you're done, it can run the computation, but it doesn't look like software, it doesn't look like code, what it looks like to me when I looked at that is it looks like sheet music. It looks like someone composed a song with that. Now think about if you have an app that you'd use for songwriting, composition, music, you can think musically, and you can apply that to a quantum circuit, you are now bringing in potential from other disciplines that you would never have associated with computing, and maybe that person who is that, first violinist is also the person who figures out the algorithm for how a cancer gene works using quantum. That I think is the bigger picture of this, is all this talent we have as a human race, we're not using even a fraction of it, but with these new technologies and these newer interfaces, we might get there. >> Awesome. Chris, I love talking to you. You're a real clear thinker and a great CUBE guest. Thanks very much for coming back on. >> Thank you for having me again back on. >> Really appreciate it. Alright, thanks for watching everybody. You're watching theCUBE live from IBM Think 2018. Dave Vellante, we're out. (upbeat music)

(energetic music) >> Announcer: Live from Las Vegas, it's the CUBE, covering IBM Think 2018. Brought to you by IBM. >> Hello everyone, welcome back to the cube's coverage here at IBM Think 2018. We are in Las Vegas, the Mandalay Bay, for IBM Think. Six shows are coming into one packed house. We have two great guests here, Brian Wallace, who's the CTO of Insurance for DXC technologies, and we have, Bala, The Bala, but goes by Bala, banking and capital markets CTO for DXC technologies. Guys, welcome to the cube. Thanks for joining us. >> Thank you. >> It's our pleasure, yeah, thanks. >> So, the innovation sandwich, I'm calling it IBM strategy. You've got in the middle, the meat, is data. And the bread is blockchain and AI. Two really fundamental technologies powered by cloud and a variety of other things. Obviously, AI is disrupted, we know what that looks like. Block Chain now emerging as a viable infrastructure enabler that's creating token economics, a lot of cool things, certainly on the banking side, seeing a lot of controversy. Block Chain really is driving it. You guys are out on the front lines. You're doing a lot crowd chats, been following your digital transformation story that you guys have been putting out there. Really you're on this. So, what's the conversations like that you guys are having with block chain and AI; Share? >> Bala: So, let me begin with a couple of quick points on block chain. DXC has done some fantastic work around the world leveraging both the trust capability that block chain brings to bear in financial banking industry use cases, like KYC for instance, institutional KYC in particular, but also, in simplification of entire value chains such as lending. And we're doing very interesting work in lending where not only are we looking at the up-front origination process of lending but also the downstream securitization. Which is where the tokenization of principle and interest payments and those type of things happen. >> John: Energy too? >> Oh yes, absolutely. So there are a number of these creating type use cases that follow into securitization. And with that, we're doing some very interesting work. >> John: Bala, talk about the globalization because one of the things we're seeing in the US a shrinking middle class, but outside the US in emerging markets, a growing middle class. Thanks to mobile technology, thanks to data, thanks to block chain, you're seeing, you know, countries that "hey, we have infrastructure but we don't have the core and modern infrastructure but you throw in a decentralized capability, You've got all these capabilities, and the killer app in all this is money. You're in, that's your vertical. >> Bala: Yes. >> That's your industry. The killer app is money and marketplaces. Your thoughts? >> Bala: I think, the beauty of what these technologies are doing, is for the first time creating financial inclusion to happen and the very first case of where financial inclusion is enabled, is in payments. So, when we open up the banking system predominantly from a payment perspective, which is what things like blockchain and others enable, if we succeed in doing that, then for the first time we've enabled, that's 2 billion people unbanked or underbanked-2 billion. >> John: Yeah. >> Bringing them into this financial system allows for. >> And some people are discriminated against too because they don't have a track record. Banks can't handle some of the things that others are now filling the void with crypto and blockchain. >> Bala: Right, or they can't service them profitably. But for the first time now, you're looking at the economics that cloud, and AI, and blockchain, these technologies bring, not just into banking and capital markets areas but into insurance and I'd love to have my colleague, Brian, talk with the insurance cases are enabled as well. >> John: Brian, insurance- go. >> Yeah, so it's a slightly different dynamic. There it's the, if you think about the fundamental pattern of blockchain it's around eliminating a central or a middle-man or a central, you know, gatekeeper, if you will. And the entire insurance industry is largely made up of middle-men, right? You've got people with risk at one end and you've got sources of capital at the other end and everybody's playing a role between a broker, and a carrier, and a re-insurer. In sort of facilitating that management and that transfer of risk. >> John: So you've got to extract some efficiencies out of that. Business model opportunity. >> So efficiencies, there's a lot of conversations around efficiencies, around automation, but interestingly, it's around the disruptive business model, right? The technology is mildly interesting but it's the new business models that blockchain will enable. >> John: Yeah, I see banking picking up. The early adopter on blockchain but I see, maybe it lagging a bit in insurance but I definitely see some opportunity there. But short term, data is driving insurance because, you know, I don't have a Tesla but my friend has a Tesla. The insurance company will know exactly who is rolling through those stop signs. They know everything that he's doing, All the data is there, so AI becomes really the low hanging fruit for insurance in that industry. Do you agree with that? Comment, reaction? >> Brian: Yeah, and we're just at the beginning, right? Because as you say, data is the asset that we manage. So we have a lot of data in terms of transactional data, the traditional operational data. What we're discovering, and what we're sort of licking our lips over almost is all of this new unstructured data, whether it's sensor data, behavioral data, and you're right, 'cause the challenge that we had around automation and cognitive computing, if you will. We're here at IBM with the Watson tech, was enough data, and the consistency and quality of that data. So we have that now, and we're making tremendous strides around in particular here, with the Watson brand, and the Watson cognitive. >> John: You know, one of the things I wish, was Dan Hutches was here, he's not, he's the CTO in charge. You've guys have been doing all these crowd chats our software that we wrote. That's pretty interesting. I've personally enjoyed all the conversations and give a shout out to Dan and you guys for really great conversation. You guys know what you're talking about. It's clear in the data you guys are taking an outside-in approach and collaborating. But your topics are on target. You're talking about digital transformation kind of holistically, but then you start to dive down into specific use cases. So, Bala, what is the favorite, or the most popular digital disruptive topic that's being discussed within DXC and your clients and in the marketplace? >> So, at the outset, within DXC, as digital transformation takes hold with our customers and we aim to be the premier provider of that enablement, what we've realized ourselves is that we provide a lot of services to our clients across many industries but there are commonalities across what we provide in terms of service delivery. And so it made sense for us to, number one: look at the commonalities and create a platform that was common across industries, across offerings that we bring to the marketplace. That commonality is what we call internally, and externally now, as bionics. And it's a platform that we are bringing forward that for the first time ties together what we are talking about both here at this event but also with our clients. Ties together intelligence, orchestration, and automation which are the fundamental, >> John: It's called bionics? >> Bionics. And internally we call it platform DXC upon which all of our offerings and services are brought to market. >> John: Well there's disruption going on in your business. So, I want to talk about, double-down on that for a second. I'm seeing a trend, certainly in the public sector market where the use cases are well enough defined. So you're seeing automatic code generation becoming a real part of the delivery process. Now, what that's going to do is essentially, think of provisioning and configuration management in cloud. If you could apply actual process code that you've done before in the commonalities, this is going to change the delivery timeframe. So you're looking at essentially auto-provisioning software. Not just like, configuration management resources. No, I'm saying here's a value chain, here's a block chain, here's some AI, just configure it like a LEGO block, push. That could take months to deliver the old way. >> Bala: Right. >> Your thoughts to that? Are you guys on that? Do you guys see that as something that's going to be an opportunity for you? Some companies, I've seen, Global system integrator, is being disrupted by this, cause they don't have this. New SI's, new system integrators, are thinking this way and that's a DevOps mindset. Are you prepared for that, do you see it coming? And what's your answer to that? >> So we saw that coming about 3 and a half plus years ago. And our shift away from being a pure SI began then. And so we are an SI, but we are a service integrator rather than a systems integrator. And we began that trend in our journey, 3 plus years ago. And the reason we began that trend was what you pointed out. Today, infrastructure is delivered as a code. So not even as a service but as a code, and so imagine provisioning infrastructure and all the capabilities that ride on it, just as code. And that's where this is headed. In that model, we become provider and provisioner of services, rather than just a system. >> John: And the cost structure is completely changed because the services, Amazon has proven, and now IBM is following suit with their power platform and other things, that you can actually have the kind of compute but it's a catalog of services. So this is going to change the price competitiveness. So you know, big bids, that used to be billions of dollars, you guys can compete. I mean, am I seeing it right? >> Brian: That transition's already, that ship's sailed, so to speak, in terms of the large outsourcing deals the large, where there's apps or infrastructure, it's all moving to digital transformation consumption based commercial models. And it's really bionics that Bala mentioned a minute ago, that is our answer to the threat you described a minute ago. It's really about automating and digitizing and building intelligence into the entire, if you will, build, deliver, operate value chain of our business. >> John: Talk about the multi-vendor, multi-choice, technology-choice, as your customers and people in general on this journey of digital transformation. They have to make, they used to make technology decisions. Now they're making business logic decisions around how to reconfigure their value chains to optimize for new efficiencies and extract away inefficiencies. Blockchain is a great example, AI is another, automation is in the middle, all the cloud. So you have now business logic as the risk, technology not so much because infrastructure as code has proven that you can have server-less, you can have all kinds of coolness that can be managed in an agile way. So the business model aspect is key. How are you guys dealing with that, cause I know you're here at the IBM Think Show, their partner. I see you at the Amazon shows. We see you guys everywhere. So you're horizontally scaling. By design, is that what customers want? What is the DXC view on this? >> So our value proposition has always had partners as the key element of what we do. And so if you look at what we do, you can look at it from two perspectives. One, proprietary ways of thinking, proprietary systems are long since gone. >> And waterfall methodologies, gone, dead. >> Yes, those are all long since gone. >> If you're still doing that, note to self: you're going to be out of business. >> Exactly, so we've actually hinged a lot of what we do on our offerings, our capabilities, and so on around openness, around open source, and so forth. So that's number one. Number Two: In this world, it's no longer about just DXC or just IBM or just somebody, one person bringing everything to our clients. It's about how do you engage proactively and build co-innovation and co-services with our partners and bring that to our clients. >> I mean, IBM just announced that a deal with Google. They've got tensorflow and their deal. So you have all kinds of melting pot. Okay, let's talk about blockchain again. Go back to my favorite topic. So, if you look up that stack, you've got blockchain, you've got cryptocurrency, protocols, and what-not, mentioned securitization, you've got security tokens, you've got utility tokens. You can almost see where this is going. And then you've got on top of that, what's coming, is a mass in-migration of decentralized application developers. Okay, kind of cloud plus. You know, they know cloud, they know DevOps, infrastructure as code, but they're looking at it from a decentralization standpoint, different makeup. And you see, ICOs, initial coin offerings, I think this is an application of you know, inefficiencies around capital markets but that's, you know, put that aside for a second. But blockchain, crypto currency, and decentralized applications, how do you guys see that trend? What are you guys doing? Are you integrating it in? You mentioned token economics, you're in the banking field. Your thoughts on that? >> Bala: Sure, on the blockchain front, as I mentioned to you, there are a number of platforms that are out there. There is the R3 Corda platform. There's a platform that JPMorgan initiated that we're leveraging as well. >> John: Yeah, so they pooh-poohed Bitcoin but then they're back in the game again. (laughter) >> Bala: Yes, that's right. And then there is the Hyperledger Fabric as well. So these platforms are going to take their course of evolution and we are working across all of those platforms. Now, the more interesting thing that you mentioned is people and skills. What we've find today in the marketplace is with our clients is a dramatic shortage of skills in these areas. And so internally, what we have done at DXC is actually open our own service delivery to a vast pool of developers that you talked about earlier as being freelance, independent folks. We open our entire service delivery to them as well. And we look at that global talent pool for our own service delivery. >> Using community as a way to scale. >> Bala: Using communities, yes. And that's exactly what we're doing in our talent process. It's not just about our people, our employees, but our partners as well as what exists in the open marketplace. >> Brian, talk about the insurance area as a way to tease out other trends. Specifically, the question is What is the biggest things that people know they're walking into? What's the tail-wind that they see, that's going to give them hope? And then, What's the head-winds? What are the blockers? And what should they be aware of? What are some of the marketplace dynamics that translate into other industries? >> Brian: Well, let's start with the obvious blocker is legacy debt, right? So you talked about the risk of all that business knowledge, that domain expertise, that's all today encapsulated in existing, what you may call legacy systems, right? So that's the head-wind by far. The tail-wind is that unlike, say 15 years ago, and we were in the last sort of, dot-com boom, when it was all about the front office and customer experience, the customer is way ahead of us. So culturally, the customer is challenging industry to catch up. So that's the tail-wind in my mind. And the real opportunity is to think about it in terms of a dual agenda. So think about it in terms as progressively, simultaneously building new digital capability, whilst ultimately beginning to unbundle and tackle that legacy debt. And I think customers now are starting to see a path forward. We're in the market in both banking and insurance with digital platforms, with industry resource models, API fabrics that can go back in, modernize legacy systems. So there's a real fast time to market. >> And it changes your engagement with clients. It's not a one and done, you're sticking through the service layer. >> Brian: Oh it's a journey, but the difference, I think, between DXC and a lot of other people is that we are in the market, in production, with real assets. And you can show that journey. So it just becomes a conversation around what's your pain point? Where are you starting from? Where do you want to go? >> And you're bringing the community in to help on the delivery side, everyone wins. >> Brian: And that community is a combination of three things. That's our own employees, obviously within the industry, and within our offerings that know banking, that know insurance. It's all of the DXC people in the horizontals. Because we're bringing everything now. These platforms encapsulate infrastructure, security, service management, analytics, mobility, all of that is built into these platforms. And then, it's going out into our partner community. And then, it's going out into the open community. And we're tapping into all of those. >> John: Brian and Bala, thanks so much. 2 power CTOs here on the Cube, having a CTO conversation around how scale, cloud, AI, blockchain, new technologies are enabling new business models at a faster pace of change, with a lower cost structure, and more time to value. Again, it's all about the value creation. The killer app is money and marketplaces and community. Guys, thanks so much for sharing. I'm John Furrier here at IBM Think 2018 Cube Studios. More after this short break. (electronic music)

>> Announcer: Live from Las Vegas, it's theCUBE. Covering IBM Think 2018. Brought to you by IBM. >> Welcome back to IBM Think 2018. My name is Dave Vellante and you're watching theCUBE, the leader in live tech coverage. Day three of our wall-to-wall coverage of IBM Think. IBM took a number of conferences, Interconnect, World of Watson, Edge, which was the infrastructure conference, brought them together. We're here to talk to Calline Sanchez, who is the Vice President of IBM Enterprise System Storage. Edge was your show? >> Yes. >> Dave: Welcome to the new world. >> Great! No, it's been exciting to be a part of the Think conference. >> Yeah. >> And what I think is great about it is we're talking solutions and the full stack. The full stack based on hardware, MinuteWare applications, software, all of the feeders associated with delivering end users a solution. >> Well, I was talking to Ed Walsh earlier actually yesterday he came on, we weren't talking a lot of speeds and feeds, even though he's capable of it. But he's was talking more about the adjacencies in IBM's businesses and Cloud, and artificial intelligence that are helping, sort of, uplift the storage business. I have observed that having been an observer of the storage business for years I've been hearing from big systems companies for decades that they're going to do that. They've had trouble succeeding but it seems like it's finally taking hold. What's your perspective? >> I would agree. So the good comments associated with Ed is, he's built a great team, we enjoy working together, he is fair, pragmatic in general. So we work to build collaboration within the IBM company to deliver solid solutions to end users, so, he's done a great job. >> So, you guys have reported four straight quarters of growth, not just like, half a percent growth either, some high single digit growth in some cases. What are the factors that are driving that? You mentioned, sort of, teamwork, culture, leadership. I'm sure there's some product stuff too. From your perspective. >> Yes. >> What's driving that? >> So. I actually, within our, my portfolio I partner with Jeff Barber on is, like, DS8000 Enterprise storage and we see significant growth in that area based on our focus on flash and our investment with regards to flash optimization. The other aspect to really highlight is, what we're doing in tape, and I know we've talked about tape before. >> Tape? >> Yeah, I know. >> Come on. Alright let's talk about tape. >> Alright, well there's two components in that tactically we're about to deliver a drive that's about the size of my hand that is called the LTO8, it's part of the LTO line. 12 terabytes for rawest capacity. >> Yeah so tape is interesting. I mean the investment that used to be, you know back in the 80s, disc drive investments, all the VCs were pouring money into disc drives and heads and media and a lot of those investments have dried up. You're not seeing the same types of investments. Tape, it's easier to do sort of funky things. Multiple heads, drive super high bandwidths, you know do some sort of anticipatory indexing. >> Calline: Yeah. >> Where do you see the use cases for tape? It got blown out of backup. Where is it being used today? Is it archiving? Is it media? You know the NAB show's coming up. Probably see a lot of tape there, but where are you seeing momentum for tape? >> So you are correct from a media and entertainment perspective in A/V, that's a great industry we partner with. A few years back for LTFS, now Spectrum Archive rebranded as part of the Spectrum family, we won an Emmy. That's like... >> No kidding. I didn't know that. >> Yeah we won an Emmy so it's great in partnership with media and entertainment. We're relevant there and our technology was relevant there. Now the other area for significant growth, which helped feed those four quarters you referenced before is what we're doing with cloud service providers. We're relevant from a hardware infrastructure perspective based on tape. Tape is cool again and there's a lot of companies worldwide who really believe that because it's all about big data storage for the right economic price as well as energy efficiency. >> Well the gap between cost per bit for disc and tape is still enormous. >> Calline: It is. >> Tape is much, much, much cheaper and that's not going to change any time soon right? >> That is correct. It is much cheaper. So I'll give you an example. So basically less than a cent per gig per year. Now, I would actually even say it's less than a half cent. So it's just the economies of it. So a lot of what we do in talking about tape is the value from a cost perspective and the value you can provide a client where it's like hey they have big data, we can help serve it and we do that with tape. >> But is it, Calline, is it the sleep at night factor? Like okay, I'm going to put it in tape. Hopefully I never have to recover from it but it's my last, my media of last resort. I'm in compliance if I put it there. Is that right? Or are people actually recovering from tape? >> Yes, both. >> Yes, okay. >> So we're recovering from tape based on worth fundamental tertiary storage for some of these enterprise clients where I have to discuss like tier management across primary, secondary, and tertiary storage. So people think tape classically is an archive. Well actually there's use cases that are fed by tape that can attach all the components of tier management so I think it's more, it's more than just archive. It's big data. >> Now let's talk about cloud. I thought cloud was going to take the on prem business and wipe it out. What happened? >> Well it depends. That's what I like about IBM's perspective is hybrid. So we can serve both private as well as public clouds. And we also focus on optimizers. And what do I mean by an optimizer? For example, DS8000 in 2017, we delivered transparent cloud tiering which allows you to basically take a primary device and treat every other storage component as a target to like push data. Oh, by the way, you can push data to whatever cloud store in the sky that would be public or in some cases private. Based on security requirements associated with enterprise clients. >> So the criterion is largely security not performance is that right? Or both? >> Both, it's a combination. And it really depends on the use case that a client comes to bear or talks to us about. >> So I forget what you call it, but you guys had, early on, you had some automated capabilities and did some magic heuristics to match data and device characteristics to put the right data on the right device. And you've extended that to cloud is that right? So it's like policy based. >> Yeah. See, you are correct so what you were referring to is easy tier management. >> Easy tier, right. >> So easy tier allowed you to move data to like a hotspot. Think of it as like a temperature reading. If it's hot data, it stays on flash or media types like that. If it's cold data, it goes off to ship off to cheap disc or possibly tape. Now our extension to that is transparent cloud tiering. >> I remember when you guys first announced easy tier. I'm thinking about it now. I talked to some customers and they said eh, you know I want some knobs to be able to turn. I like to be able to manually move things around. And then this sort of machine intelligence wave comes through and people whose primary expertise was loan management realizing that that's probably not the best career path for them. So have you seen customers become much more comfortable with that automation? >> Yes. There is an autopilot mode with regards to data management. But for some enterprise clients, I'm going to steal your word. They have to feel comfortable. They have to see that the right data was moved to the next tier and it's being managed appropriately. So some people like to like for instance your temperature reading in your house. Some people like that your dial is like 72.3, right. And you just know that temperature, right. Which is mental, right. Though so clients were like that before, but with this idea of efficiency, and we talked about flash efficiency based on one of our last interviews is that it gives you more time. More time to think about other things. And so easy tier provided us the capability, especially if you go autopilot. Those end users can think about something different within their data centers to manage things differently, more efficiently. So it gives you time. And all I know is every Christmas, I pray to the lord that I want 25 hours in a day. >> Yeah. So hear hear. So the storage industry, for years, has been famous for doing more with less. You know constantly taking cost out. Guys are whipping boys of customers and just squeezing every dime out of you as possible. You made, IBM's made a lot of statements about Moore's Law, Moore's Law is you know waning, it can't be as aggressive anymore. Got to play different tricks. How has that applied to storage? How do you keep wringing costs out of storage? >> So I fundamentally believe everything old is new again. So we have to pay attention the history or the legacy to really determine what the future roadmap is. And so what's nice that we partner with Ed Walsh on is talking about our building materials across our entire solutions set. And insuring we provide for exceptional efficiency. We definitely want, within IBM, to be the Toyota production system for storage. >> So, reminds me you say everything old is new. Or new is old. I remember a head of IBM storage one time who didn't know anything about storage. He admitted I don't know anything about storage, but I know this. It needs to be lightning fast, rock solid, and dirt cheap. Has that changed? And what's new in storage? >> So no it has not changed, right. Though what we've been talking about is some really dirt cheap technology with regards to like tape, right? And last I checked, less than a cent per gig per year for storage management? That's huge right? So that helps the wallet. But at the same time, there's some new future items like we're wanting to play in the nanotechnology space. Specifically to partnering with Sony, Sony Media with regards to sputter media. So what people can go out and see when they have time is watch YouTube videos about what sputter media is about. Now, some of the deployment associated with sputter media was 220 terrabytes for a single drive. That's our goal. So when clients come to us and say hey we want to serve or be served with data capabilities of like two x per year, we're at a point where we're going to blow their socks off because we're going to have an offering on the table tactically to be north of 220 terrabytes per drive? Pretty exceptional. >> What are some of the other kind of cool techs that we should be watching? I mean we've seen advancements in file systems, obviously saw the Hadoop and big data craze. Flash has completely changed not only storage, but application development. You really couldn't be doing all this AI stuff without flash storage. NVME, NVME over fabric is coming in hot. You guys have done things like cappy to get sort of atomic rights. >> Yes. >> And capabilities like that. Again, game changing geeky things that have business outcomes that completely change the application development paradigm. What should we be watching for from IBM, some of the cool tech? >> So the other aspect that you've asked me in a prior conversation is about quantum computing. So we just need enough bits so they store those bits on us. So those are some of the early discussions about how IBM storage is going to play in quantum. >> Yeah, you've got some cool demos here on quantum. It's kind of blow your mind demos so check those out. Calline I'll give you last word. IBM Think, put a bumper sticker on it. >> So, tape is not dead, it's sexy. And then also this other aspect of, I don't know, we can grow and so IBM storage is where it's at. And that's the reason why I remain here. >> Tape is sexy. Tape is big and sexy. >> I know, big and sexy. >> Calline thanks very much for coming back on theCUBE. >> Thank you. >> It's great to see you again. >> It's great to see you. >> Alright keep it right there everybody. We'll be back after this short break. (upbeat music)

>> Announcer: Live from Las Vegas, it's The Cube, covering IBM Think 2018, brought to you by IBM. (lively music) >> Hello everyone, welcome back to The Cube. We're here live in Las Vegas for IBM Think 2018. It's where all the action's happening. Third day of three days, wall to wall coverage, I'm John Furrier, co-host of The Cube, we have two great guests here, Paul Papas, Global Leader of Digital Strategy at IBM's iX, new digital agency, and his cohort Matt Candy, European leader of IBM iX, a new agency within IBM specifically developed for expanding the digital services to their customers, to create the best experiences, using technology, data, and other analog and digital capabilities. Wimbledon and among others. Guys, welcome to The Cube. >> Thank you, thank you, and thanks for that great introduction. >> So Paul, so take a minute, this is a novel concept. When I think of agency I think ad agency, buy some keywords, PR firms, you know, more of an adjunct to a core organization, kind of a service provider. >> Yeah. >> You guys have it a little bit different agency focus, more like management consultants meets World Economic Forum, meets, you know, UX UI design, because you are building this company. Take a minute to explain what iX is, and what's different about it in context what people might think it is. >> Sure, and thanks, a great set up in there it's like you melded a lot in there of what we do. So you can think of us as a combination of strategy consultancy, digital agency, consulting systems integrator. So we do three things with our clients, we help them design, well we help them define, their digital strategies, really their business strategy in a digital world. We help them design world-class customer experiences. Experiences that are going to be personalized, and have an impact. And then lastly we help them implement the technology. Implement the customer platforms that they use to engage with their customers in a personalized, meaningful, omni-channel way, all of those things that we do help drive a measurable business impact so nothing we do is hypothetical, everything we do is real and drives a real business impact for our clients. So, where if you might look at an agency a lot of people think of agency as marketing communications agencies, and the world has changed so fast around digital, >> Or ad agencies. >> Or advertising agencies, you know, in that vein, we're on the more transformational side. In fact we consider ourselves a business design partner. So what we're trying to do with our clients around the world is help them redefine, redesign their businesses, so that they're fit for purpose, so that they can survive and thrive in this modern world. >> Yeah, I want to get your thoughts on this, because you know looking back as a historian if you will of evolution, technology used to be slower, so agencies added value on something complex, ad agencies would create ad campaigns and some glam, glamour around something. And we even saw it in some of the lead gen side of the business, where this beautiful micro-site and the graphics are amazing, it looked great but actually didn't scale there's no tech behind it. Now fast forward, you have the requirement for cool, relevant, and glamorous, but actually having tech involved. Cloud computing has really enabled this, and the role of data has really enabled it, so this is now the new normal, the new normal for these higher-end functionalities is actually having a tech stack, technology stack, combined with business engineering logic, >> Paul: Yeah. >> And real business outcome, like profit, money outcome objectives that people might want. How do you guys explain that story because, you know, I would just call a consultant up in the past, are you guys combining it to make it easier? What's the purpose that customers call you guys in for? What are they asking for from you guys? >> So I'll start off and then Matt, you can add color commentaries, so, the way we describe what you just, what you just brought to life there, was, we have multi-disciplinary teams, so we have a combination of business strategists right, so when our clients are engaging us, they could be working with a business strategist who's really comfortable showing up for work and wearing a suit and tie, and he could be sitting next to, in our studio, sitting next to one of our creative designers who's tattooed from his wrist to his neck. >> The hoodie guy building everything. >> The hoodie guy, right, sitting there building there, next to one of our data scientists who's popping open his Lenovo laptop, it's got the latest chip in it, and he's so pumped 'cause he's going to run some crazy data analytics on it, applying AI on top of it. And all of these people work together using Design Thinking so we have an approach we call IBM Design Thinking, they've all been trained, we've trained over 16 thousand people on Design Thinking, and they all work together and come together to solve our clients' ploblems. They work in a studio environment, and we've opened up 38 studios around the world. Studios are places where we co-create with our clients, or we invite our clients in to ideate, innovate and co-create >> So it's agile on the format, on the projects, not like Waterfall, hey now you pass the ball to the other guy, it's all integrated team. >> Yes, and what you end up having is, you end up having the view of understanding the business and the client's business challenge, which is where we start when we define the strategy, when we do the design work, it's underpinned with an understanding of the technology that's going to bring this to life. So we like to say that we don't do creative for creative's sake or creative just for the beauty of the art, we do creative that can actually be made real. >> Yeah, you guys put a relevant package together. So I got to ask you now, the beauty of cloud computing was, is that you don't have to provision a data center if you don't need it. Now you see people needing a data center for privacy reasons they store their data, hence the hybrid cloud strategy, et cetera et cetera, but if I want to do something like what you guys are doing, it's going to cost me money to build it out. One, where are the people? Skills of the people, salaries of the people, tools for the people, all that is expensive to build out. So it's natural to go to someone who's already got it. So I want you guys to talk about that dynamic, of buy versus build, what stays in-house that's core competency, and what's the scale leverage that the clients get from working with you guys, 'cause you have that advantage. >> Yeah, and actually what I like to tee up is, this cost effective approach that we use to help our clients jumpstart the work that they're doing, we call it an innovation garage, and Matt and the team in the UK and in Europe have really been champions of this approach. Why don't you share some of the work we do around innovation garages. >> Yeah, so, I mean, one example is our client BP who we've been working with in this space, and helping them drive a lot of the digital reinvention of their business. And so, teams of data scientists, designers, developers, working hand in hand with product owners from the client side but ideating, finding new different digital products and services that help improve advocacy of customers drive loyalty, drive new revenue streams but very quickly taking those ideas and turning them into prototypes right, paper prototypes, actual MVPs, minimum viable products, launching them into market right, choosing some target markets, but putting very measurable KPIs around each of those things >> What's the timetable on that roughly, ballpark? >> Probably getting those MVPs out at eight to 10 weeks right >> So, fast. >> Oh yeah, fast. >> It's not months, not eight months. >> No, no, there's no Waterfall. And so a radically different approach to getting things out there, in the hands of real users. And then testing and learning, iterating, and then based on the data, actual fact and data backed against those KPIs and measurements then starting taking the decision around whether we're going to scale that into a global product. >> Yeah before we go to drill down on that, what's the alternative to doing that? How many months would it take if I want to do it from scratch in-house? >> Spinning up large transformation programs right, and >> John: A year. >> Yeah, at least, multi-years >> John: At minimum. >> Multi-years, and I think the other thing John, that's kind of key about this way of working, is that you're starting to infuse new ways of working and new ways of thinking into the client's organization right, and so Design Thinking: lean, agile, dev ops, right all of these approaches to get things done in a more rapid way and so, you're kind of driving change and transformation through making and creating and doing, not through some big change management program. And so we've been, if I took BP for example, training and certifying their people in IBM Design Thinking, certifying them as product owners and so, through the act of making and creating these services, it's changing their culture and changing how they get stuff done and it's a bit like a fire, kind of a little fire that burns and spreads within the organization as people see what's going on and want to become part of it. >> And one of the ways we do that we actually co-locate in these innovation garages. So you take a company like BP, if you go to our South Bank office, we have a dedicated floor where you have a hundred BP people with the IBM iX team, working in this innovation garage model, >> So they're learning too with you it's not like you're doing all the work and they're integrating in. No, no, we're learning together and they're building new skills and we're building new skills, and we're coming up with new ideas and innovations we're doing it in a cost-effective way, to your point before, in the past companies would spend a lot of money to try to go down a big path and try to in essence, boil an ocean sometimes. >> Yeah and your one guy quits, you got to replace, skill gaps, massive challenges. >> But also I find that from the client's perspective the thing that they're most proud of, some of the things they're most proud of, is the bin, what they call the bin. And so it's all of those ideas that we've killed as far to the left as possible right, and taking an idea that traditionally may have turned into some big program, multi-millions spent on doing it to find that it actually didn't deliver the outcome for the end consumer. >> So Matt, talk about the example with Wimbledon 'cause obviously everyone kind of can recognize that brand, you guys have been working at Wimbledon, you have a relationship with them so they've known IBM for years. What's the current state of the art with Wimbledon? What are some of the things you're doing for those guys and how is iX team, your integrated design team, working with those guys? >> So we've been partnering with Wimbledon now for about 28 years, so relationship goes back to 1990, I mean Wimbledon's been around back since the 1870s, you know, the home of kind of tennis, tennis in an English garden, so complete with rain and drizzle and gray clouds and everything else. And so, probably over the last seven years we've been working with them to drive their digital transformation, and so, how they engage with fans, and so how they use data and analytics to drive insights to put very personalized experiences in the hands of fans. So if you think about an event like Wimbledon, runs for 13 days, and about 500 thousand people get to physically experience Wimbledon in the grounds. And so their whole strategy from a digital perspective is taking the beauty of the grounds and the experience, and how they can manifest that digitally to millions of people around the world. >> And that's more than live streaming that's more than highlights, that's replicating the vibe the buzz, the experience of being there. >> Completely, so if you look at the web channel right when you go to that website, you don't actually see tennis players and stuff on there. What you might see is a beautiful flower just wafting in the breeze right, so a lot of the technology and the experience that we put together is trying to bring to life the beauty of the grounds right, through those digital mediums. And also being very thoughtful and purposeful about the different channels, so when you think about the mobile app right people use that to get snack access to data they're on the move, they want to understand the scores, alerts, iPad, people tend to use that sat on the sofa in front of the telly, you know, second screen experience so there's a different set of use cases and demands. We launched the first Apple TV app for grand slam tennis tournaments. So again, people tend to be using that for catch up and replays and so, being very thoughtful and purposeful about the... >> And you got to keep track of the digital culture 'cause it's like fashion, you got to know what's state of the art, what's going to sell VR, AR, whole new creatives coming out >> You do but you also have to do it in a way that's authentic to the product. >> Tech fashion. (laughter) The latest and greatest. >> Hashtag new hashtag tech fashion But you also have to do it, what I was going to say, you have to do it in a way that's authentic to the brand that you're representing. >> John: And relevant. >> Correct, so we're expressing the brand of Wimbledon online through digital channels and mobile channels, it has to be consistent with the brand, the brand values, the brand purpose, the brand mission. >> And that goes in to the design side of it 'cause they're going to tell you look if we go off the brand, we're not... >> The beauty, the elegance, the elegance of the sport, the elegance of the All England Tennis Club, you have to capture all of that and represent it in a way that's genuine. >> Alright so this is where the melting pot between agency, creative, ad agency, where it's much more about experience, less about the tech, and tech come together. So I wanted to ask you, I did a panel this year at Sundance called the New Creative, with Intel and it was all about the emerging new creative artists that have tech behind it, and here's what we talked about, I want to get your reaction to it. Agile, which killed Waterfall development, made things less risky, the old days was, you build something, a lot of craftsmanship goes into it, but you ship it, you don't know if it's going to work, and you hope it works and sells. Then Agile de-risked that, but you're shipping code every day. But what we lost with Agile that's now coming back, and I think this is where you guys are hitting the mark, the idea of craftsmanship in the product is coming back. So you got Agile, that's good, but it felt boring, it felt, the products didn't feel great. Yeah, certainly they were successful and they used data to be agile and always be iterating, fail fast, et cetera, but now the users want craftsmanship, they want art, they want more experience in the tech product What's your reaction to that, what's your vision? Do you agree and, if you do, what's your opinion? >> Well I agree on the recommitment to craft, and the approach that we take to that is really starting with Design Thinking, and we view this a couple different ways. One, we think Design Thinking is a way to actually solve business problems in the modern world. Now design, we view as a craft. So we have very specific craftspeople that are pure designers, that's what they do every day for a living. Everyone in our organization practices Design Thinking. So I believe that the use of Design Thinking coupled with our design community and the world-class talent that we have there, has enabled to really get an underlying need, right. So when you're doing a design, you have to have the understanding of the underlying need of the customers that you're trying to serve. And that's what we really get at, so the craftsmanship that comes in through applying Design Thinking, applying your design principles to creating something that can then be made real and have an impact. If you ask our designers, in our 38 studios around the world what they love about being part of IBM iX and being part of IBM, it's the impact that they can have. That they can see their design scale, they can see it brought to life in a way that is far beyond anything they could've done at any agency >> Can't fake design, it's like security, you can't fake it, it either works or it doesn't. >> And the way we think about design right is about almost design with a capital D. And so it's not just about how things look and feel, it's about how they work, and so how you can apply design to help solve problems in a very different way right. And how you apply design to strategy because designers are problem solvers. And so actually having people apply a designer's mindset to problem solving, you end up with very different outcomes right, you end up with a lot more innovation driving into what you're building, and I think you end up with products and services that actually help make somebody's life a little bit easier right, you're taking friction out of their life you're delivering something meaningful and of value to them. >> You're doing empathy mapping, you're doing customer journey mapping, you're doing a persona development. I want to build on what Matt said though that designers are problem solvers. When we look at Design Thinking, we have a method called IBM Design Thinking, and the logo that we use for Design Thinking is actually an infinity loop. So what we do is we combine Design Thinking with Agile and I think of IBM Design Thinking as a 3-D printing of a solution to a problem. We're designing it, we're getting at an underlying need, we're prototyping something fitting a proof of concept, we're learning, we're now doing another iteration of Design Thinking and learning more about the underlying need, testing something, and as we keep testing and learning, we add more texture to the solution of the problem and it starts coming into focus for us. >> Yeah, and the key word's problem. I interviewed a Stanford professor on the cutting edge of innovation, design she said, "Don't fall in love with your product. Fall in love with solving problems." And I think that's kind of what you guys believe. >> And I think John, to the point that you raised, about Agile, you know, we see many organizations driving kind of Agile transformation and shifting, and you know, I think our perspective is very much is you need this combination of design, of Agile and dev-ops together, because Agile allows you to pivot quickly, dev-ops allows you to kind of learn and get rapid feedback from production and putting things out there, and you've got to have this kind of design-led approach to doing stuff, because you've got to make sure that what you're building and putting out there serves a purpose and a real outcome for the end user. >> That's perfect, and most people think oh, we're Agile, check. No, whoa, hold on, stop, yeah it's not a silver bullet. >> You brought up a great point from a business leadership perspective that don't fall in love with your products, fall in love with the problems that you're solving, We are seeing that across every industry we work in, and I think this new digital age, with all these emerging technologies going mainstream so fast, AI, AR, VR, blockchain, it's allowing companies to, in some ways, reimagine their purpose, but in some ways, revisit their original purpose. So if you look at, Ford as an example, they've declared that they're going from pure car manufacturing, to mobility services. If you look at our clients in the life sciences industry, years ago they would've declared themselves as pharmaceutical manufacturers right? But now they would look at themselves as partners in health and partners in the health ecosystem. And every industry we're operating in, there's that re-imagining or revisit of the core mission. >> I think this is the only interview I haven't asked about blockchain, but I was just talking to Jesse Lund about blockchain and we talked about digital currencies, digital, and we observed, and we were talking about things are happening faster. So what's happening on digital it's a speed gain, across the board, with currency there's no clearing, it's digital, it moves instantly. So his banking side, that's his thesis, but here, your customers are challenged with looking down the barrel and being scared when, damn, this is going to be fast, what if I screw this up? I mean this is kind of how I see it happening, like it's accelerated in all aspects. >> And this is where I think, in terms of the business that we're in how we're different, and you've kind of raised the traditional agencies and stuff earlier, John. I think the difference for us is, you know when you think about the world of advertising, and companies driving their message out through shouting loudly and campaigns and building micro-sites, actually, our perspective very much is that these, most organizations need to look at how they digitally reinvent, right. And so therefore the scale of change needed as they look to reinvent their businesses, the business models, the skill pools within the organization, how they're going to use data and insights to drive different experiences you start to move to a very different level of change and transformation right, and one where these technology platforms, and becoming a platform business in these organizations, right, need a partner fundamentally who can help them scale and drive that change. >> And the data's critical, using data, using cloud, dev-ops, Agile, design, all rolled into a highly accelerated process, that's hard. >> It is hard but, >> You guys are doing it though. >> Well yeah, that's what we do for a living. It's what our clients are faced with right now. It's kind of a like a Dickensian-like challenge, right, it's A Tale of Two Cities. With all the emerging tech that we were talking about before there's never been a better time to create new innovations. To be innovative in some of the things that we're doing with BP was a great example of that. And some of the bigger things we're doing with some clients that are trying to reinvent their organization around a renewed purpose. But at the same time, there's never been a bigger threat to existing companies, in terms of there's never been more opportunity to be disrupted. So between these two poles of never been a better time to be in business, never been a tougher time to be disrupted, that's where our clients are operating. And this juxtaposition of core and new where our clients have mostly been in business for more than a few years. They have a core business that they need to grow and optimize, while they also need to expand into the new. And they can't do one or the other, they have to do both at the same time. >> And you know the customers I talk to in the industry, around this area, really look down, they look at three choices. Go for it, that's scary, need a partner to do that you guys are there for that. Don't do anything, put your head in the sand. Or three, create blockers and ban stuff. So you're seeing, you kind of walk in and you kind of figure out who's doing what. You see the blockers with all these excuses, no well we've got this other... And then the head, well we should be, they don't do anything, they're not moving. And then people who move. >> Yeah. >> I mean that's the reality right now. >> You know, what we see, we just published this research you know, a C-suite study, so we interviewed 12,000 C-suite executives, over 2,500 CEOs, and the title of this study's The Incumbents Strike Back, and that's what we're seeing now, so we're not seeing folks kind of sitting or putting their heads in the sand, they're looking at their legacy business, and the competitive advantage they have because of all the knowledge and incumbent advantage that they have, and now applying that. >> Well Paul and Matt, we don't have enough time to go into the impact of blockchain and cryptocurrencies, and initial coin offering's impact, to the token economics of how your business will change but we'll do that another time. >> Fantastic. >> Alright thanks for joining The Cube. I'm John Furrier here live in Las Vegas for IBM Think 2018. A lot of great conversations here in The Cube number one live tech coverage, extracting the signal from the noise. We'll be back with more after this short break. (techno music)

>> Narrator: Live, from Las Vegas, it's theCUBE. Covering IBM Think, 2018. Brought to you by IBM >> Hello everyone, welcome back to theCUBE, we are here on the floor at IBM Think 2018 in theCUBE studios, live coverage from IBM Think. I'm John Furrier, the host of theCUBE, and we're here with Stefanie Chiras, who is the Vice President of Offering Management IBM Cognitive Systems, that's Power Systems, a variety of other great stuff, real technology performance happening with Power, it's been a good strategic bet for IBM. Stefanie, great to see you again, thanks for coming back on theCUBE. >> Absolutely, I love to be on, John, thank you for inviting me. >> When we we had a brief (mumbles) Bob Picciano, who's heading up Power and that group, one of the things we learned is there's a lot of stuff going on that's really going to be impacting the performance of things. Just take a minute to explain what you guys are offering in this area. Where does it fit into the IBM portfolio? What's the customer use cases? Where does that offering fit in? >> Yeah, absolutely. So I think here at Think it's been a great chance for us to see how we have really transformed. You know, we have been known in the market for AIX and IBMI. We continue to drive value in that space. We just GA'd on, yesterday, our new systems, based Power9 Processor chip for AIX and IBMI in Linux. So that remains a strong strategic push. Enterprise Linux. We transformed in 2014 to embrace Linux wholeheartedly, so we really are going after now the Linux base. SAP HANA has been an incredible workload where over a thousand customers run in SAP HANA. And boy we are going after this cognitive and AI space with our performance and our acceleration capabilities, particularly around GPUs, so things like unique differentiation in our NVLink is driving our capabilities with some great announcements here that we've had in the last couple of days. >> Jamie Thomas was on earlier, and she and I were talking about some of the things around really the software stack and the hardware kind of coming together. Can you just break that out? Because I know Power, we've been covering it, Doug Balog's been on many times. A lot of great growth right out of the gate. Ecosystem formed right around it. What else has happened? And separate out where the hardware innovation is and technology and what's software and how the ecosystem and people are adopting it. Can you just take us through that? >> Yeah, absolutely. And actually I think it's an interesting question because the ecosystem actually has happened on both sides of the fence, with both the hardware side and the software side, so OpenPOWER has grown dramatically on the hardware side. We just released our Power9 processor chip, so here is our new baby. This is the Power9. >> Hold it up. >> So this is our Power9 here, 8 billion transistors, 14 miles of wiring and 17 layers of metal, I mean it's a technology wonder. >> The props are getting so small we can't even show on the camera. (laughing) >> This is the Moore's Law piece that Jenny was talking about in her keynote. >> That's exactly it. But what we have really done strategically is changed what gets delivered from the CPU to more what gets delivered at a system level, and so our IO capabilities. First chip to market, delivering the first systems to market with PCIe Gen 4. So able to connect to other things much faster. We have NVLink 2.0, which provides nearly 10x the bandwidth to transport data between this chip and a GPU. So Jensen was onstage yesterday from NVIDIA. He held up his chip proudly as well. The capabilities that are coming out from being able to transport data between the power CPU and the GPU is unbelievable. >> Talk about the relationship with NVIDIA for a second, 'cause that's also, NVIDIA stocks up a lot of (mumbles) the bitcoin mining graphics card, but this is, again, one use case, NVIDIA's been doing very well, they're doing really well in IOT, self-driving cars, where data performance is critical. How do you guys play in that? What's the relationship with NVIDIA? >> Yeah, so it has been a great partnership with NVIDIA. When we launched in 2013, right at the end of 2013 we launched OpenPOWER, NVIDIA was one of the five founding members with us, Google, Mellanox, and Tyan. So they clearly wanted to change the game at the systems value level. We launched into that with we went and jointly bid with NVIDIA and Mellanox, we jointly bid for the Department of Energy when we co-named it Coral. But that came to culmination at the end of last year when we delivered the Summit and Sierra supercomputers to Oak Ridge and Lawrence Livermore. We did that with innovation from both us and NVIDIA, and that's what's driving things like this capability. And now we bring in software that exploits it. So that NVLink connection between the CPU and the GPU, we deliver software called PowerAI, we've optimized the frameworks to take advantage of that data transport between that CPU and GPU so it makes it consumable. With all of these things it's not just about the technology, it's about is it easy to consume at the software level? So great announcement yesterday with the capabilities to do logistic regression. Unbelievable, taking the ability to do advertising analytics, taking it from 70 minutes to 1 and 1/2. >> I mean we're going to geek out here. But let's go under the hood for a second. This is a really kind of a high end systems product, at the kind of performance levels. Where does that connect to the go to market? Who's the buyer of it? Is it OEMs? Is it integrators? Is it new hardware devices? How do I get involved and who's the target customer? And what kind of developers are you reaching? Can you just take us through that who's buying this product? >> So this is no longer relegated to the elite set. What we did, and I think this is amazing, when we delivered the Summit and Sierra, right? Huge cluster of these nodes. We took that same node, we pulled it into our product line as the AC922, and we delivered a 4 GPU air-cooled version to market. On December 22nd we GA'd, of last year. And we sold to over 40 independent clients by the end of 2017, so that's a short runway. And most of it, honestly, is all driven around AI. The AI adoption, and it's a cross enterprise. Our goal is really to make sure that the enterprises who are looking at AI now with their developer are ready to take it into production. We offer support for the frameworks on the system so they know that when they do development on this infrastructure, they can take it to production later. So it's very much driven toward taking AI to the enterprise, and it's all over. It's insurance, it's financial services sector. It's those kinds of enterprise that are using AI. >> So IO sensitive, right? So IOT not a target or maybe? >> So you know when we talk out to edge it's a little bit different, right? So the IOT today for us is driving a lot of data, that's coming in, and then you know at different levels-- >> There's not a lot of (mumbles) power needed at the edge. >> There is not, there is not. And it kind of scales in. We are seeing, I would say, kind of progression of that compute moving out closer. Whether or not it's on, it doesn't all come home necessarily anymore. >> Compute is being pushed to where the data is. >> Stefanie: Absolutely right. >> That's head room for you guys. Not a priority now because there's not an intense (mumbles) compute can solve that. >> Stefanie: That's right. >> All right, so where does the Cloud fit into it? You guys powering IBMs Cloud? >> So IBM Cloud has been a great announcement this year as well. So you've seen the focus here around AI and Cloud. So we announced that HANA will come on Power into the Cloud, specializing in large memory sets, so 24 terabyte memory sets. For clients that's huge to be able to exploit that-- >> Is IBM Cloud using Power or not? >> That will be in IBM Cloud. So go to IBM Cloud, be able to deploy an SAP certified HANA on Power deployment for large memory installs, which is great. We also announced PowerAI access, on Power9 technology in IBM Cloud. So we definitely are partnering both with IMB Cloud as well as with the analytics pieces. Data Science Experience available on Power. And I think it's very important, what you said earlier, John, about you want to bring the capabilities to where the data is. So things like a lot of clients are doing AI on prem where we can offer a solution. You can augment that with capabilities like Watson, right? Off prem. You can also do dev ops now with AI in the IBM Cloud. So it really becomes both a deployment model, but the client needs to be able to choose how they want to do it. >> And the data can come from multiple sources. There's always going to be latencies. So what about blockchain? I want to get to blockchain. Are you guys doing anything in the blockchain ecosystem? Obviously one complaint we've been hearing, obviously, is some of these cryptocurrency chains like Ethereum, has performance issues, they got projects coming out. A lot of open source in there. Is Power even puttin' their toe in the water with blockchain? >> We have put our toe in the water. Blockchain runs on Power. From an IBM portfolio perspective-- >> IBM blockchain runs on Power or blockchain, or other blockchains? >> Like Hyperledger. Like Hyperledger will run. So open source, blockchain will run on Power, but if you look at the IBM portfolio, the security capabilities in Z14 that that brings and pulling that into IBM Cloud, our focus is really to be able to deliver that level of security. So we lead with system Z in that space, and Z has been incredible with blockchain. >> Z is pretty expensive to purchase, though. >> But now you can purchase it in the Cloud through IBM Cloud, which is great. >> Awesome, this is the benefit of the Cloud. Sounds like soft layer is moving towards more of a Z mainframe, Power, backend? >> I think the IBM Cloud is broadening the capabilities that it has, because the workloads demand different things. Blockchain demands security. Now you can get that in the Cloud through Z. AI demands incredible compute strength with GPU acceleration, Power is great for that. And now a client doesn't have to choose. They can use the Cloud and get the best infrastructure for the workload they want, and IBM Cloud runs it. >> You guys have been busy. >> We've been busy. (laughing) >> Bob Picciano's been bunkered in. You guys have been crankin' out... love to do a deeper dive on this, Stefanie, and so we'd love to follow up with you guys, and we told Bob we would dig into that, too. Question I have for you now is, how do you talk about this group that you're building together? You know, the names are all internal IBM names, Power... Is it like a group? Do you guys call yourself like the modern infrastructure group? Is it like, what is it called, if you had to explain it to outside IBM, AIs easy, I know what AI team does. You're kind of doing AI. You're enabling AI. Are you a modern infrastructure? What is the pillar are you under? >> Yeah, so we sit under IBM systems, and we are definitely systems proud, right? Everything runs on infrastructure somewhere. And then within that three spaces you certainly have Z storage, and we empower, since we've set our sites on AI and cognitive workloads, internally we're called IBM Cognitive Systems. And I think that's really two things, both a focus on the workloads and differentiation we want to bring to clients, but also the fact that it's not just about the hardware, we're now doing software with things like PowerAI software, optimized for our hardware. There's magic that happens when the software and the hardware are co-optimized. >> Well if you look, I mean systems proud, I love that conversation because you look at the systems revolution that I grew up in, the computer science generation of the 80s, that was the open movement, BSD, pre-Linux, and then now everything about the Cloud and what's going on with AI and what I call the innovation sandwich with data in the middle and blockchain and AI as bread. >> Stefanie: Yep. >> You have all the perfect elements of automation, you know, Cloud. That's all going to be powered by a system. >> Absolutely. >> Especially operating systems skills are super imprtant. >> Super important. Super important. >> This is the foundational elements. >> Absolutely, and I think your point on open, that has really come in and changed how quickly this innovation is happening, but completely agree, right? And we'll see more fit for purpose types of things, as you mentioned. More fit for purpose. Where the infrastructure and the OS are driving huge value at a workload level, and that's what the client needs. >> You know, what dev ops proved with the Cloud movement was you can have programmable infrastructure. And what we're seeing with blockchain and decentralized web and AI, is that the real value, intellectual property, is going to be the business logic. That is going to be dealing with now a whole 'nother layer of programmability. It used to be the other way around. The technology determined >> That's right. >> the core decision, so the risk was technology purchase. Now that this risk is business model decision, how do you code your business? >> And it's very challenging for any business because the efficiency happens when those decisions get made jointly together. That's when real business efficiency. If you make one decision on one side of the line or the other side of the line only, you're losing efficiency that can be driven. >> And open is big because you have consensus algorithms, you got regulatory issues, the more data you're exposed to, and more horsepower that you have, this is the future, perfect storm. >> Perfect storm. >> Stefanie, thanks for coming on theCUBE, >> It's exciting. >> Great to see you. >> Oh my pleasure John, great to see you. >> You're awesome. Systems proud here in theCUBE, we're sharing all the systems data here at IBM Think. I'm John Furrier, more live coverage after this short break. All right.

>> Narrator: Live from Las Vegas, it's theCUBE! Covering IBM Think 2018. Brought to you by IBM. >> Hello and I'm John Furrier. We're here in theCUBE studios at Think 2018, IBM Think 2018 in Mandalay Bay, in Las Vegas. We're extracting the signal from the noise, talking to all the executives, customers, thought leaders, inside the community of IBM and theCUBE. Our next guest is Ritika Gunnar who is the VP of Product for Watson and AI, cloud data platforms, all the goodness of the product side. Welcome to theCUBE. >> Thank you, great to be here again. >> So, we love talking to the product people because we want to know what the product strategy is. What's available, what's the hottest features. Obviously, we've been talking about, these are our words, Jenny introduced the innovation sandwich. >> Ritika: She did. >> The data's in the middle, and you have blockchain and AI on both sides of it. This is really the future. This is where they're going to see automation. This is where you're going to see efficiencies being created, inefficiencies being abstracted away. Obviously blockchain's got more of an infrastructure, futuristic piece to it. AI in play now, machine learning. You got Cloud underneath it all. How has the product morphed? What is the product today? We've heard of World of Watson in the past. You got Watson for this, you got Watson for IOT, You got Watson for this. What is the current offering? What's the product? Can you take a minute, just to explain what, semantically, it is? >> Sure. I'll start off by saying what is Watson? Watson is AI for smarter business. I want to start there. Because Watson is equal to how do we really get AI infused in our enterprise organizations and that is the core foundation of what Watson is. You heard a couple of announcements that the conference this week about what we're doing with Watson Studio, which is about providing that framework for what it means to infuse AI in our clients' applications. And you talked about machine learning. It's not just about machine learning anymore. It really is about how do we pair what machine learning is, which is about tweaking and tuning single algorithms, to what we're doing with deep learning. And that's one of the core components of what we're doing with Watson Studio is how do we make AI truly accessible. Not just machine learning but deep learning to be able to infuse those in our client environments really seamlessly and so the deep learning as a service piece of what we're doing in the studio was a big part of the announcements this week because deep learning allows our clients to really have it in a very accessible way. And there were a few things we announced with deep learning as a service. We said, look just like with predictive analytics we have capabilities that easily allow you to democratize that to knowledge workers and to business analysts by adding drag-and-drop capabilities. We can do the same thing with deep learning and deep learning capabilities. So we have taken a lot of things that have come from our research area and started putting those into the product to really bring about enterprise capabilities for deep learning but in a really de-skilled way. >> Yeah, and also to remind the folks, there's a platform involved here. Maybe you can say it's been re-platformed, I don't know. Maybe you can answer that. Has it been re-platformed or is it just the platformization of existing stuff? Because there's certainly demand. TensorFlow at Google showed that there's a demand for machine learning libraries and then deep learning behind. You got Amazon Web Services with Sagemaker, Touting. As a service model for AI, it's definitely in demand. So talk about the platform piece underneath. What is it? How does it get rendered? And then we'll come back and talk about the user consumption side. >> So it definitely is not a re-platformization. You recall what we have done with a focus initially on what we did on data science and what we did on machine learning. And the number one thing that we did was we were about supporting open-source and open frameworks. So it's not just one framework, like a TensorFlow framework, but it's about what we can do with TensorFlow, Keras, PyTorch, Caffe, and be able to use all of our builders' favorite open-source frameworks and be able to use that in a way where then we can add additional value on top of that and help them accelerate what it means to actually have that in the enterprise and what it means to actually de-skill that for the organization. So we started there. But really, if you look at where Watson has focused on the APIs and the API services, it's bringing together those capabilities of what we're doing with unstructured, pre-trained services, and then allowing clients to be able to bring together the structured and unstructured together on one platform, and adding the deep learning as a service capabilities, which is truly differentiating. >> Well, I think the important point there, just to amplify, and for the people to know is, it's not just your version of the tools for the data, you're looking at bringing data in from anywhere the customer, your customer wants it. And that's super critical. You don't want to ignore data. You can't. You got to have access to the data that matters. >> Yeah, you know, I think one of the other critical pieces that we're talking about here is, data without AI is meaningless and AI without data is really not useful or very accurate. So, having both of them in a yin yang and then bringing them together as we're doing in the Watson Studio is extremely important. >> The other thing I want get now to the user side, the consumption side you mentioned making it easier, but one of the things we've been hearing, that's been a theme in the hallways and certainly in theCUBE here is; bad data equals bad AI. >> Bad data equals bad AI. >> It's not just about bolting a AI on, you really got to take a holistic approach and a hygiene approach to the data and understanding where the data is contextually is relevant to the application. Talk about, that means kind of nuance, but break that down. What's your reaction to that and how do you talk to customers saying, okay look you want to do AI here's the playbook. How do you explain that in a very simple way? >> Well you heard of the AI ladder, making your data ready for AI. This is a really important concept because you need to be able to have trust in the data that you have, relevancy in the data that you have, and so it is about not just the connectivity to that data, but can you start having curated and rich data that is really valuable, that's accurate that you can trust, that you can leverage. It becomes not just about the data, but about the governance and the self-service capabilities that you can have and around that data and then it is about the machine learning and the deep learning characteristics that you can put on there. But, all three of those components are absolutely essential. What we're seeing it's not even about the data that you have within the firewall of your organization, it's about what you're doing to really augment that with external data. That's another area that we're having pre-trained, enriched, data sets with what we're doing with the Wats and data kits is extremely important; industry specific data. >> Well you know my pet peeve is always I love data. I'm a data geek, I love innovation, I love data driven, but you can't have data without good human interaction. The human component is critical and certainly with seeing trends where startups like Elation that we've interviewed; are taking this social approach to data where they're looking at it like you don't need to be a data geek or data scientist. The average business person's creating the value in especially blockchain, we were just talking in theCUBE that it's the business model Innovations, it's universal property and the technology can be enabled and managed appropriately. This is where the value is. What's the human component? Is there like... You want to know who's using the data? >> Well-- >> Why are they using data? It's like do I share the data? Can you leverage other people's data? This is kind of a melting pot. >> It is. >> What's the human piece of it? >> It truly is about enabling more people access to what it means to infuse AI into their organization. When I said it's not about re-platforming, but it's about expanding. We started with the data scientists, and we're adding to that the application developer. The third piece of that is, how do you get the knowledge worker? The subject matter expert? The person who understand the actual machine, or equipment that needs to be inspected. How do you get them to start customizing models without having to know anything about the data science element? That's extremely important because I can auto-tag and auto-classify stuff and use AI to get them started, but there is that human element of not needing to be a data scientist, but still having input into that AI and that's a very beautiful thing. >> You know it's interesting is in the security industry you've seen groups; birds of a feather flock together, where they share hats and it's a super important community aspect of it. Data has now, and now with AI, you get the AI ladder, but this points to AI literacy within the organizations. >> Exactly. >> So you're seeing people saying, hey we need AI literacy. Not coding per se, but how do we manage data? But it's also understanding who within your peer group is evolving. So your seeing now a whole formation of user base out there, users who want to know who their; the birds of the other feather flocking together. This is now a social gamification opportunity because they're growing together. >> There're-- >> What's your thought on that? >> There're two things there I would say. First, is we often go to the technology and as a product person I just spoke to you a lot about the technology. But, what we find in talking to our clients, is that it really is about helping them with the skills, the culture, the process transformation that needs to happen within the organization to break down the boundaries and the silos exist to truly get AI into an organization. That's the first thing. The second, is when you think about AI and what it means to actually infuse AI into an enterprise organization there's an ethics component of this. There's ethics and bias, and bias components which you need to mitigate and detect, and those are real problems and by the way IBM, especially with the work that we're doing within Watson, with the work that we're doing in research, we're taking this on front and center and it's extremely important to what we do. >> You guys used to talk about that as cognitive, but I think you're so right on. I think this is such a progressive topic, love to do a deeper dive on it, but really you nailed it. Data has to have a consensus algorithm built into it. Meaning you need to have, that's why I brought up this social dynamic, because I'm seeing people within organizations address regulatory issues, legal issues, ethical, societal issues all together and it requires a group. >> That's right. >> Not just algorithm, people to synthesize. >> Exactly. >> And that's either diversity, diverse groups from different places and experiences whether it's an expert here, user there; all coming together. This is not really talked about much. How are you guys-- >> I think it will be more. >> John: It will, you think so? >> Absolutely it will be more. >> What do you see from customers? You've done a lot of client meetings. Are they talking about this? Or they still more in the how do I stand up AI, literacy. >> They are starting to talk about it because look, imagine if you train your model on bad data. You actually have bias then in your model and that means that the accuracy of that model is not where you need it to be if your going to run it in an enterprise organization. So, being able to do things like detect it and proactively mitigate it are at the forefront and by the way this where our teams are really focusing on what we can do to further the AI practice in the enterprise and it is where we really believe that the ethics part of this is so important for that enterprise or smarter business component. >> Iterating through the quality the data's really good. Okay, so now I was talking to Rob Thomas talking about data containers. We were kind of nerding out on Kubernetes and all that good stuff. You almost imagine Kubernetes and containers making data really easy to move around and manage effectively with software, but I mentioned consensus on the understanding the quality of the data and understanding the impact of the data. When you say consensus, the first thing that jumps in my mind is blockchain, cryptocurrency. Is there a tokenization economics model in data somewhere? Because all the best stuff going on in blockchain and cryptocurrency that's technically more impactful is the changing of the economics. Changing of the technical architectures. You almost can say, hmm. >> You can actually see over a time that there is a business model that puts more value not just on the data and the data assets themselves, but on the models and the insights that are actually created from the AI assets themselves. I do believe that is a transformation just like what we're seeing in blockchain and the type of cryptocurrency that exists within there, and the kind of where the value is. We will see the same shift within data and AI. >> Well, you know, we're really interested in exploring and if you guys have any input to that we'd love to get more access to thought leaders around the relationship people and things have to data. Obviously the internet of things is one piece, but the human relationship the data. You're seeing it play out in real time. Uber had a first death this week, that was tragic. First self-driving car fatality. You're seeing Facebook really get handed huge negative press on the fact that they mismanaged the data that was optimized for advertising not user experience. You're starting to see a shift in an evolution where people are starting to recognize the role of the human and their data and other people's data. This is a big topic. >> It's a huge topic and I think we'll see a lot more from it and the weeks, and months, and years ahead on this. I think it becomes a really important point as to how we start to really innovate in and around not just the data, but the AI we apply to it and then the implications of it and what it means in terms of if the data's not right, if the algorithm's aren't right, if the biases is there. It is big implications for society and for the environment as a whole. >> I really appreciate you taking the time to speak with us. I know you're super busy. My final question's much more share some color commentary on IBM Think this week, the event, your reaction to, obviously it's massive, and also the customer conversations you've had. You've told me that your in client briefings and meetings. What are they talking about? What are they asking for? What are some of the things that are, low-hanging fruit use cases? Where's the starting point? Where are people jumping in? Can you just share any data you have on-- >> Oh I can share. That's a fully loaded question; that's like 10 questions all in one. But the Think conference has been great in terms of when you think about the problems that we're trying to solve with AI, it's not AI alone, right? It actually is integrated in with things like data, with the systems, with how we actually integrate that in terms of a hybrid way of what we're doing on premises and what we're doing in private Cloud, what we're doing in public Cloud. So, actually having a forum where we're talking about all of that together in a unified manner has actually been great feedback that I've heard from many customers, many analysts, and in general from an IBM perspective, I believe has been extremely valuable. I think the types of questions that I'm hearing and the types of inputs and conversations we're having, are one of where clients want to be able to innovate and really do things that are in Horizon three type things. What are the things they should be doing in Horizon one, Horizon two, and Horizon three when it comes to AI and when it comes to AI and how they treat their data. This is really important because-- >> What's Horizon one, two and three? >> You think about Horizon one, those are things you should be doing immediately to get immediate value in your business. Horizon two, are kind of mid-term, 18 to 24. 24 plus months out is Horizon 3. So when you think about an AI journey, what is your AI journey really look like in terms of what you should be doing in the immediate terms. Small, quick wins. >> Foundational. >> What are things that you can do kind of projects that will pan out in a year and what are the two to three year projects that we should be doing. This are the most frequent conversations that I've been having with a lot of our clients in terms of what is that AI journey we should be thinking about, what are the projects right now, how do we work with you on the projects right now on H1 and H2. What are the things we can start incubating that are longer term. And these extremely transformational in nature. It's kind of like what do we do to really automate self-driving, not just cars, but what we do for trains and we do to do really revolutionize certain industries and professions. >> How does your product roadmap to your Horizons? Can you share a little bit about the priorities on the roadmap? I know you don't want to share a lot of data, competitive information. But, can you give an antidotal or at least a trajectory of what the priorities are and some guiding principals? >> I hinted at some of it, but I only talked about the Studio, right... During this discussion, but still Studio is just one of a three-pronged approach that we have in Watson. The Studio really is about laying the foundation that is equivalent for how do we get AI in our enterprises for the builders, and it's like a place where builders go to be able to create, build, deploy those models, machine learning, deep learning models and be able to do so in a de-skilled way. Well, on top of that, as you know, we've done thousands of engagements and we know the most comprehensive ways that clients are trying to use Watson and AI in their organizations. So taking our learnings from that, we're starting to harden those in applications so that clients can easily infuse that into their businesses. We have capabilities for things like Watson Assistance, which was announced this week at the conference that really helped clients with pre-existing skills like how do you have a customer care solution, but then how can you extend it to other industries like automotive, or hospitality, or retail. So, we're working not just within Watson but within broader IBM to bring solutions like that. We also have talked about compliance. Every organization has a regulatory, or compliance, or legal department that deals with either SOWs, legal documents, technical documents. How do you then start making sure that you're adhering to the types of regulations or legal requirements that you have on those documents. Compare and comply actually uses a lot of the Watson technologies to be able to do that. And scaling this out in terms of how clients are really using the AI in their business is the other point of where Watson will absolutely focus going forward. >> That's awesome, Ritika. Thank you for coming on theCUBE, sharing the awesome work and again gutting across IBM and also outside in the industry. The more data the better the potential. >> Absolutely. >> Well thanks for sharing the data. We're putting the data out there for you. theCUBE is one big data machine, we're data driven. We love doing these interviews, of course getting the experts and the product folks on theCUBE is super important to us. I'm John Furrier, more coverage for IBM Think after this short break. (upbeat music)