>> Narrator: Live from Stanford University in Palo Alto, California, it's theCube, covering Women in Data Science conference 2018. Brought to you by Stanford. >> Welcome back to theCube. I'm Lisa Martin and we're live at Stanford University, the third annual Women in Data Science conference, WiDS. This is a great one day technical event with keynote speakers, with technical vision tracks, career panel and some very inspiring leaders. It's also expected to reach over 100,000 people today, which is incredible. So we're very fortunate to be joined by our next guest, Ruth Marinshaw, the CTO for Research Computing at Stanford University. Welcome to theCube, Ruth. >> Thank you. It's an honor to be here. >> It's great to have you here. You've been in this role as CTO for Research Computing at Stanford for nearly six years. >> That's correct. I came here after about 25 years at the University of North Carolina Chapel Hill. >> So tell us a little bit about what you do in terms of the services that you support to the Institute for Computational Mathematics and Engineering. >> So our team and we're about 17 now supports systems, file systems storage, databases, software across the university to support computational and data intensive science. So ICME, being really the home of computational science education at Stanford from a degree perspective, is a close partner with us. We help them with training opportunities. We try to do some collaborative planning, event promotion, sharing of ideas. We have joint office hours where we can provide system support. Margot's graduate students and data scientists can provide algorithmic support to some thousands of users across the campus, about 500 faculty. >> Wow. So this is the third year for WiDS, your third year here. >> Ruth: It is. >> When you spoke with Margot Gerritsen, who's going to be joining us later today, about the idea for WiDS, what were some of your thoughts about that? Did you expect it to make as big of >> Ruth: No. >> an impact? >> No, no people have been talking about this data tsunami and the rise of big data, literally for 10 years, but actually it arrived. This is the world we live in, data everywhere, that data deluge that had been foreseen or promised or feared was really there. And so when Margot had the idea to start WiDS, I actually thought what a nice campus event. There are women all over Stanford, across this disciplines who are engaged in data science and more who should. Stanford, if anything, is known for its interdisciplinary research and data science is one of those fields that really crosses the schools and the disciplines. So I thought, what a great way to bring women together at Stanford. I clearly did not expect that it would turn into this global phenomenon. >> That is exactly. I love that word, it is a phenomenon. It's a movement. They're expecting, there's, I said over a 100,000 participants today, at more than 150 regional events. I think that number will go up. >> Ruth: Yes. >> During the day. And more than 50 countries. >> Ruth: Yes. >> But it shows, even in three years, not only is there a need for this, there's a demand for it. That last year, I think it was upwards of 75,000 people. To make that massive of a jump in one year and global impact, is huge. But it also speaks to some of the things that Margot and her team have said. It may have been comfortable as one of or the only woman at a boardroom table, but maybe there are others that aren't comfortable and how do we help them >> Ruth: Exactly. >> and inspire them and inspire the next generation. >> Exactly. I think it's a really very powerful statement and demonstration of the importance of community and building technical teams in making, as you said, people comfortable and feeling like they're not alone. We see what 100,000 women maybe joining in internationally over this week for these events. That's such a small fraction compared to what the need probably is to what the hunger probably is. And as Margot said, we're a room full of women here today, but we're still such a minority in the industry, in the field. >> Yes. So you mentioned, you've been here at Stanford for over five years, but you were at Chapel Hill before. >> Ruth: Yes. >> Tell me a little bit about your career path in the STEM field. What was your inspiration all those years ago to study this? >> My background is actually computational social sciences. >> Lisa: Oh interesting. >> And so from an undergraduate and graduate perspective and this was the dawn of western civilization, long ago, not quite that long (Lisa laughs) but long ago and even then, I was drawn to programming and data analysis and data sort of discovery. I as a graduate student and then for a career worked at a demographic research center at UNC Chapel Hill, where firsthand you did data science, you did original data collection and data analysis, data manipulation, interpretation. And then parlayed that into more of a technical role, learning more programming languages, computer hardware, software systems and the like. And went on to find that this was really my love, was technology. And it's so exciting to be here at Stanford from that perspective because this is the birthplace of many technologies and again, referencing the interdisciplinary nature of work here, we have some of the best data scientists in the world. We have some of the best statisticians and algorithm developers and social scientists, humanists, who together can really make a difference in solving, using big data, data science, to solve some of the pressing problems. >> The social impact that data science and computer science alone can make with ideally a diverse set of eyes and perspectives looking at it, is infinite. >> Absolutely. And that's one reason I'm super excited today, this third WiDS for one of the keynote speakers, Latanya from Harvard. She's going to be talking, she's from government and sort of political science, but she's going to be talking about data science from the policy perspective and also the privacy perspective. >> Lisa: Oh yes. >> I think that this data science provides such great opportunity, not just to have the traditional STEM fields participating but really to leverage the ethicists and the humanists and the social sciences so we have that diversity of opinions shaping decision making. >> Exactly. And as much as big data and those technologies open up a lot of opportunities for new business models for corporations, I think so does it also in parallel open up new opportunities for career paths and for women in the field all over the world to make a big, big difference. >> Exactly. I think that's another value add for WiDS over it's three years is to expose young women to the range of career paths in which data science can have an impact. It's not just about coding, although that's an important part. As we heard this morning, investment banking, go figure. Right now SAP is talking about the impact on precision medicine and precision healthcare. Last year, we had the National Security Agency here, talking about use of data. We've had geographers. So I think it helps broaden the perspective about where you can take your skills in data science. And also expose you to the full range of skills that's needed to make a good data science team. >> Right. The hard skills, right, the data and statistical analyses, the computational skills, but also the softer skills. >> Ruth: Exactly. >> How do you see that in your career as those two sides, the hard skills, the soft skills coming together to formulate the things that you're doing today? >> Well we have to have a diverse team, so I think the soft skills come into play not just from having women on your team but a diversity of opinions. In all that we do in managing our systems and making decisions about what to do, we do look at data. They may not be data at scale that we see in healthcare or mobile devices or you know, our mobile health, our Fitbit data. But we try to base our decisions on an analysis of data. And purely running an algorithm or applying a formula to something will give you one perspective, but it's only part of the answer. So working as a team to evaluate other alternative methods. There never is just one right way to model something, right. And I think that, having the diversity across the team and pulling in external decision makers as well to help us evaluate the data. We look at the hard science and then we ask about, is this the right thing to do, is this really what the data are telling us. >> So with WiDS being aimed at inspiring and educating data scientists worldwide, we kind of talked a little bit already about inspiring the younger generation who are maybe as Maria Callaway said that the ideal time to inspire young females is first semester of college. But there's also sort of a flip side to that and I think that's reinvigorating. >> Yes. >> That the women who've been in the STEM field or in technology for awhile. What are some of the things that you have found invigorating in your own career about WiDS and the collaboration with other females in the industry? >> I think hearing inspirational speakers like Maria, last here and this year, Diane Greene from Google last year, talk about just the point you made that there's always opportunity, there's always time to learn new things, to start a new career. We don't have to be first year freshmen in college in order to start a career. We're all lifelong learners and to hear women present and to see and meet with people at the breakout sessions and the lunch, whose careers have been shaped by and some cases remade by the opportunity to learn new things and apply those skills in new areas. It's just exciting. Today for this conference, I brought along four or five of my colleagues from IT at Stanford, who are not data scientists. They would not call themselves data scientists, but there are data elements to all of their careers. And watching them in there this morning as they see what people are doing and hear about the possibilities, it's just exciting. It's exciting and it's empowering as well. Again back to that idea of community, you're not in it alone. >> Lisa: Right. >> And to be connected to all of these women across a generation is really, it's just invigorating. >> I love that. It's empowering, it is invigorating. Did you have mentors when you were in your undergraduate >> Ruth: I did. >> days? Were they males, females, both? >> I'd say in undergraduate and graduate school, actually they were more males from an academic perspective. But as a graduate student, I worked in a programming unit and my mentors there were all females and one in particular became then my boss. And she was a lifelong mentor to me. And I found that really important. She believed in women. She believed that programming was not a male field. She did not believe that technology was the domain only of men. And she really was supportive throughout. And I think it's important for young women as well as mid-career women to continue to have mentors to help bounce ideas off of and to help encourage inquiries. >> Definitely, definitely. I'm always surprised every now and then when I'm interviewing females in tech, they'll say I didn't have a mentor. >> Lisa: Oh. >> So I had to become one. But I think you know we think maybe think of mentors in an earlier stage of our careers, but at a later stage we talked about that reinvigoration. Are you finding WiDS as a source of maybe not only for you to have the opportunity to mentor more women but also are you finding more mentors of different generations >> Oh sure. >> as being part of WiDS? >> Absolutely, think of Karen Mathis, not just Margot but Karen, getting to know her. And we go for sort of walks around the campus and bounce ideas of each other. I think it is a community for yes, for all of us. It's not just for the young women and we want to remain engaged in this. The fact that it's global now, I think a new challenge is how do we leverage this international community now. So our opportunities for mentorship and partnership aren't limited to our local WiDS. They're an important group. But how do we connect across those different communities? >> Lisa: Exactly. >> They're international now. >> Exactly. I think I was on Twitter last night and there was the WiDS New Zealand about to go live. >> Yeah, yeah. >> And I just thought, wow it's this great community. But you make a good point that it's reached such scale so quickly. Now it's about how can we learn from women in different industries in other parts of the world. How can they learn from us? To really grow this foundation of collaboration and to a word you said earlier, community. >> It really is amazing though that in three years WiDS has become what it has because if you think about other organizations, special interest groups and the like, often they really are, they're not parochial. But they tend to be local and if they're national, they're not at this scale. >> Right. >> And so again back to it's the right time, it's the right set of organizers. I mean Margot, anything that she touches, she puts it herself completely into it and it's almost always successful. The right people, the right time. And finding ways to harness and encourage enthusiasm in really productive ways. I think it's just been fabulous. >> I agree. Last question for you. Looking back at your career, what advice would you have given young Ruth? >> Oh gosh. That's a really great question. I think to try to connect as much as you can outside your comfort zone. Back to that idea of mentorship. You think when you're an undergraduate, you explore curricula, you take crazy classes, Chinese or, not that that's crazy, but you know if you're a math major and you go take art or something. To really explore not just your academic breadth but also career opportunities and career understanding earlier on that really, oh I want to be a doctor, actually what do you know about being a doctor. I don't want to be a statistician, well why not? So I think to encourage more curiosity outside the classroom in terms of thinking about what is the world about and how can you make a difference. >> I love that, getting out of the comfort zone. One of my mentors says get comfortably uncomfortable and I love that. >> Ruth: That's great, yeah. >> I love that. Well Ruth, thank you so much for joining us on theCube today. It's our pleasure to have you here and we hope you have a great time at the event. We look forward to talking with you next time. >> We'll see you next year. >> Lisa: Excellent. >> Thank you. Buh-bye. >> I'm Lisa Martin. You're watching theCube live from Stanford University at the third annual Women in Data Science conference. #WiDS2018, join the conversation. After this short break, I'll be right back with my next guest. Stick around. (techno music)

>> Announcer: Live from Las Vegas, it's the Cube. Covering VM World 2017. Brought to you by vmware, and its ecosystem partner. (electronic music) >> And we're back, this is SiliconANGLE Media's production of the Cube. I'm here with Keith Townsend, I'm Stu Miniman. Keith, I don't know about you, but one of the things that really excites me when I get to come to events like this is talking to the users, talking about the practitioners, what they're using, how they're using it. And so I'm really happy to welcome to the program, first-time guest Brett Ruth who's the server, storage, and virtualization supervisor at BKD. Brett, thanks so much for joining us. >> Thank you for having me. >> Alright so BKD. I know you're big in your field, but there might be some people out there that aren't familiar with your organization. Maybe just give us the thumbnail of the company, how long you been there, and your role there. >> Sure, BKD is the number 12 accounting firm in the United States, 36 offices, net revenue 564 million. Tax audit, corporate finance, wealth advisors, technology services, that's BKD in a nutshell. >> Alright, and your role in the organization? >> My role is kind of the server supervisor. I have a team of seven assist admins who report to me. We take care of anything on the Windows server to Lennox server, to our Nutanix environment, our Vmware environment, our IceLAN storage environment, and all the applications that live on those. >> Alright, so Brett, one of the things I'm sure you'll find, your stuff doesn't change, you don't acquisitions to integrate, you don't have new technology being thrown at you all the time. If sure every year they just say how much more budget and how many more people do you want. >> Exactly >> So bring us in the reality. What's your world like? What are some of the big challenges? I'd say first if you can from just kind of the industry standpoint, and how does that impact what you're doing? >> Sure, so BKD is a growth firm so we look at business acquisitions when we can. We look at those, we actually completed one not that long ago in Chicago. We expanded there. So each one's always different, you know different technology. Some of those acquisitions are a couple servers, some of them are completely cloud-based, some of them are mixed in between. So having a platform where we settle on with Nutanix has kind of helped be able to make those integrations a little bit easier. But no, every year budget cycle comes around, and what's the initiative the firm wants to do. And every year it's different. It's fun, you know it's challenging to have different and new things we have to tackle every year. >> So when choosing these platforms, one, quick question around the organization, a bunch of knowledge workers. How many, what's the head count? >> Brett: Around 26,000. >> 26,000. So you guys and your IT organization, you work for the bean counters of bean counters. (laughing) So they understand ROI, TCO. When it comes to selecting these technologies, how much pressure are you under to do less for more, and prove that you're doing, I'm sorry, do more with less, and prove that you're doing more or less? >> Sure, and that comes up during the budget cycles. I mean there is a large amount of time that is spent of what's next year's initiatives? What does that server landscape look like? You know, does there a new product that comes out that requires a head count increase or not? Or is it a new application we need to stand up? And every year that comes around, and the questions come. Well, maybe the firm didn't have a good year, maybe the firm had a better year. So we, you know, the budget gets adjusted based on that. But more times than not, the firm recognizes that putting money into IT does nothing but help the business grow. So as long as we spend it wisely, we usually can, we can get accomplished. >> Alright Brett, I want you to take us inside, you know I hate to do it, but the budgeting thing. Cause one of the promises of, you said you're using Nutanix, used to be okay this year, oh it's time for the server refresh, next year, wait, no, you don't have any server budget, you know, we're doing some storage ad ons, or things like that. You might get some budget here or there if you need it, or if there's an emergency, but you got to justify that. The promise of a pool of resources should be, well I'm consolidating a number of pools, and therefore, I should be able to be more agile, more flexible, I'm buying in smaller chunks, rather than bigger chunks. What's your experience been on kind of that purchasing from that relationship with the finance side of the business? >> Sure, so when I started BKD, I've been there about five years, it was a traditional three-tier architecture when we rolled into it. And the firm was growing at such a rate that we were running into those physical limitations of the hardware. And it's never a fun game to go ask the CIO an unbudgeted SAN purchase you know. Do that a couple of years in a row, and it gets harder and harder to ask those questions. So we finally came to a point as a company of we need to do something different. And, you know, through research and product I had, and my team all had to do to accomplish it, we landed on Nutanix, and we landed on a hybrid converge infrastructure. And what we can do is we build those quote unquote lego blocks, so now there's not a big, giant purchase of a SAN or a new set of UCS Chassis or whatever the product might be. It's a, I know this quarter I need this amount of nodes, or I know for this project I'm going to need this, and I can just build and add on when I need to. So it makes the budgeting and those unbudgeted purchases a lot more easier to take. >> So much of the messaging from day one, day two is aimed kind of at you. You're on the ground, you have to deal with not only the engineers that implement the technology, but also the executives that approve the purchases. So a lot of the messaging here has been for you. How have you received it, and what's your impression of Vmware's messaging around, take your favorite topic? >> Right, you know a lot of cloud talk's been happening here and a lot of DevOps has been talked about here, and a way to improve that. BKD has an internal IT development team, so a lot of those things I can take away here, and try and see if I can help our Dev team however I can. A lot of the messaging is just seeing where the industry is going, not just Vmware, but everyone on the solutions floor. I mean that's a lot of my time here is research and seeing what products that I know we have to complete in the next fiscal year or two, and then what products are out there that I can just buy. >> Alright, can you bring us into your application portfolio? What sits on the Nutanix platform, what doesn't? I hear you said you got a scale-out NAS platform also. You talked about some developers there. I'd love to understand how you figure out what goes where, where you are in building that out. How many nodes you have if you can share? >> The IceLAN is six nodes in each data center, the Nutanix is 26 nodes in each data center. We're probably 99.9% virtualized. The only thing I think we don't have virtualized is we still have a physical domain controller outside of both just from shear, if everything is off, I have one point I can get back into, right. But exchange, sharepoint, our sequel is all virtualized. The IceLAN is really kind of the unstructured file pool that we can put map drives, we can put blob storage from our sharepoint environment lands onto it. Flat files from our sequel land onto it. And, yeah, everything runs on our Nutanix. >> So going into that developer relationship, you know Nutanix, I've talked to these guys before about their ideal of being a cloud company. So developers, when they hear the term cloud, what's the impact of you, on your role, when you have Nutanix, a cloud company, and your developers asking for cloud? >> It's a interesting question because we try and phrase it as BKD, we now have an internal cloud, we have an enterprise cloud, you know the term private cloud. And we can provide those instant resources to DevOps when they need it depending on if they have a new set of QA boxes that need to be stood up. But you know there is some projects that we're looking at of is it AWS or is it Azure or is it Google's cloud. Are there things that make sense to go out there versus keeping 'em in house? And those come up as an as-need basis. >> So DevOps, so (laughing) When we talk about DevOps, what are the pain points that you guys, cause that's a big topic. Do I go all the way as far as Netflix and DevOps all the things that we say, or what have you guys targeted to say, okay, here's where the value add is in the enterprise? >> I think we're still, that's still of of those things that our development team's looking at. I think it really depends on the application and what the business is looking for. I mean there's been some products internally that the team's released that makes sense to stay on Prim. The next project I find out a month from now might be something that's perfect for the cloud. I think they just take that on a kind of case-by-case basis. >> Alright, Brett, you've got a portfolio of partners that you're working with here. What's on your list of to-do's for them? What are you looking for from the ecosystem to make your life easier and help? >> Always looking for more stable code releases. I think any engineer would love stable code releases. You know for the most part everybody gets that. We're always going to have issues. >> Anybody you want to call out for not giving you stable code releases? (laughing) >> I can say everybody because, I mean everyone will do that. No, I think it's continuing to improve the product, continuing to make it. It's that do more with less right? I can't have two or three dedicated people working on the virtualization environment. They have to be multi-skilled you know. My team that I have, my seven assist admins are all great, probably some of the best guys I've worked with. We all have to wear multiple hats, even sometimes maybe we don't want to. So having those products come into the environment that make it easier for them, and then just seeing how those code releases come out, that would just make our lives even better. >> Just real quick, can you say whose hardware your Nutanix is on? >> It's Supermicro, it's from Nutanix. >> It's the basic things. This morning the keynote got a big laugh talking about some of the coope-tition that goes on just between Dell, EMC, Vmware in some of their partnerships. Some of your partners get along better than others. Is that something that impacts you, something you think about at all? >> It's definitely, being a Nutanix guy coming into VM World this year has definitely been an interesting experience. It's that cohabitation that happens between the two. But at the end of the day, I still have severs to run, I have an environment to maintain for BKD, and you know, if I need something done, I know I can go to them, and they'll help work with me on it. >> So the show floor this year, Vmware just as massive as it's been all-- >> Yeah. >> Vmware is all about the ecosystem. How important is this large ecosystem to your everyday operations of you environment? >> I mean it's the never knowing what the next project that comes out, or the next scene the business wants to do, or the next acquisition comes up. Maybe there's a product that I don't have in house that needs to take care of it. And then having this many vendors that I can go and talk with over these couple days has been great because I can now go back to the team and go, man I didn't think about this, and this product would help solve that. Or two months from now something comes around, I go oh yeah I talked to these guys, and go flip through the business cards and the paper stuff we take home and call 'em up. >> I love that even as a Nutanix customer, the Vmware, the coope-tition, that you still find value in the overall-- >> Brett: Oh yeah absolutely. >> Brett, any either announcements or kind of new things coming out in the market, anything catch in your eye? You said you were bringing that back to the office. >> Forgive me but I can't remember the name. The malware kind of virus scanner that Pat was talking about yesterday. That kind of really was a, being able to use that AI to figure out at a base level what milicent code is and isn't was, it would be an awesome game changer if it works out how it looks to be. >> Absolutely, no shortage of new things to look into. Brett Ruth, BKD, really appreciate you sharing your viewpoint everything going on inside. Really appreciate you coming on. >> Thank you guys. >> Hope to catch up with you sometime in the future. For Keith Townsend, and I'm Stu Miniman, we'll be back with lots more coverage here from VM World 2017. You're watching the Cube. (electronic music)

>>Welcome everyone. This is Stephanie Chan with the cube, but this conversation is part of Ws 2022 coverage. Today, we'll be speaking with Lila cor managing director at Google. Welcome to show Lila. >>Thank you so much. It's great to be here. >>So how did you come to be a data science leader? >>Yeah. Thank you. Um, you know, let me tell you how I came to be a data science leader, and also just thank you again to, uh, WIDS for having me here, this mission to support those in university or aspiring to be data scientists and those who are in the fee. It's just so important and inspiring to me. So it's been great to see this interest in WIDS and data science from young people all across the globe. So just thanks for having me here, uh, let me tell you how I came to be a data science leader. It really starts with identifying what you're passionate about and what you enjoy and what you're good at really passionate about using data to solve problems. I enjoy problem solving with data and analytics and following these passions led me to take classes in math and economics and econometrics. >>And I also took classes in political science and public policy have a diverse background. Um, and I think that having diverse backgrounds around the table are critical and an asset, um, but that those, uh, courses and that, uh, getting a, that undergrad and a master's started, I started my career as an economist at the us treasury department. And then I moved into technology over 20 years ago. I joined a startup in early 2000 and I've been a big tech companies like Google as well as at startups. And I really realized early on, uh, in my career, how much I enjoy data driven decision making. And I understood how powerful of a role data plays in making informed business decisions. There's just so much uncertainty in the problem that we're trying to address. There's a lot of ambiguity. Um, and data science is just absolutely critical to helping think through making those decisions and uncertainty. >>Another passion of mine is asking questions. My teams will tell you, I like asking a lot of questions and that is key. Uh, when you're a data scientist and we, you lead data science team, who's asking a lot of really good questions and impact. That's also super important to me. The best feeling is the impact you can make on a company with data. Finally, I'm also passionate about managing people and team leadership and applying data to solve cross-functional problems across so many different functions. I've been able to work product and marketing and strategy and operations. And by following these passions, I've gravitated towards managing more quantitative and analytical teams that are also passionate about using data and analytics to grow businesses. And when you work at Google, you're surrounded by this culture of innovation and a culture that's focused on translating data into value. So that's how I ended up becoming a data science leader. Um, you know, my advice to everyone is just like, uh, you know, to is stay curious, think about your passions, what you enjoy doing and the type of problems that you enjoy solving and that, that, and think about the kind of impact that you are looking to drive in this world. For me, that's led to leading data science teams and other broader teams, um, and I had to be open and flexible to where that might take take you, uh, it, it might be different from what you envisioned front >>And speaking of your teams, can you tell us about your teams and the work they do? >>Absolutely. Um, so I'm currently the managing director of Google's technical professional services and marketing data science teams for a group called the global clients and agency solutions. And we help the world's largest brands. In the digital age. We work directly with some of the world's most sophisticated, uh, chief marketing officers and marketing organizations in the world. So I'm honored to lead an organization that develops advanced engineering and data science solutions for Google's largest customers and largest advertisers. My team include customer solution engineers. They include engagement managers, they include technical specialists, and they also include, uh, data scientists. There's, you know, PhD, statisticians, economists, former consultants with deep experience in data science, machine learning and marketing analytics, uh, in my teams and my data teams, they find insights that change the business, uh, in the future. They're, they're amazing. And they do work. That's really groundbreaking. Actually. Can I tell you about some of the superpowers of the data scientists on my teams? >>Of course, I would love to hear it. >>Yeah, well, um, our marketing data science teams, they help measure optimize marketing, uh, a return on investment for Google's largest global clients. So one superpower is their customer obsessed. Um, they, we sit down at the C level table and with our customers, we ask a lot of questions so that we can understand the customer's business objective and how data can help them think through the various options they have. Another superpower is my teams are really good at asking really important questions. You know, you need to really have that back and forth to understand what your customer, what your exec, what they're trying to achieve. Um, and then they build cutting edge complex models that address our customers, key business questions that translates into things like marketing analytics, marketing, mix modeling, statistical modeling, machine learning, uh, you know, digital attribution, predictive analytics, my teams, they create rigorous experiments to help deliver the best possible solutions to our customers. >>Um, another superpower is helping to make better decisions in uncertainty. This is key data. Scientists are so good at this and my teams help these big cutting edge, you know, C level execs and CMOs and marketing organizations all around the world. Um, they help them find better ways to achieve peak marketing ROI. I've been a VP of marketing, um, you know, in startups and throughout my career, I know how hard it is and how important it, it is to grow your business with marketing, um, and really impact, uh, a business and all of their customers. So I'm really proud of the groundbreaking work that my teams are doing to help the world's biggest brands grow, uh, in the digital age, this just one of the types of careers and data science. Uh, my teams were in the, a business organization that works with marketers and advertisers, but I've also been able to lead teams that work with Google's product and engineering leadership to improve our products as well with data science. And there are data science teams in so many different parts of Google that are working on really complex, important challenges, whether it's in our global business organization, whether it's in Google cloud or Google product, YouTube, Google health, I mean, Google health, you know, has done some amazing things using artificial intelligence to prevent blindness. So that's a little bit about my teams and the work that they do >>And what career skills and experiences are most important to you as a data science leader at Google. >>Yeah. Um, thank you. Like I mentioned, we have such a great culture here at Google, a culture of innovation, um, a culture of really trying to solve complex and hard problems, important problems. And these problems have a lot of ambiguity. A lot of uncertainty, there's not always a, a clear right answer. This is where data science can just have such a huge impact. So of course, there's the strong foundation that we look for in the core data, science skills, stats, econometrics, and math, but some of the other skills that are so important, I would say being clear on the problem that you're trying to solve, uh, and focusing on what matters most, this is so important when you're faced with complex ambiguous, multifaceted problems to not get lost in the details or lose focus, asking those really important and, uh, questions and really trying to understand the problem that your customer or your exec is trying to solve. >>So ask, uh, being clear on the problem that you're trying to solve and asking really good questions. That's a, a, a key skill, um, that I think is very important at Google. Another one is the importance of storytelling. I mean, without a good narrative, it can be hard to move from data to insight. And when you're faced with lots of data, you know, being able to distill that complex data into a meaningful and coherent and impactful story. So those strong narrative and communication skills, they're critical, they're critical to ensure that your customer or your exec or your audience, here's the insight that these types of skills, data science skills can help uncover. And I've just add one more, which is there's a skill around thriving and uncertainty and thriving and ambiguity. You know, there's, you'll, it's just inevitable. Um, you've got to, you're gonna hit roadblocks. There's gonna be setbacks. There's a lot of complexity. So being able to be flexible, being able to pivot, being a leader, a role model about how to bounce back, helping others to do so. That's a really critical skill because a lot of the work that we're doing, uh, at Google and specifically data science, they're here to help people think through uncertainty. So those are some of the, um, the skills and experiences that I think are most important to me as a data science leader at Google >>And throughout your career, what is the best piece of advice you have received? >>Uh, thank you for that question. Um, I've received a lot of really great advice, but if I were to pick one for this group, it would be never underestimate the power of showing the world. What's possible. Ruth Perra said that, um, I heard her say that once, and she's the CFO at Google, and it really resonates with me. It's a great reminder of how powerful role models are. They provide us with inspiration and a vision for who we can aspire to be. They help us dream bigger dreams for ourselves. I know I've benefited so much from role models all throughout my life and career who show, show me what's possible. And that idea that you are showing someone else what's possible that they may not have envisioned for themselves. Well, that's super inspiring, motivating to me. So don't underestimate that power that you are providing visual proof, uh, for others about being leaders in data science or to technology. >>And I'd, you know, when I reflect on that advice, I also realize you don't need to have a big title to do this, to show the world what's possible. I have two daughters, my 10 year old daughter. She's inspiring people all the time, including me. Uh, my eight year old daughter is a role model for others in the community, including me. Um, I see courage and inspiration all around me every single day from my team members. Like I, uh, mentioned from friends, from colleagues, from community members. There, there there's so many important firsts that they're role modeling, whether they're first in their family to go to college or the first to pursue data science or just so many other important firsts. So I would say never underestimate the power of showing the world. What's possible. That's a great piece of advice I've received. >>And this, my last question for you, what, what is one thing that you want all of the aspiring data scientists or women in the field who are listening to this interview to take away? >>Yeah. I would want them to take away that your voice matters. You belong at this table for everyone who is listening in the audience. You know, those of you in universe are aspiring to be data scientists. Those in the field, the world needs you. We need you to be data scientists. We need your voice and your insights at the table to address the biggest challenges in business and technology in the environment, in health, in society, you belong, you belong in data science, you belong at that sea sweet table. You belong here, you belong in your voice matters. >>Well, thank you so much for teaching us more about science and all your advice. >>It's a pleasure. Thank you again for having me. I really appreciate it. >>I'm Stephanie Chan with de cube. We'll see you next time.

(upbeat music) >> Hello, and welcome to theCUBE special presentation of Unstoppable Domains Partner Showcase. I'm John Furrier, your host of theCUBE. We've got a great conversation talking about the future of the infrastructure of Web3, all around domains, non fungible tokens and more. Two great guests, Charlie Brooks with Business Development of Unstoppable Domains, and Michael Williams, Product Leader and Advisor with Unstoppable Domains. Gentlemen, thanks for coming on theCUBE, Partner Showcase with Unstoppable Domains. >> Thanks John, excited to be here. >> So I love what you guys are doing. Congratulations on all your success. You guys are on the leading edge of what is a major infrastructure. Shift to Web3 is being called, but people who have been doing this for a while know that you see the blockchain, you see decentralization, you see immutability all these future smart contracts. All the decentralized applications are now hitting the scene and NFTs are super hot as you can imagine, you guys in the middle of it. So you guys are in the sweet spot of what I call the Pragmatic pioneers. You guys are the building solutions that are making a difference, like single sign-on you have the login product, let's get into it. What is the path to a digital identity beyond the web? 'Cause we know what web identity is. But now that the web is being abstracted a away by this new Web3 layer, what is digital identity? >> I can take that one. So I think what we're really seeing is this transition away from a purely physical identity. Where your online identity is really just a reflection of the parts of your physical identity. Where you live, where you go to school, all of these things. And we're really seeing this world emerge where your online identity becomes much more of a primary. So if you have a way that you represent yourself in the online world, whether that's an Instagram account, or TikTok, or email address or username, all of these things together make up your digital identity. So congrats, if you have any of those things, you already have one. >> We see that all the time with Linktree, people put their Linktree out there and it's got the zillion handles. We all get up to Instagram. Everyone's got like zillion identities. Is that a problem or an opportunity? >> I think it's just a reality. The fact is our identities are spread across all of these different services and platforms that we use. The problem with something like Linktree is that it is owned by Linktree. If I won the lottery, purchased Linktree and decided I wanted to change your personal website, John, I could easily do that. Moving to the architecture that we have and NFT architecture, changes that significantly. It puts a lot of power back in the hands of the people who actually own those identities. I do a lot of CUBE showcases with folks around talking about machine learning and AI, and the number one conversation that they bring up, the number one issue, is data. And they say, when data's siloed and protected and owned, it is not optimized for machine learning. So I can almost imagine, as you bring NFTs to the digital identity, you mentioned you don't own your identity if someone else is managing the service like Linktree. This is a cultural shift, and infrastructure software shift at the same time. Can you guys expand more about what you guys are doing with the NFT and unstoppable domains with respect to that digital identity, because is that power shifting to the users now? And how does that compare to what's out there today? >> Sure, I think so. Our domains are NFTs, so they are ERC 721 tokens. And if you think about in the past Web2 identities are controlled by the platforms that we use. Twitter, Facebook, whatnot. There's really a lack of data portability there. Our accounts and data live on their servers, they can be deleted any time. So using an NFT to anchor your data identity, really gives you full control over your identity. It can't be deleted, it can't be revoked or edited, or changed without your permission. And really even better, the information you store on your entity domain can be plugged into the services you use, so that you never have to enter the same data twice. So when you go from platform to platform, everything can be tied to your existing domain. You're not going to a new site, entering their ecosystem and providing all this information time and time again, and not really having a clear understanding of how your data's being used and where it's being stored. >> So the innovation here is the NFT is your identity. And a non fungible token NFT is different than say a fungible token. So for the folks out there that's trying to follow the bouncing ball, Michael, what's the difference between an NFT and a fungible token? And why is that important for identity? >> My favorite metaphor here is baseball cards versus dollar bills. So a dollar bill is fungible. If I have a dollar and you have a dollar, we can trade dollars and none of us is richer or poorer. If I have a Babe Ruth and you have a Hank Aaron, and we swap baseball cards, we have changed something fundamental. So the important thing about NFTs is that they are non fungible. So if I have a domain and you have a domain, like I have that identity and you have that identity, they are unique, they're independent, they're owned by each one of us, and then we can't swap them interchangeably. >> And that's why you're seeing NFTs hot with art and artists, because it's like a property. It's a property issue, not so much- >> Absolutely >> Interchangeable or divisible kind of asset. >> Yep, it is ownership rights in digital form, yes. >> All right, so now let's get into what the identity piece. I think find that interesting because if I have something that's an NFT, it's non fungible, it's unique to me, it's property, my property my login, this sounds compelling. So how does login work with the NFT? Can you guys take us through that architecture, what does it do? How does it work? And what's the benefit? >> Good, so the way our login product works is it effectively uses your NFT domain. So Michael.crypto, for example, as the authentication piece of a login session. So basically when I go and I try to log in with my domain, I type in Michael.crypto, I sign it with my wallet which cryptographically proves that I am this human, this is me, I have the rights to log in. And then when I do so, I have the ability to share certain parts of my identity information with the applications that I use. So it really blends the ease of use from Web2 of just a standard like login with Gmail, SSO experience, with all of the security and privacy benefits of Web3. >> How important is single sign-on? Because right now people are used to seeing things like log with your GitHub handle or LinkedIn, or Google, Apple. You seeing people offering login. What's the difference here from those solutions and why does it make sense for the user? >> Sure, the big difference is what we're building is really user first. So if you think about traditional SSOs, you are the product. When you use their product, they're selling your data, they're tracking everything you do. Login with unstoppable handles not only authentication, but data sharing as well. So when you log in a domain owner can choose to share aspects of their online identities, such as first name, preferred language, profile picture, location. So this is a user controlled way of using a sign-on where their permissioning these different of their identity. And really apps can use this information to enable new experiences, such as, for example, website might automatically enable high contrast mode for someone visually impaired. It could pre-populate your friends from a decentralized social graph. So, what we're doing is taking the best parts of Web2 SSO and combining them with the best of Web3. So, no more losing your password, entering in the same data hundreds of times depending on other services to keep your information safe. Login with unstoppable really puts you in complete control of your data. And a big part of that is you're not going to have 80 plus usernames and passwords anymore. We have these tools like password managers that exist to put a bandaid on this issue, but it's not really a long term solution. So what we're building is really seamless onboarding where everything can be tied to your domains so that you can navigate to different apps in a much more seamless way. >> Michael, I got to get your thoughts on this because in the product side, it's interesting, my mind's connecting some dots. If I have first of all, great convenience to reduce all those logins. So, check their little pain reduction. But when you just think about what's different, I can now broker my data as well as login. So let's just say, hypothetically, I'm cruising around some dApps and I'm doing things in earning reputation, or attention, or points, or whatever utility tokens. There could be a way for me to control what I own. I'm the product, I own the data. Is that where this is going? >> I think it's definitely a direction it could go, say, for example, if I'm a e-commerce platform and I'm trying to figure out where I'm going to place a new billboard. One of the things that I could request from a user, is their address. I can figure out where they live, what city they're in, that will help inform me the decision that I need to make as a business. And in return, maybe I give that person a dollar off their purchase. We can start to build a stronger relationship between the applications that people use, and the people that use them. And try to optimize that whole experience, and try to just transfer information back and forth to make everyone's lives better. >> What's the roadmap on the business side Charlie, when you see companies adopting it, they're probably taking babies steps they're crawling before they walk, they're walking before they run. I can see decentralized applications in the future where there's FinTech or whatever, having new kinds of marketplaces that take advantage of the paradigm where the script flips to the user first. Okay, so I see that. How do people get started now? What are some of the success momentum points that you're seeing companies do now with unstoppable? >> Sure, so a lot of Web3 apps are very sensitive about respecting the information that their users are providing. So, what we're doing is offering different ways for apps can touch with their users in a way that is user controlled. So, an example there is that a lot of Web3 companies will use WalletConnect to allow users to log in using a wallet address. An issue there is that one person can have hundreds of wallet addresses, and it's impossible for the app to understand that. So, what we do is we use login, we attach an email address, some other pieces to a wallet address so that we can identify who our unique user is. And the app is able to collect that information, they don't have to deal with passwords or PII storage. They have access to a huge amount of new data for an improved UX. It's really simple to maintain as well. So one example there is if you are a DeFi platform and you want to reward your users for coming to their site for the first time, now that they can identify unique user, they can drop a token into that user's wallet. All because they're able to identify that user as unique. So they have a better way of understanding their customers. They enable their customers to share data. A lot of these companies will ask users to follow them on Twitter or Discord when they need to provide updates or bug bounties, all these different things. And login if unstoppable lets them permission email addresses so they can collect emails if they want to do a newsletter. And instead of harvesting data from elsewhere and forcing people to join this newsletter program, it's all user controlled. So each user saying, yes, you can use my email for your newsletter. I'm supporting your project, I want to be kept up to date with bugs or bounties or rewards programs. So really it's just a better way for users to share the data that they're willing to with dAPPs, and dAPPs can use it to create all sorts of incentives and really just understand their users on a different level. >> How is the development Michael, going on the smart contract side of the business? Ethereum has always been heralded as being very developer focused. There's been created innovations, you still got gas fees out there. You still got to do some things. How is the development environment? How are the applications coming? 'Cause I can see the flywheel kicking in as the developer front gets more streamlined, more efficient. And now you got the identity piece nailed down. I just see a lot of dominoes falling at the same time. What's the status on the DEV side. What you're doing. >> Good. The fascinating thing about crypto is how quickly it changes. When I joined Ethereum there was pretty reasonable still for transactions. It was very cheap to get things done very fast. With a look at last summer that things went completely out of control. This is a big reason that unstoppable for a long time has been working on a layer two. And we've moved over to the polygon as our primary source of record, which is built on top of Ethereum. Of course, I think saved well over a hundred million in gas fees for our users. We're constantly keeping an eye on new technologies that are emerging, weighing how we can incorporate those things. And really where of this industry is going to take us. In many ways we are just as much passengers as the other people floating around the ecosystem as well. >> It's certainly getting faster every day, I'm seeing a huge uptake on Ethereum. I heard a stat that most people at the university of California, Berkeley, 30% of the computer science students are dropping out to join Web3 companies. This goes to show you this cultural shift and you're going to see a lot more companies getting involved. So I got to ask you Charlie, on the BizDev front, how are companies getting started? What's the playbook? Are they putting their toe in the water? They jumping in full throttle? What's the roadmap? What's the best practice for people to get started with unstoppable? >> Absolutely. We're lucky that we get a lot of inbound interest from companies Web2 and Web3, because they first want to secure their domains. And we do a ton of work on the back end to protect trademark domains. We want to avoid squatting as much as possible. We don't think that's the spirit of Web3 at all. And certainly not what the original tension of the internet was. So, fair amount of companies will reach out to us to get their domain. And then we can have a longer conversation about some of the other integrations and ways we can collaborate. So certainly visiting our website, unstoppabledomains.com is a great starting point. We have an app submission page where apps can reach out to us, even request a grant. We have a grant program to help developers get started, provide them some resources to work with us and integrate some of our technology. We have great documentation as well on the site. So you can read all about what it takes to resolve domains, if you're a wallet and an exchange, as well as what it takes to integrate login with unstoppable, which is actually a super easy integration as well, which we're really excited about. So yeah, I'd say check out the website, apply for a grant if you think you're a fit there, then of course, people can always reach out to me directly on Twitter, on Telegram, email. We're very reachable and we're always happy to chat with projects and learn more about what they're doing. >> What's the coolest thing you see going on Charlie, with your partners right now? What's the number one use case that's cool that people are jumping on right now to get in and get some success out of the gate? >> Maybe GameFi play to earn is huge. It's blowing up and the gaming community is really passionate, vibrant, just expanding like crazy. Same with DeFi, there's all this cool new stuff you can do with DeFi where no matter how big your portfolio is, you're able to stake and use all these interesting tools to grow your book. So it's super exciting to see and talk to all these projects. And, there's certainly an energy in the community where everyone wants to onboard the general public to Web3. So we're all working on these school projects, but we need everyone to come over from Web2, understand the advantages of DeFi, of GameFi of having an entity domain. So, I'm lucky that I'm one of the first layers there of meeting new projects and helping get access to more users so that they can grow along with us. >> I remember the early days of Bitcoin and Ethereum, we were giving it away. The community mantra was, give a Bitcoin to someone. That was like, >> Right. >> When you can actually give a Bitcoin to someone. What's the word of mouth or organic viral? I won't say growth hack 'cause that's got negative connotations. But what's the community's way of putting forth the mission for unstoppable? Is it just more domains? You guys have any programs got going on? Is it give it away? Obviously you can get domains on your site, but what's the way to get people ingratiated in and getting comfortable? >> So much of what we do is really to solve that question, answer that question. We spend a ton of time and energy just on education and whether that's specifically around domains or just general Web3. We have a podcast which is pretty exceptional, which talks to Web3 leaders from across the space and makes the project that they're working on more accessible. I think we passed over a hundred episodes, not too long ago. There's a ton of stuff that we do that other people do. If anyone has questions, I'm happy to talk about our resources, of course. >> The pod, I think you guys are up to 117, but that's a deep dive. You guys go deep on the podcast. So that's where you go in. What else is new on digital identity? Where do you guys see the future going? Now that you get the baseline identity with the NFT. Makes a lot of sense, create innovation. Good logic, makes sense. Solid technically, what's next? >> I think this really boils down to the way that the internet has grown. Doesn't really feel like the way that the internet should be. Like our data shouldn't live in these wild gardens, controlled by these large companies. Ultimately people should be responsible for their own identities. They should have control over of things that they do online. The data that's shared, the benefit of that data. It's about the world that we are working towards, is very much that. Where we are giving people the ability to be paid for sharing their data with companies. We're giving applications the ability to request information from the people that use those applications to improve their experience. We're really just trying to make connections across the ecosystem through these products, to enable a better experience for everyone. So whether that's the use cases that I mentioned already, or maybe viewing reviews on something like Yelp or Amazon, that just confirm that the person that you are you're looking at is actually a real person, not some bot that's been paid to load a review. The interesting thing about these products is they're so universally applicable. There are so many different ways that we can try to plug them in. So we are- >> A bots is a great example, double-edged sword. You can have a metaverse image and have pre-programmed conversations with liquid audio and the video application. Or it's a real person. How do you know the difference? These are going to be questions around who solves that problem. Now there's time for bots and there's a time not for bots. We all know what happens when you get into the game of manipulation, but also it can be helpful. This is where you got to be smart. And identity's critical in this future. Charlie, what's your reaction to the future of digital identity? So much to look at here on the trajectory. >> I think a big part of it is data portability. If you go to a site like Instagram, you're giving them all this content that's very personal to you, and you can't just pack up and leave Instagram. So we want a future where most of these apps are just a front end and you can navigate from one to the other and bring your data with you. And not be beholden to the companies that operate centralized servers. So, I think data portability is huge and it's going to open up a lot of doors. And just going back to that thought on cleaning up Web2 for a better web three. When I think about the Amazons, the Yelps of the world, there are all these bots, there are all these awful fake reviews. There's a lot of gamification happening that is really just creating a lot of noise. And I want to bring transparency back to the internet where when you see a review, you should know that that's a real human. And blockchain technology is enabling us to do that. And certainly FT domains are going to play a huge part of that. So I think that having an experience where you know and trust the people that you're interacting with is going to be really powerful and just a better experience for everyone. And there's a lot of ramifications with that. politically speaking, we've all seen all the issues with attacking communities and using bots and fake accounts to hit people's pain points, it's sad and certainly not something that we want to see continue happening. So, whatever we can do to give people their digital identity and help people understand that this is a real person on the other end, I think is huge for the future of the internet and really for society as well. >> That's a great call out there Charlie. Cleaning up the mess of Web 2.0, Web2, actually it was 2.0 technically, now Web3 is no point zero in it. But I saw on or listened to the podcast with Matt. This recent one, he had a great metaphor that went back to when I was growing up in the internet, you had IP addresses. And the mess there was, you couldn't find what you want to look. And no one could remember what to type in, 'cause you could type in IP address in the browser back then. And then DNS came out and then keywords that's web. Now that mess, now is fraud, misinformation, bot manipulation, deep fakes, many other kind of unwanted time to innovate. And every year, every time you had these inflection points, there'd be an abstraction on top of it. So, similar thing happening here, is that how you guys see it too? >> I think we're going back to some of the foundational architecture of the internet, DNS. And really bringing that forward about 30, 40 years in terms of technology. So loading in some more cryptography and some other fancy things to help patch some of those issues from the previous versions of the web. >> Awesome. Well guys, thanks so much for coming on and the spirit of TikTok, Emily summarizes asking, can you guys give us a quick TikTok moment, short comment on where this is all going, where is login, single sign-on mean and what should people do to steps to secure their digital identity? >> Sure, I'll jump in here. So, it's time for people to secure their digital identity. The great first step is going to sample domains and getting an NFT domain. You can control your data. You can do a lot of cool different things with your domain, including posting your own website that you will own forever, no one can take it away from you. I would certainly recommend that people join our Discord, Telegram communities, check out our podcasts. It's really great especially if you're new to crypto Web3. We do a great job of explaining all the basic concepts and expanding on them. So yeah, I would say, the time is now to get your digital identity and start embracing Web3 because it's really exploding right now. And there's just so many incredible advantages, especially for the user. >> Michael, what's your take? >> But not, have said it better myself. >> Like we always say, if you're not on the next wave, you're driftwood. And this is a big wave that's happening. It's pretty clear guys, it's there, it's happening now. And again, very pragmatic implementations of solving problems. The sign-on, the app integration. Congratulations and we got our CUBE domain too, by the way. So I think we're good. >> Excellent. >> So, we got to put it to use. Appreciate it, Charlie, Michael, thanks for coming on and sharing the update. >> It's pleasure. >> Welcome. >> Okay, this is theCUBE, with Unstoppable Domains Partner Showcase I'm John for your host, got a lot of other great interviews. Check them out. We're going to continue our coverage and continue on with this great showcase. Thanks for watching. (upbeat music)

>>Hello, and welcome to the cube special presentation of unstoppable domains partner showcase. I'm John furrier, your host of the cube. We got a great conversation talking about the future of the infrastructure of web three, all around domains, non fungible tokens, and more two great guests. Charlie Brooks, with business development of ensemble domains, and Michael Williams, product leader and advisor with unstoppable doing gentlemen, thanks for coming on the cube partner showcase with unstoppable domains. >>Thanks John. Excited to be here. So >>I love what you guys are doing. Congratulations on all your success. You guys are on the leading edge of what is a major infrastructure shift. Web three is being called, but people who have been doing this for a while, know that you see the blockchain, you see decentralization, you see immutability, all these future smart contracts. All the decentralized applications are now hitting the scene and NFTs are super hot as, as, as you can imagine, you guys are in the middle of it. So you guys are in, in, in the sweet spot of what I call the pragmatic pioneers. You guys are to building solutions that are making a difference like single sign-on. You have the login product, let's get into it. What is the path to I digital identity beyond the web, because we know what web identity is, but now that the web is kind of being abstracted away by this new web three layer, what is digital identity? >>Yeah, I can take that one. So I think what we're really seeing is this transition away from a purely physical identity where your digital life or where your, your online identity is really just a reflection of the, the parts of your physical identity, where you live, where you go to school, all of these things. And we're really seeing this world emerge where your online identity becomes much more of a primary. So if you have a way that you represent yourself in the online world, whether that's an Instagram account or TechTalk or email address or username, all of these things together make up your digital identity. So congrats. If you have any of those things, you already have one. >>Yeah. And we see that all the time with link tree people put their link tree out there and it's got the zillion handles. You're right. We all get up to Instagram and everyone's got like zillion identities. Is that a problem or an opportunity? >>I think it's just a reality. The fact that as our identities are spread across all of these different services and platforms that we use, the problem with something like link tree is that it is owned by link tree. You know, if I won the lottery purchased link tree and decided I wanted to change your personal website, John, I could easily do that. Moving to the kind of architecture that we have. And then if T architecture changes that significantly, it puts a lot of power back in the hands of the people who actually own those identities. >>You know, I do a lot of cube showcases with folks rent on my machine, learning and AI, and the number one conversation that they bring up. The number one issue is data. And they say when data is siloed and, and protected and owned, it is not optimized for machine learning. So I can almost imagine, as you bring NFTs to the digital identity, you mentioned you don't own your identity. If someone else is managing the service like link tree, this is, this is a cultural shift. This is an infrastructure software shift at the same time. Can you guys expand more about what you guys are doing with the NFT and ensemble domains with respect to that digital identity, because is that power shifting to the users now? And how does that compare to what's out there today? >>Sure. I think so. Our domains are NFTs, so they are ERC 7 21 tokens. And if you think about the past kind of web two identities are controlled by the platforms that we use, Twitter, Facebook, whatnot. There's a really a lack of data portability there. Our accounts and data live on their servers. They can be deleted at any time. So using an NFT to anchor your digital identity really gives you full control over your identity. You can't, it can't be deleted. It can't be revoked or edited or changed without your permission. And really, even better than information you store on your entity domain can be plugged into the services you use so that you never have to enter the same data twice. So when you go from platform to platform, everything can be tied to your existing domain. You're not going to a new site, kind of entering their ecosystem and providing all this information time and time again, and not really having a clear understanding of how your data is being used and where it's being stored. >>So the innovation here is the NFT is your identity and, and a non fungible token NFT is different than say a fungible tokens. So for the folks out there, that's trying to follow the bouncing ball. Michael, what's the difference between an NFT and a fungible token. And how does, and why is that important for identity? >>Yeah. My favorite metaphor here is baseball cards versus like dollar bills. So a dollar bill is fungible. If I have a dollar and then you have a dollar, we can trade dollars. And none of us is richer or poorer. If I have a babe Ruth and you have a Hank Aaron, and we swap baseball cards, like we have, we have changed something fundamental. So the, the important thing about NFT is, is that they are non fungible. So if I have a domain and you have a domain, like I have that identity and you have that identity, they are unique. They're independent, they're owned by each one of us. And then we can kind of swap them interchangeably. >>And that's why you're seeing NFTs hot with art and artists, because it's like a property, it's a property issue, not so much absolutely changeable, a divisible kind of asset. >>It is a, it is ownership rights in digital >>Form. Yes. All right. So now let's get into what the, the identity piece. I think I find that interesting because if I have something that's an NFT, it's not fungible. It's unique to me. It's property, my property, my login, this sounds compelling. So how does log-in work with the NFT? Can you guys take us through that, that architecture, what does it do? How does it work? And what's the benefit? >>So the way our login product works is it effectively uses your NFT domain. So Michael dot crypto, for example, as the authentication piece of a, of a login session. So basically when I, when I go and I try to log in with my domain, I type in Michael dot crypto. I sign it with my wallet, which cryptographically proves that I am this human. This is me. I have the rights to log in. And then when I do so I have the ability to share certain parts of my identity information with the applications that I use. And so it really blends the best of the ease of use from web to have just a standard like login with Gmail SSL experience, with all of the security and privacy benefits of web three. >>How important is single sign-on because, I mean, right now people are used to like, seeing things like log with your kid hub handle or LinkedIn, or, you know, Google, apple. I mean, you're seeing people offering login. Okay. What's the difference here from those solutions and why is it make sense for the user? >>Sure. Yeah. The big differences, what we're building is really user first. So if you think about traditional SSOs, you are the product. When you use their product, they're selling your data and, you know, they're tracking everything you do logging in with unstoppable handles, not only authentication, but data sharing as well. So when you log in a domain or owner can choose to share aspects of their online identity, such as first name, preferred language profile, picture location. So this is a user controlled way of using a sign-on, where they are permissioning, these different pieces of their identity. And really apps can use this information to enable new experiences, such as for example, website might automatically enable high contrast mode for someone visually impaired. It could, pre-populate your friends from a decentralized social graph. So what we're doing is taking the best parts of web to SSL and combining them with the best parts of web three. >>So no more losing your password entering in the same data, hundreds of times, you know, depending on other services, keep your information safe. Logging with unstoppable really puts you in complete control of your data. And, you know, a big part of that is you're not going to have 80 plus usernames and passwords anymore. You know, we have these tools like password managers that exist to kind of put a bandaid on this issue, but it's not really a long-term solution. So we're, we're building is really seamless onboarding where everything can be tied to your domain so that you can navigate to different apps in a much more seamless way. >>Michael, I got to get your thoughts on this because on the product side, it's interesting. My mind's kind of connecting some dots if I have, first of all, great convenience to reduce all those logins, right? So, you know, check their little pain, pain reduction. But when you think about what's different, I can now broker my data as well as log in. So let's just say, hypothetically, I'm cruising around some D apps and, you know, doing things and earning reputation or attention or points or whatever, tokens utility tokens. There could be a way for me to control what I own. I'm the product I own the data. Is that kind of where this is going? >>I think it's definitely a direction. It could go say, for example, if I'm a e-commerce platform and I'm trying to figure out where I'm going to place a new billboard, you know, one of the things that I could request from a user is their address. I can figure out where they live, what city they're in that will help inform the, the decision that I need to make as a business. And in return, maybe I give that person a dollar off their purchase, right? Like we can, we can start to build a stronger relationship between the applications that people use and the people that use them and try to optimize that whole experience and try to just transfer information back and forth to make everyone's lives better. >>What's the roadmap on the business side, Charlie, when you see companies kind of adopting it, they're probably taking baby steps or crawling before they walk they're walking before they run. I mean, I can see decentralized applications in the future, whether it's FinTech or whatever, having new kinds of marketplaces that take advantage of the paradigm where the, the script flips to the user first. Okay. So I see that. How do people get started now? What are some of the success momentum points that you're seeing companies do now with unstoppable? >>Sure. So a lot of web three apps are very sensitive about respecting the, the information that their users are providing, right? So what we're doing is I'm offering different ways for apps can touch with their users in a way that is user controlled. So an example there is that a lot of web three companies will use wallet connect to allow users to log in using a wallet address, an issue. There is that one person can have hundreds of wallet addresses, and it's impossible for the app to understand that. So what we do is we use login, we attach an email address, some other pieces to a wallet address so that we can identify who a unique user is. And the app is able to collect that information. They don't have to deal with passwords or PII storage. They have access to a huge amount of new data for an improved UX. >>It's really simple to implement and maintain as well. So one example there is if you are a DFI platform and you want to reward your users for coming to their site for the first time, now that they can identify unique user, they can drop a token into that user's wallet all because they're able to identify that user as unique. So they have a better way of understanding their customers. They enable their customers to share data. A lot of these companies well ask users to follow them on Twitter or discord when they need to provide updates or, you know, bug bounties, all these different things and log in with unstoppable, lets them permission, email addresses so they can collect emails if they want to do a newsletter. And instead of sort of harvesting data from elsewhere and kind of forcing people to join this newsletter program, it's all user controlled. So each user saying, yes, you can use my email for your newsletter. You know, I'm supporting your project, want to be kept up to date with bugs or bounties or rewards programs. So really it's just kind of a, a better way for users to, to share the data that they're willing to with dApps and dabs can use it to create all sorts of incentives and really just kind of understand their users on a, on a different level. >>How has the development Michael going on the, on the smart contract side of the business, you know, theories has always been heralded as being very developer focused. There's been great innovations. Just, you still got, you know, gas fees out there. You still gotta do some things. How is the development environment, how are the applications coming? Cause I can see the really, I can see the flywheel kicking in as a developer, Frank gets more streamlined, more efficient, and now you've got the identity piece nailed down. I just see a lot of kind of dominoes falling at the same time. What's the status on the dev side? >>What's your tour? The fascinating thing about crypto is how quickly it changes. You know, when I, when I joined Ethereum was pretty reasonable still for transactions. It was very cheap to get things done very fast. We've looked at last summer that things went completely out of control. This is a big reason that unstoppable for a long time has been working on a layer two and we've moved over to the Pollyanna, our primary source of record, which is built on top of it. The area of course, I think saved well over a hundred million dollars in Gaspe is for our users that we're constantly keeping an eye on new technologies that are emerging, weighing how we can incorporate those things and really where this industry is going to take us. You know, in many ways we are, are just as much passengers as the other people floating around the ecosystem as well. >>Yeah, it's, it's certainly getting faster every day and seeing a huge uptake on a theorem. I heard a stat that most people at the university of California, Berkeley, 30% of the computer science students are dropping out to join web three companies just goes to show you this cultural shift and you can see a lot more companies getting involved. So I got to ask you Charlie, on the biz dev front, how are companies getting started? What's the playbook? Are they putting their toe in the water? Are they jumping in full throttle? What's, what's the, what's the roadmap. What's the best practice for people to get started with unstoppable? >>Absolutely. You know, we're lucky that we get a lot of inbound interest from companies web two and web three because they first want to secure their domains. And we do a ton of work on the backend to protect trademark domains. We want to avoid squatting as much as possible. You know, we don't think that's the spirit of, of weaponry at all. And certainly not what the original intention of the internet was. So fair amount of companies will reach out to, out to us to get their domain. And then we can have a longer conversation about some of the other integrations and ways we can collaborate. So certainly visiting our website and several domains.com is a great starting point. We have an app submission page where asking, reach out to us, even request a grant. We have a grant prop, a program to help developers get started, provide them some resources to, to work with us and integrate some of our technology. >>We have great documentation as well on the site. So you can read all about what it takes to resolve domains, if you're a water and an exchange, as well as what it takes to integrate login within softball, which is actually a super easy integration as well, which we're, we're really excited about. So yeah, I'd say check out the website apply for our grant. If you think you're a fit there, then of course, people can always reach out to me directly on Twitter, on telegram email. We're very reachable and, and we're always happy to chat with projects and, and learn more about what they're doing. >>What's the coolest thing you've seen going on trial with your partners right now. What's, what's the, what's the number one use case that's cool that people are jumping on right now to get in and get some, some, you know, some success out of the gate. >>Yeah. Maybe, maybe gamefied kind of played, earns huge. It's blowing up. And the gaming community is really passionate, vibrant, just expanding like crazy same with there's all this cool new stuff you can do with defy where no matter, you know, how many, how, how big your kind of portfolio is, you're you're able to stake and use all these interesting tools to kind of grow your book. So it's super exciting to see and talk to all these projects and, you know, there's certainly kind of an energy in the community where everyone wants to onboard the general public to web three, right? So we're all working on these school projects, but we need everyone to come over from web to kind of understand the advantages of defy of game fi of having an empty domain. So I'm lucky that I'm kind of one of the first layers there of, of meeting new projects and kind of helping them get access to more users so that they can grow along with. >>Yeah. I remember the early days of Bitcoin and Ethereum, we were giving it away to give the, the community manager was give a, give a Bitcoin to someone that was when it was, you can actually give a Bitcoin to someone what's the, what's the word of mouth or organic viral. I won't say growth hack because that's got negative connotations, but what's the community's way of putting forth the mission for unstoppable. Is it just more domains you guys have any programs got going on? Is it give it away? I'll see you, you can get domains on your site, but what's the, what's the way to get people in gray shaded in and getting comfortable. >>Yeah. So much of what we do is really just all of that, to all that question, to answer that question, we spent a ton of time and energy just on education and whether that's specifically around domains or just general led three, we have a podcast which is pretty exceptional, which talks to what three leaders from across the space and makes the projects that they're working on more accessible. I think we passed over a hundred episodes, not too long ago. There's a ton of stuff that we do that other people do. If anyone has questions, I'm happy to talk about resources. >>Yeah. The part I think you guys are up to one 17, but that's a deep dive that you guys go deep on the podcast. So that's, you know, where you go in, what else is new on digital identity? Where do you guys see the future going now that you get the baseline identity with the NFT? It makes a lot of sense. Create innovation. Good logic makes sense. Solid. Technically what's next. >>Yeah. I think that's really boils down to the way that the internet has grown. Doesn't really feel like the way that the internet should be like our data shouldn't live in these walled gardens controlled by these large companies. Like ultimately people should be responsible for their own identity it's they should have control over the things that they do online, the data that's shared or the benefit of that data. And so the world that we are working towards is very much that where we are giving people the ability to be paid for sharing their data with companies, we're giving applications, the ability to request information from the people that use those applications to improve their experience. We're really just trying to make connections across the ecosystem, through these products to enable a better experience for everyone. So whether that's the, the use cases that I mentioned already, or maybe viewing reviews on something like Yelp or Amazon that just confirmed that the person that you are looking at is actually a real person, not some bot that's been paid to to the loader review. Like the, the interesting thing about these products is they're so universally applicable, applicable. There are so many different games that we can try to plug them in. So have >>It's a great example. It's double-edged sword. You can have a, a metaverse image and have pre-programmed conversations with, with, you know, liquid audio and the video application, you know, or it's a real person. How do you know the difference? You, these are going to be questions, you know, around, around who solves that problem. Now this is time for bots and is it time not for bots? We all know what happens when you get into the, you know, the game of manipulation, but also it can be helpful. This is where you gotta be smart and identity is critical in this future. Charlie, what's your reaction to the future of digital identity? I mean so much to look at here on the trajectory. >>Yeah. You know, I think a big part of it is data portability, right? If you go to a site like Instagram, you're giving them all this content that's very personal to you and you can't just pack up and leave Instagram. So we want a future where most of these apps are just kind of a front end and you can navigate from one to the other and bring your data with you and not be beholden to the companies that operate centralized servers. So I think data portability is huge and it's going to open up a lot of doors. And, and just going back to that thought on kind of cleaning up web two for a better web three. When I think about the Amazons, the Alps, the Yelps of the world, they're all these bots are all these awful fake reviews. There's a lot of gamification happening that is really just creating a lot of noise. >>And I want to bring kind of transparency back to the internet, where when you see a review, you should know that that's a real human and blockchain technology is enabling us to do that. And certainly enough, two domains are going to play a huge part of that. So I think that having an experience where, you know, and trust the people that you're interacting with is going to be really powerful and just a better experience for everyone. And there's a lot of ramifications with that. You know, politically speaking, we've, we've all seen all the issues with kind of attacking communities and using bots and fake accounts to kind of hit people's pain points is it's kind of sad and, and certainly not something that we want to see continue happening. So whatever we can do to kind of give people their digital identity and help people understand that this is a real person on the other end, I think is huge for, for the future of the internet and really for society as well. >>That's a great call out there. Charlie cleaning up the mess of web 2.0 web two. Well, actually I was, it was 2.0 technically now web three is no nos 0.0 in it, but, but I saw on our listen to the podcast with Matt, this recent one, and he had a great metaphor that went back to when I was growing up in the internet, you got IP addresses, right? And the mess there was, it was, you couldn't find what you want to look and no one could remember what to type in. Cause you can type in IP addresses in the browser back then. And then DNS came out and then keywords that's web. Okay. Now that mess now is fraud. Misinformation, bot manipulation, deep fakes, many other kind of unwanted kind of time to innovate. And every year, every time you had these inflection points, there'd be an abstraction on top of it. So similar thing happening here is that you guys see it too. >>Yeah. I think we're going back to some of the foundational architecture of the internet DNS and really bringing that forward about 30, 40 years in terms of technology. So loading in some work cryptography and some other fancy things to help patch some of those issues from the previous versions of the web. >>Yeah. Awesome. Well guys, thanks so much for coming on and the spirit of our tick talk, you know, I'm only summarize this. Can you guys give us a quick tick tock moment, short comment on, you know, where this is all going, whereas log-in single sign on mean and what should people do to take steps to secure their digital identity? >>Sure. I'll jump in here. So it's time for people to secure their digital identity. That great first step has gone on several domains and getting an entity domain. You know, you can control your data. You can do a lot of cool different things with your domain, including posting your own website that you own forever. And no one can take it away from you. I would certainly recommend the people join. Our discord, telegram community is check out our podcasts. It's really great. Especially if you're new to crypto web three, you know, we do a great job of sort of explaining all the basic concepts and expanding on them. So yeah, I'd say, you know, the time is now, so to get your digital identity and start embracing web three, because it's really exploding right now. And there's just so many incredible advantages, especially for the user, >>Michael, what's your take? >>I mean, I put not, I've said it better myself. >>Like we always say, if you're not on the next wave, your driftwood, and this is a big wave it's happening. It's pretty clear guys. It's it's there, it's happening now. And again, very pragmatic implementations of solving problems. The sign-on the app integration. Congratulations. And we've got our cube domain too, by the way. So we're we're I think we're good. You know, so we've got to put it to you. It's appreciate it, Charlie, Michael, thanks for coming on and sharing the update. Okay. This is the cube with unstoppable domains partner showcase, shout for your hosts. Got a lot of other great interviews. Check them out. We're going to continue our coverage and continue on with this great showcase. Thanks for watching.

(joyful music) >> According to storage guru, Fred Moore, 60 to 80% of all stored data is archival data, leading to the need for what he calls the infinite archive. And in this world, digital customers require inexpensive access to archive data that's protected, it's got to be available, durable, it's got to be able to scale and also has to support the governance and compliance edicts of the organizations. Welcome to this next session of the AWS Storage Day with theCUBE. I'm your host, Dave Vellante. We're going to dig into the topic of archiving and digitally preserving data and we're joined by Joe Fitzgerald, who's the general manager of Amazon S3 Glacier. Joe, welcome to the program. >> Hey, Dave. It's great to be here. Thanks for having me. >> Okay, I remember early last decade, AWS announced Glacier, it got a lot of buzz. And since then you've evolved your archival storage services, strategy and offerings. First question: why should customers archive their data in AWS? >> That's a great question. I think Amazon S3 Glacier is a great place for customers to archive data. And I think the preface that you gave, I think, covers a lot of the reasons why customers are looking to archive data on the cloud. We're finding a lot of customers have a lot of data. And if you think about it, most of the world's data is cold by nature. It's not data that you're accessing all the time. So if you don't have an archival story as part of your data strategy, I think you're missing out on a cost savings opportunity. So one of the reasons we're finding customers looking to move data to S3 Glacier is because of cost. With Glacier Deep Archive, we have an industry-leading price point of a dollar per terabyte per month. I think another reason that we're finding customers wanting to move data to the cloud, into Glacier, is because of the security, durability and availability that we offer. Instead of having to worry about some of the most valuable data that your company has and worrying about that being in a tape library that doesn't get access very often on premises or offsite in a data locker that you don't really have access to, and we offer the best story in terms of the durability and security and availability of that data. And I think the other reason that we're finding customers wanting to move data to S3 Glacier is just the flexibility and agility that having your data in the cloud offers. A lot of the data, you can put it in Deep Archive and have it sit there and not access it but then if you have some sort of event that you want to access that data, you can get that back very quickly, as well as put the power the rest of the AWS offerings, whether that's our compute offerings, our machine learning and analytics offerings. So you just have unmatched flexibility, cost, and durability of your data. So we're finding a lot of customers looking to optimize their business by moving their archive data to the cloud. >> So let's stick on the business case for a minute. You nailed the cost side of the equation. Clearly, you mentioned several of the benefits, but for those customers that may not be leaning in to archive data, how do they think about the cost-benefit analysis when you talk to customers, what are you hearing from them, the ones that have used your services to archive data, what are the benefits that they're getting? >> It's a great question. I think we find customers fall into a few different camps and use cases and one thing that we recommend as a starting point is if you have a lot of data and you're not really familiar with your access patterns, like what part of the data is warm, what part is cold? We offer a storage class called S3 intelligent tiering. And what that storage class does is it optimizes the placement of that data and the cost of that data based on the access patterns. So if it's data that is accessed very regularly, it'll sit in one of the warmer storage tiers. If it's accessed infrequently, it'll move down into the infrequent access tier or to the archive or deep archive access tiers. So it's a great way for customers who are struggling to think about archive, because it's not something that every customer thinks about everyday, to get automatic cost savings. And then for customers who have either larger amounts of data or better understand the access patterns, like some of the industries that we're seeing, like autonomous vehicles, they might generate tons of training data from running the autonomous vehicles. And they know, okay, this data, we're not actively using it, but it's also very valuable. They don't want to throw it away. They'll choose to move that data into an archive tier. So a lot of it comes down to the degree to which you're able to easily understand the access pattern of the data to figure out which storage class and which archive storage class maps best to your use case. >> I get it, so if you add that deep archive tier, you automagically get the benefit, thanks to the intelligent tiering. What about industry patterns? I mean, obviously, highly regulated industries have compliance issues and you have data intensive industries are going to potentially have this because they want to lower costs, but do you see any patterns emerging? I mean every industry needs this, but are there any industries that are getting more bang from the buck that you see? >> I would say every industry definitely has archived data. So we have customers in every vertical segment. I think some of the ones that we're definitely seeing more activity from would be media and entertainment customers are a great fit for archive. If you think about even digital native studios who are generating very high definition footage and they take all that footage, they produce the movie, but they have a lot of original data that they might reuse, that you remaster, director's cut, to use later, they're finding archive is a great fit for that. So they're able to use S3 Standard for their active production, but when they're done finishing a movie or production, they can save all that valuable original footage and move it in deep archive and just know that it's going to be there whenever they might need to use it. Another use case, we're staying in media, entertainment, similar to that and this is a good use case for S3 Glacier is if you have sports footage from like the '60s and then there's some sort of breaking news event about some athlete that you want to be able to cut a shot for the six o'clock news, with S3 Glacier and expedited retrievals, you're able to get that data back in a couple of minutes and that way you have the benefit of very low cost archive storage, but being able to get the immediacy of having some of that data back when you need it. So that's just some of the examples that we're seeing in terms of how customers are using archives. >> I love that example because the prevailing wisdom is the older data is, the less valuable it is, but if you can pull a clip up of Babe Ruth at the right time, even though it's a little grainy, wow, that's huge value for the-- >> We're finding like lots of customers that they've retained this data, they haven't known why they're going to need it, they just intrinsically know this data is really valuable, we might need it. And then as they look for new opportunities and they're like, hey, we're going to remaster this. And they've gone through a lot of digital transformation. So we're seeing companies have decades of original material moving into the cloud. We're also seeing fairly nascent startups who are also just generating lots of archive data. So it's just one of the many use cases we see from our customers love Glacier. >> Data hoarders heaven. I love it. Okay, Joe. Let's wrap up. Give us your closing thoughts, how you see the future of this business, where you want to take your business for your customers. >> Mostly, we just really want to help customers optimize their storage and realize the potential of their data. So for a lot of customers, that really just comes down to knowing that S3 glacier is a great and trusted place for their data, and that they're able to meet their compliance and regulatory needs, but for a lot of other customers, they're looking to transform their business and reinvent themselves as they move to the cloud. And I think we're just excited by a lot of emerging use cases and being able to find that flexibility of having very low cost storage, as well as being able to get access to that data and hook it up into the other AWS services and really realize the potential of their data. >> 100%, we've seen it over the decades, cost drops and use cases explode. Thank you, Joe. Thanks so much for coming on theCUBE. >> Thanks a lot, Dave. It's been great being here. >> All right, keep it right there for more storage and data insights. You're watching AWS Storage Day on theCUBE. (tranquil music)

(upbeat music) >> According to storage guru, Fred Moore, 60 to 80% of all stored data is archival data leading to the need for what he calls the infinite archive, In this world digital customers require inexpensive access to archive data that's protected it's got to be available, durable, it's got to be able to scale and also has to support the governance and compliance edicts of the organizations. Welcome to this next session of the AWS storage day with The Cube. I'm your host, Dave Vellante. We're going to dig into the topic of archiving and digitally preserving data and we're joined by Joe Fitzgerald, who is the general manager of Amazon S3 Glacier, Joe. Welcome to the program. >> Hey Dave, it's great to be here. Thanks for having me. >> Yeah, I remember early last decade, AWS announced Glacier, it got a lot of buzz, and since then you've evolved your archival storage services, strategy and offerings. First question. Why should customers archive their data in AWS? >> That's a great question. I think Amazon S3 Glacier is a great place for customers to archive data and I think the preface that you gave, I think covers a lot of the reasons why customers are looking to archive data on the cloud. We're finding a lot of customers have a lot of data. And if you think about it, most of the world's data is cold by nature. It's not data that you're accessing all the time. So if you don't have an archival story as part of your data strategy, I think you're missing out on a cost savings opportunity. So one of the reasons we're finding customers looking to move data S3 glacier is because of cost with Glacier Deep archive we have an industry leading price point of a dollar per terabyte per month. I think another reason that we're finding customers wanting to move data to the cloud into glacier is because of the security, durability, and availability that we offer. Instead of having to worry about some of the most valuable data that your company has and worrying about that being in a tape library that doesn't get accessed very often on premises or offsite in a, in a data locker that you don't really have access to. And we offer the best story in terms of the durability and security and availability of that data. And I think the other reason that we're finding customers wanting to move data to S3 Glacier is just the flexibility and agility that having your data in the cloud offers. A lot of the data, you can put it in deep archive and have it sit there and not access it, but then if you have, you know, some sort of event that you want to access that data, you can get that back very quickly, as well as put to power the rest of the AWS offerings, whether that's our compute offerings, or our machine learning and analytics offerings. So you just have like unmatched, you know, flexibility, cost, and durability of your data. So we're finding a lot of customers looking to optimize their business by moving their archive data to the cloud. >> Let's stick on the business case for a minute. I mean, you kind of nailed the cost side of the equation. Clearly you mentioned several of the benefits, but, but for those customers that may not be leaning in to, to, to archive data, how do they think about the cost benefit analysis when you talk to customers, what are you hearing from them? The ones that have used your services to archive data, what are the benefits that they're getting? >> It's a great question. I think we find customers fall into a few different, you know, camps in use cases. And one thing that we recommend as a starting point is if you have a lot of data and you're not really familiar with your access patterns, like which what, what part of the data is warm, what part is cold, we offer a storage class called S3 intelligent tiering. And what that storage class does is it optimizes the placement of that data and the cost of that data based on the access patterns. So if, if it's data that is accessed very regularly, it'll sit in one of the warmer storage tiers. If it's, accessed infrequently, it'll move down into the infrequent access tier or into the archive or deep archive access tiers. So it's a great way for customers who are struggling to think about archive, because it's not something that every customer thinks about every day to get on automatic cost savings. And then for customers who have, you know, either larger amounts of data or, or better understand the access patterns, like, you know, some of the industries that we're seeing like in, you know, autonomous vehicles, you know, they, they might have, they might generate like tons of training data from, from, you know, from running the autonomous vehicles. And they kind of know, okay, this data it's, it's, we're not actively using it, but it's also very valuable. They don't want to throw it away, they'll choose to move that data into an archive tier. So a lot of it kind of comes down to the degree to which you're able to easily understand the access pattern of the data to figure out which storage class and which archive storage class match best to your use case. >> I get it, so if you add that deep archive tier, you auto-magically get the benefit thanks to the intelligent tiering. What about industry patterns? I mean, obviously highly regulated industries have compliance issues. You know,, data intensive industries are going to potentially have this because they want to lower lower costs, but do you see any patterns emerging? I mean, every industry kind of needs this, but, but are there any industries that are getting more bang from the buck that, that you see? >> I would say every industry definitely has archived data. So we have, we have customers in every vertical segment. I think some of the ones that we're definitely seeing more activity from would be, you know, media and entertainment customers are a great fit for archive. If you think about, you know, even like digital native studios who are, you know, generate, you know, very high definition footage and, you know, they take all that footage, they produce the movie, but they have a lot of original data that they, you know, they, they might reuse. You know, remaster director's cut or, you know, to use later. They're finding archive is a great fit for that. So they're able to use S3 standard for their active production, but when they're done finishing a movie or production, they can save all that valuable original footage and move it into deep archive and just know that it's going to be there whenever they might need to use it. Another use case for staying in media entertainment, you know, kind of similar to that. And this is a good use case for S3 Glacier is if, if you have like sports footage from like the '60s, and then, you know, there's like some sort of breaking news event about some athlete that you want to be able to cut a shot for the six o'clock news, with S3 Glacier and expedited retrievals, you're able to kind of get like that, you know, that data back in a couple of minutes and that way you have the benefit of like very low cost archive storage, but being able to get the immediacy of having some of that data back when you need it. So, that's just some of the examples that we're seeing in terms of how customers are using archives. >> I love that example because, you know, the, the prevailing wisdom is the older, you know, data is the less valuable it is, but if you can pull a clip up of, you know, Babe Ruth at the right time, even though it's a little grainy, wow. That's huge value for the-- >> Yeah, I mean, we're, we're finding like lots of customers that, you know, they've retained this data, they haven't known why they're going to need it. They just sort of intrinsically know this data is really valuable and, you know, we might need it. And then as they, you know, they look for new opportunities and they're like, hey, you know, we're, we're going to remaster this and they they've gone through a lot of digital transformation. So we're seeing companies have, you know, decades of original material moving to the cloud where we're also seeing, you know, fairly new startups who are also just generating lots of archive data. So it's just, you know, one of the many use cases we see from our customers who love Glacier. >> Data hoarder's heaven, I love it. Okay, Joe, let's wrap up, give us your closing thoughts, how you see the future of this business, where you want to take, take your, your business for your customers. >> I think mostly we, we just really want to help customers optimize their storage and realize the potential of their data. So for a lot of customers that really just comes down to knowing that S3 Glacier is a great and trusted place for their data, and that they're able to kind of meet their compliance and regulatory needs, but for, you know, a lot of other customers, they're, they're looking to kind of transform their business and reinvent themselves as they move to the cloud, and I think we're just excited by a lot of emerging use cases, and, you know, being able to find that flexibility of having like very low cost storage, as well as being able to get access to that data and, hook it up into the other AWS services and really realize the potential of their data. >> 100%, I mean, we've seen it over the decades, cost drops and use cases explode. Thank you, Joe. Thanks so much for coming on The Cube. >> Thanks a lot, Dave, it's been great being here. >> All right keep it right there for more storage and data insights. You're watching AWS Storage Day on The Cube. (upbeat music)

(joyful music) >> According to storage guru, Fred Moore, 60 to 80% of all stored data is archival data, leading to the need for what he calls the infinite archive. And in this world, digital customers require inexpensive access to archive data that's protected, it's got to be available, durable, it's got to be able to scale and also has to support the governance and compliance edicts of the organizations. Welcome to this next session of the AWS Storage Day with theCUBE. I'm your host, Dave Vellante. We're going to dig into the topic of archiving and digitally preserving data and we're joined by Joe Fitzgerald, who's the general manager of Amazon S3 Glacier. Joe, welcome to the program. >> Hey, Dave. It's great to be here. Thanks for having me. >> Okay, I remember early last decade, AWS announced Glacier, it got a lot of buzz. And since then you've evolved your archival storage services, strategy and offerings. First question: why should customers archive their data in AWS? >> That's a great question. I think Amazon S3 Glacier is a great place for customers to archive data. And I think the preface that you gave, I think, covers a lot of the reasons why customers are looking to archive data on the cloud. We're finding a lot of customers have a lot of data. And if you think about it, most of the world's data is cold by nature. It's not data that you're accessing all the time. So if you don't have an archival story as part of your data strategy, I think you're missing out on a cost savings opportunity. So one of the reasons we're finding customers looking to move data to S3 Glacier is because of cost. With Glacier Deep Archive, we have an industry-leading price point of a dollar per terabyte per month. I think another reason that we're finding customers wanting to move data to the cloud, into Glacier, is because of the security, durability and availability that we offer. Instead of having to worry about some of the most valuable data that your company has and worrying about that being in a tape library that doesn't get access very often on premises or offsite in a data locker that you don't really have access to, and we offer the best story in terms of the durability and security and availability of that data. And I think the other reason that we're finding customers wanting to move data to S3 Glacier is just the flexibility and agility that having your data in the cloud offers. A lot of the data, you can put it in Deep Archive and have it sit there and not access it but then if you have some sort of event that you want to access that data, you can get that back very quickly, as well as put the power the rest of the AWS offerings, whether that's our compute offerings, our machine learning and analytics offerings. So you just have unmatched flexibility, cost, and durability of your data. So we're finding a lot of customers looking to optimize their business by moving their archive data to the cloud. >> So let's stick on the business case for a minute. You nailed the cost side of the equation. Clearly, you mentioned several of the benefits, but for those customers that may not be leaning in to archive data, how do they think about the cost-benefit analysis when you talk to customers, what are you hearing from them, the ones that have used your services to archive data, what are the benefits that they're getting? >> It's a great question. I think we find customers fall into a few different camps and use cases and one thing that we recommend as a starting point is if you have a lot of data and you're not really familiar with your access patterns, like what part of the data is warm, what part is cold? We offer a storage class called S3 intelligent tiering. And what that storage class does is it optimizes the placement of that data and the cost of that data based on the access patterns. So if it's data that is accessed very regularly, it'll sit in one of the warmer storage tiers. If it's accessed infrequently, it'll move down into the infrequent access tier or to the archive or deep archive access tiers. So it's a great way for customers who are struggling to think about archive, because it's not something that every customer thinks about everyday, to get automatic cost savings. And then for customers who have either larger amounts of data or better understand the access patterns, like some of the industries that we're seeing, like autonomous vehicles, they might generate tons of training data from running the autonomous vehicles. And they know, okay, this data, we're not actively using it, but it's also very valuable. They don't want to throw it away. They'll choose to move that data into an archive tier. So a lot of it comes down to the degree to which you're able to easily understand the access pattern of the data to figure out which storage class and which archive storage class maps best to your use case. >> I get it, so if you add that deep archive tier, you automagically get the benefit, thanks to the intelligent tiering. What about industry patterns? I mean, obviously, highly regulated industries have compliance issues and you have data intensive industries are going to potentially have this because they want to lower costs, but do you see any patterns emerging? I mean every industry needs this, but are there any industries that are getting more bang from the buck that you see? >> I would say every industry definitely has archived data. So we have customers in every vertical segment. I think some of the ones that we're definitely seeing more activity from would be media and entertainment customers are a great fit for archive. If you think about even digital native studios who are generating very high definition footage and they take all that footage, they produce the movie, but they have a lot of original data that they might reuse, that you remaster, director's cut, to use later, they're finding archive is a great fit for that. So they're able to use S3 Standard for their active production, but when they're done finishing a movie or production, they can save all that valuable original footage and move it in deep archive and just know that it's going to be there whenever they might need to use it. Another use case, we're staying in media, entertainment, similar to that and this is a good use case for S3 Glacier is if you have sports footage from like the '60s and then there's some sort of breaking news event about some athlete that you want to be able to cut a shot for the six o'clock news, with S3 Glacier and expedited retrievals, you're able to get that data back in a couple of minutes and that way you have the benefit of very low cost archive storage, but being able to get the immediacy of having some of that data back when you need it. So that's just some of the examples that we're seeing in terms of how customers are using archives. >> I love that example because the prevailing wisdom is the older data is, the less valuable it is, but if you can pull a clip up of Babe Ruth at the right time, even though it's a little grainy, wow, that's huge value for the-- >> We're finding like lots of customers that they've retained this data, they haven't known why they're going to need it, they just intrinsically know this data is really valuable, we might need it. And then as they look for new opportunities and they're like, hey, we're going to remaster this. And they've gone through a lot of digital transformation. So we're seeing companies have decades of original material moving into the cloud. We're also seeing fairly nascent startups who are also just generating lots of archive data. So it's just one of the many use cases we see from our customers love Glacier. >> Data hoarders heaven. I love it. Okay, Joe. Let's wrap up. Give us your closing thoughts, how you see the future of this business, where you want to take your business for your customers. >> Mostly, we just really want to help customers optimize their storage and realize the potential of their data. So for a lot of customers, that really just comes down to knowing that S3 glacier is a great and trusted place for their data, and that they're able to meet their compliance and regulatory needs, but for a lot of other customers, they're looking to transform their business and reinvent themselves as they move to the cloud. And I think we're just excited by a lot of emerging use cases and being able to find that flexibility of having very low cost storage, as well as being able to get access to that data and hook it up into the other AWS services and really realize the potential of their data. >> 100%, we've seen it over the decades, cost drops and use cases explode. Thank you, Joe. Thanks so much for coming on theCUBE. >> Thanks a lot, Dave. It's been great being here. >> All right, keep it right there for more storage and data insights. You're watching AWS Storage Day on theCUBE. (tranquil music)

(upbeat music) >> Okay, Chloe, thank you very much. Hey folks, in here in the Cloud City We with Danielle Royston. Great to see you. Watching you up on stage, I got to say, as the CEO of TelcoDR, leader and chief executive of that company. As well as a great visionary, you laid out the vision. It's hard to debate that. I mean, I think there's people who will say that vision, is like freedom, no one can debate it. It's not going to happen. >> Yeah, there's still a lot of debate in our industry about it. There's a lot of articles being written about it. I've referenced one about, you know, should we let the dragons into the castle? For me, I think it's super obvious. I think other industries are like "Duh, we've made the move." And Telco is still like, "Hmm, we're not sure." And so, am I a visionary, I don't know. I'm just sort of just Babe Ruth-ing it a little bit. I think that's where we're going. >> You know you do, you have a lot of content, podcasts, you write blogs, you do a lot of speaking. You brought it all together on stage, right? That has got to feel good. >> Yeah. >> You've got a body of work and it came together very nicely. How did you feel up there? >> Oh my God, it's absolutely nerve wrecking. I sort of feel like, you know, could you tell if my hands were shaking? Right, could you tell that my heart was racing? >> It's a good feeling. >> I don't know. >> Come on! >> I'll be honest, I'm happy it's over, I'm happy. I think I did a really great job and I'm really happy >> Yeah, you did a great job, I love the dragon reference-- >> Have it in the can. >> Fantastic, loved the Game of Thrones vibe there. It was cool-- >> Totally. >> One of the things I wanted pick up on, I thought it was very interesting and unique was the iPhone reference 14 years ago, because that really, to me, was a similar moment because that shifted the smartphone. A computer that happened to make phone calls. And then we all knew who was the leader at that time, Nokia, Blackberry with the phones, and they became toast. That ushered in a whole another era of change, wealth creation, innovation, new things. >> Yeah. Well, up until that moment, carriers had been designing the phones themselves. They were branded with their logos. And so Steve Jobs fought for the design of the iPhone. He designed it with the consumer, with the user in mind. But I think what it really, I mean, it's such a big pivotal moment in our industry because it singled the end of voice revenue and ushered in the era of data. But it also introduced the OTT players, right? That came in through the apps and started a siphon approved from the carriers. And this is like, it's a pivotal moment in the industry, like, changed the industry forever. >> It's a step function, it was a step function change, it's obvious, everyone knew it. But what's interesting is that we were riffing yesterday about O-RAN and Android. So you have iPhone, but Android became a very successful open source project that changed the landscape of the handset. Some are saying that that kind of phenomenon is coming here. Into Telco with software, kind of like an Android model where that'll come in. What's your thoughts on that, reaction to that? >> Yeah, well the dis-aggregation of the hardware, right? We're in the iconic Erickson booth, right? They get most of their revenue from RAN, from Radio Access Networks. And now with the introduction of Open RAN, right? With 50% less CapEx, 40% less OPEX, you know, I think it's easiest for Greenfield operators like Dish, that are building a brand new network. But just this month, Vodafone announced they're going to build the world's largest Open RAN network. Change is happening and the big operators are starting to adopt Open RAN in a real big way. >> So to me, riding the dragon means taking the advantage of new opportunities on top of that dragon. Developing apps like the iPhone did. And you mentioned Android, they got it right. Remember the Windows Phone, right? They tried to take Windows and shove it to the phone-- >> Barely. >> It was a kin phone too. >> I try to delete it from my, look here, beep! >> I'm going to take this old world app and I'm going to shove it into the new world, and guess what, it failed. So if the Telco is trying to do the same thing here, it will fail, but if they start building 5G apps in the cloud and pick the cloud native and think about the consumer, isn't really that the opportunity that you're talking about? >> Well, I think it is, absolutely. And I think it's a wake up call for the vendors in our space, right? And I'm certainly trying to become a vendor with Totogi. I'm really pushing my idea. But you can't take, using your Windows example on the Windows Phone, you can't take a Windows app and stuff it onto a phone and you can't take these old school applications that were written 20 years ago and just stuff them into the cloud, right? Cloud is not a place, it's a way to design applications and it all needs to be rewritten and let's go write, rewrite it. >> It's not a destination as we always say. Let's take a step back on the keynote 'cause I know we just did a couple of highlights there, wasn't the whole thing. We were watching it, by the way, we thought you did a great job, you were very cool and calm under pressure. But take us through the core ideas in the keynote. Break down the core elements of what the talk was about. >> Yeah, I think the headline really is, you know, just like there were good and bad things about the iPhone, right? It killed voice, but introduced data and all these other things. There's good and bad things about the public cloud, right? It's not going to be smooth sailing, no downsides. And so I acknowledge that, even though I'm the self appointed queen, you know? This self appointed evangelist. And so, I think that if you completely ignore the public cloud, try to stick your head in the sand and pretend it doesn't exist, I think there's nothing but downsides for Telcos. And so I think you need to learn how to maximize the advantage there, ride he dragon, like spew some fire and, you know, get some speed and height, and then you can double your ARPU. But I think, going from there, so the next three, I was trying to give examples of what I meant by that, of why it's a double-edged sword, why it's two sides of the coin. And I think there's three areas, which is the enterprise, the network, and a relationship with subscribers. And so that really what the talk, that's what the talk is about >> The three main pillars. >> Yeah, yeah! >> Future, work, enterprise, transition, Open RAN. >> The network and then the relationship with the subscribers. >> Those are the structural elements you see. >> Yeah, yeah, yeah. >> What's the most important one you think, right now, that people are focused on? >> I mean, I think the first one, with work, that's an easy one to do, because there's not too much downside, right? I think we all learned that we could work productively from home. The reason public cloud matter there is because we had tools like Zoom and G Suite and we didn't need to be, I mean, imagine if that this had happened even 20 years ago, right? Broadband at the home wasn't ready, the tools weren't ready. I mean, it would have been, I mean a bigger disaster than it was, right? And so this is an opportunity to sort of ride this work from home wave that a lot of CEOs are saying, we're not coming back or we're going to have smaller offices. And all of those employees need fiber to their home. They need 5G at their home. I mean, if I'm a head of enterprise in a Telco, I am shifting my 5G message from like random applications or whatever, to be like, how are you getting big pipes to the home so your workers can be productive there? And that, I don't hear Telco's talking about that and that's a really big idea. >> You know, you say it's a no brainer, but it's interesting you had your buildings crumbling, which was great, very nice effect in the talk. I heard a executive, Wall Street executive the other day, talking about how, "My people will be back in the office. "I'm going to mandate vaccinations, they're going to be back "in the office, you work for me. "Even though it's an employee friendly environment "right now, I don't care". And I was shocked. I go, okay, this is just an old guy. But, and it's not just the fact that it's an old guy, old guard doing that because I take two examples of old guys, Michael Dell and Frank Slootman. >> Yeah. >> Right, Michael Dell, you know, hundred billion dollar company, Frank Slootman, hottest, you know, software company. Both of them, sort of agree. It's a no brainer. >> Yeah. >> Why should I spend all this money on buildings? And my people are going to be more productive. They love it, so. Why fight the fashion? >> Well, I think the office and I can talk about this for a long time and I know we don't have that much time, but on offices, it's a way to see when did you come in and when did you leave, and look over your shoulder and what we're working on. And that's what offices are for. Now, we tell ourselves it's about collaboration and all this other stuff. And you know, these guys are saying, "come back to the office." It's because they don't have an answer on how to manage productivity. What are you working on? Are you off, are you authentically working 40 hours a week? I want to see, I know if at least you're here, you're here. Now, you might be playing, you know, Minesweeper. You might be playing Minesweeper on your computer, but at least you were, your butt was at your computer. So yeah, I think this is a pivotal moment in work. I think Telcos could push it, to work from home. We'll get you the pipes, we'll get you the cloud-based tools to help manage productivity, to change in work style. >> Yeah, and we've covered this in theCube many times, about how software is going to enable this virtual first model, no one's actually built software for virtual first. I think that's going to happen. Again, back to your team software, but I want to ask you about software defined infrastructure. You mentioned O-RAN, and as software eats the world and eats infrastructure, you still need infrastructure. So, talk about the relationship of how you see O-RAN competing and winning with the balance of software versus the commodity argument. >> Yeah, and I think this is really where people get scared in Telco. I mean, authentically nervous, right. Where you're like, okay, really the public cloud is at that network edge, right? We're really going to like, who are we? It's an identity crisis. We're not the towers anymore. We're renting space, right? We're now dis-aggregating the network, putting the edge cloud right there and it's AWS or Google. Who are we, what do we do, are we networks? Are we a tech company? Right, and so I'm like, guys, you are your subscribers and you don't focus on that. I mean, it's kind of like a last thought. >> So you're like a therapist then too, not just an evangelist. >> I'm a little bit of a therapist. >> Okay, lay down on the couch, Telco. >> Let's talk about what your problems are. (laughs) >> They have tower issues. >> All seriousness, no but, the tower is changing is backhauling. Look at direct connects for instance. The rise of direct and killed the exchanges. I mean, broadband, backhaul, last mile, >> Yeah. >> Completely, still issues, >> Yeah. >> But it's going to software and so that's there. The other thing I want to get to quickly, I know we don't have a lot of time, is the love relationship you talk about with subscribers. We had Peter Adderton on, from a Boost Mobile, formerly Boost Mobile, earlier. He was saying, if you don't have a focus on the customer, then you're just selling minutes and that's it. >> Yeah. >> And his point was, they don't really care. >> Yeah. Let's talk about organizational energy, right? How much energy is contained within any organization, not just Telco, but any organization. To some of your people time is the hours they work per week. And then you think of that as a sack on how you're allocating your time and spending your time, right? And so I think they spend 50% of their time, maybe more, fighting servers, machines, the network, right? And having all these battles. How much of that organizational energy is dedicated to driving great subscriber experiences? And it just shrunk, right? And I think that's where the public cloud can really help them. Like ride the dragon. Let the dragon deal with some of this underlying stuff. So that you can ride a dragon, survey the land, focus on your subscriber and back to the software. Use software, just like the OTT players are doing. They are taking away your ARPU. They're siphoning your ARPU, 'cause they're providing a better customer experience. You need to compete on that dimension. Not the network, not the three Telcos in the country. You're competing again, WhatsApp, Apple, Amazon, Facebook. And you spent how much of your organizational energy to focus on that? Very small. >> And that's where digital platforms roll by, it uses the word platform, why? Because everybody wants to be a platform. Why do you want to be a platform? Because I want to be like Amazon, they're a platform. And you think about Netflix, right? It's not, you know, you don't think about Netflix UK or Netflix Spain, right? >> It's global. >> There's one Netflix >> Yeah, yeah. >> You don't think about their marketing department or their sales department or their customer service, you think about the app. >> Yeah. >> You know. One interface. And that's what digital platforms allow you to do. And granted, there's a lot of public policy to deal with, but if you're shooting satellites up in space, >> Yeah. >> You know, now, you own that space, right, global network. >> And what makes Netflix so good, I think, is that it knows you, right? It knows what you're watching and recommends things, and you're like, "Oh, I would like that, that's great." Who knows more about you than your mobile phone? Carry it everywhere you go, right? What you're watching, what you're doing, who you're calling, what time did you wake up? And right now all of that data we talked about a couple of days ago, it's trapped in siloed old systems. And like why do people think Google knows so much about you? Telco knows about you. And to start to use that to drive a great experience. >> And you've got a great relationship with Netflix. The relationship we have with our our carrier is to your admin, "can you call these guys? "I don't know, I lost the password, I can't get in". >> Right. >> It's like-- >> Or you get SIM hacked-- >> I don't have an hour and a half to call your call center 'cause you don't have a chat bot, right. >> I don't have time. >> Chat bot, right. I can't even do the chat bot because my problem is, you're like, I got to talk to someone. All of their systems are built with the intention of a human being on the other side, and there's all this awesome chat bot AI that works. >> Yeah. >> Set it free. >> Yeah, yeah, right. You almost rather go to the dentist, then calling your carrier. >> Well, we're going to wrap things up here on the keynote review. Did you achieve what you wanted to achieve? I mean, controversy, bold vision, leadership, also that came across, but people they know who you are now. You're out there and that's great news. >> Yeah. I think I rocked the Telco universe and I'm really, that was my goal, and I think I accomplish it so, very excited. >> Well, we love having you on theCUBE. It's great to have great conversations, not only are you dynamic and smart, you're causing a lot of controversy, in a good way and getting, waking people up. >> Making people talk, that's a start. >> And I think, the conversations are there. People are talking and having relationships on the ecosystem open, it's all there. Danielle Royston, you are a digital revolution, DR. Telco DR, thanks for coming to theCube. >> Thank you so much, always fun. >> Good to see you. >> Thanks. >> Of course, back to the Cloud City studios. Adam is going to take it from here and continue on day three of theCube. Adam in studio, thanks for having us and take it from here.

>>Yeah, yeah. >>Welcome back. I'm so excited to introduce our next session empowerment through inclusion, reimagining society and technology. This is a topic that's personally very near and dear to my heart. Did you know that there's only 2% of Latinas in technology as a Latina? I know that there's so much more we could do collectively to improve these gaps and diversity. I thought spot diversity is considered a critical element across all levels of the organization. The data shows countless times. A diverse and inclusive workforce ultimately drives innovation better performance and keeps your employees happier. That's why we're passionate about contributing to this conversation and also partnering with organizations that share our mission of improving diversity across our communities. Last beyond, we hosted the session during a breakfast and we packed the whole room. This year, we're bringing the conversation to the forefront to emphasize the importance of diversity and data and share the positive ramifications that it has for your organization. Joining us for this session are thought spots Chief Data Strategy Officer Cindy Housing and Ruhollah Benjamin, associate professor of African American Studies at Princeton University. Thank you, Paola. So many >>of you have journeyed with me for years now on our efforts to improve diversity and inclusion in the data and analytic space. And >>I would say >>over time we cautiously started commiserating, eventually sharing best practices to make ourselves and our companies better. And I do consider it a milestone. Last year, as Paola mentioned that half the room was filled with our male allies. But I remember one of our Panelists, Natalie Longhurst from Vodafone, suggesting that we move it from a side hallway conversation, early morning breakfast to the main stage. And I >>think it was >>Bill Zang from a I G in Japan. Who said Yes, please. Everyone else agreed, but more than a main stage topic, I want to ask you to think about inclusion beyond your role beyond your company toe. How Data and analytics can be used to impact inclusion and equity for the society as a whole. Are we using data to reveal patterns or to perpetuate problems leading Tobias at scale? You are the experts, the change agents, the leaders that can prevent this. I am thrilled to introduce you to the leading authority on this topic, Rou Ha Benjamin, associate professor of African studies at Princeton University and author of Multiple Books. The Latest Race After Technology. Rou ha Welcome. >>Thank you. Thank you so much for having me. I'm thrilled to be in conversation with you today, and I thought I would just kick things off with some opening reflections on this really important session theme. And then we could jump into discussion. So I'd like us to as a starting point, um, wrestle with these buzzwords, empowerment and inclusion so that we can have them be more than kind of big platitudes and really have them reflected in our workplace cultures and the things that we design in the technologies that we put out into the world. And so to do that, I think we have to move beyond techno determinism, and I'll explain what that means in just a minute. Techno determinism comes in two forms. The first, on your left is the idea that technology automation, um, all of these emerging trends are going to harm us, are going to necessarily harm humanity. They're going to take all the jobs they're going to remove human agency. This is what we might call the techno dystopian version of the story and this is what Hollywood loves to sell us in the form of movies like The Matrix or Terminator. The other version on your right is the techno utopian story that technologies automation. The robots as a shorthand, are going to save humanity. They're gonna make everything more efficient, more equitable. And in this case, on the surface, he seemed like opposing narratives right there, telling us different stories. At least they have different endpoints. But when you pull back the screen and look a little bit more closely, you see that they share an underlying logic that technology is in the driver's seat and that human beings that social society can just respond to what's happening. But we don't really have a say in what technologies air designed and so to move beyond techno determinism the notion that technology is in the driver's seat. We have to put the human agents and agencies back into the story, the protagonists, and think carefully about what the human desires worldviews, values, assumptions are that animate the production of technology. And so we have to put the humans behind the screen back into view. And so that's a very first step and when we do that, we see, as was already mentioned, that it's a very homogeneous group right now in terms of who gets the power and the resource is to produce the digital and physical infrastructure that everyone else has to live with. And so, as a first step, we need to think about how to create more participation of those who are working behind the scenes to design technology now to dig a little more a deeper into this, I want to offer a kind of low tech example before we get to the more hi tech ones. So what you see in front of you here is a simple park bench public bench. It's located in Berkeley, California, which is where I went to graduate school and on this particular visit I was living in Boston, and so I was back in California. It was February. It was freezing where I was coming from, and so I wanted to take a few minutes in between meetings to just lay out in the sun and soak in some vitamin D, and I quickly realized, actually, I couldn't lay down on this bench because of the way it had been designed with these arm rests at intermittent intervals. And so here I thought. Okay, the the armrest have, ah functional reason why they're there. I mean, you could literally rest your elbows there or, um, you know, it can create a little bit of privacy of someone sitting there that you don't know. When I was nine months pregnant, it could help me get up and down or for the elderly, the same thing. So it has a lot of functional reasons, but I also thought about the fact that it prevents people who are homeless from sleeping on the bench. And this is the Bay area that we were talking about where, in fact, the tech boom has gone hand in hand with a housing crisis. Those things have grown in tandem. So innovation has grown within equity because we haven't thought carefully about how to address the social context in which technology grows and blossoms. And so I thought, Okay, this crisis is growing in this area, and so perhaps this is a deliberate attempt to make sure that people don't sleep on the benches by the way that they're designed and where the where they're implemented and So this is what we might call structural inequity. By the way something is designed. It has certain effects that exclude or harm different people. And so it may not necessarily be the intense, but that's the effect. And I did a little digging, and I found, in fact, it's a global phenomenon, this thing that architects called hostile architecture. Er, I found single occupancy benches in Helsinki, so only one booty at a time no laying down there. I found caged benches in France. And in this particular town. What's interesting here is that the mayor put these benches out in this little shopping plaza, and within 24 hours the people in the town rallied together and had them removed. So we see here that just because we have, uh, discriminatory design in our public space doesn't mean we have to live with it. We can actually work together to ensure that our public space reflects our better values. But I think my favorite example of all is the meter bench. In this case, this bench is designed with spikes in them, and to get the spikes to retreat into the bench, you have to feed the meter you have to put some coins in, and I think it buys you about 15 or 20 minutes. Then the spikes come back up. And so you'll be happy to know that in this case, this was designed by a German artists to get people to think critically about issues of design, not just the design of physical space but the design of all kinds of things, public policies. And so we can think about how our public life in general is metered, that it serves those that can pay the price and others are excluded or harm, whether we're talking about education or health care. And the meter bench also presents something interesting. For those of us who care about technology, it creates a technical fix for a social problem. In fact, it started out his art. But some municipalities in different parts of the world have actually adopted this in their public spaces in their parks in order to deter so called lawyers from using that space. And so, by a technical fix, we mean something that creates a short term effect, right. It gets people who may want to sleep on it out of sight. They're unable to use it, but it doesn't address the underlying problems that create that need to sleep outside in the first place. And so, in addition to techno determinism, we have to think critically about technical fixes that don't address the underlying issues that technology is meant to solve. And so this is part of a broader issue of discriminatory design, and we can apply the bench metaphor to all kinds of things that we work with or that we create. And the question we really have to continuously ask ourselves is, What values are we building in to the physical and digital infrastructures around us? What are the spikes that we may unwittingly put into place? Or perhaps we didn't create the spikes. Perhaps we started a new job or a new position, and someone hands us something. This is the way things have always been done. So we inherit the spike bench. What is our responsibility when we noticed that it's creating these kinds of harms or exclusions or technical fixes that are bypassing the underlying problem? What is our responsibility? All of this came to a head in the context of financial technologies. I don't know how many of you remember these high profile cases of tech insiders and CEOs who applied for Apple, the Apple card and, in one case, a husband and wife applied and the husband, the husband received a much higher limit almost 20 times the limit as his wife, even though they shared bank accounts, they lived in Common Law State. And so the question. There was not only the fact that the husband was receiving a much better interest rate and the limit, but also that there was no mechanism for the individuals involved to dispute what was happening. They didn't even know what the factors were that they were being judged that was creating this form of discrimination. So in terms of financial technologies, it's not simply the outcome that's the issue. Or that could be discriminatory, but the process that black boxes, all of the decision making that makes it so that consumers and the general public have no way to question it. No way to understand how they're being judged adversely, and so it's the process not only the product that we have to care a lot about. And so the case of the apple cart is part of a much broader phenomenon of, um, racist and sexist robots. This is how the headlines framed it a few years ago, and I was so interested in this framing because there was a first wave of stories that seemed to be shocked at the prospect that technology is not neutral. Then there was a second wave of stories that seemed less surprised. Well, of course, technology inherits its creator's biases. And now I think we've entered a phase of attempts to override and address the default settings of so called racist and sexist robots, for better or worse. And here robots is just a kind of shorthand, that the way people are talking about automation and emerging technologies more broadly. And so as I was encountering these headlines, I was thinking about how these air, not problems simply brought on by machine learning or AI. They're not all brand new, and so I wanted to contribute to the conversation, a kind of larger context and a longer history for us to think carefully about the social dimensions of technology. And so I developed a concept called the New Jim Code, which plays on the phrase Jim Crow, which is the way that the regime of white supremacy and inequality in this country was defined in a previous era, and I wanted us to think about how that legacy continues to haunt the present, how we might be coding bias into emerging technologies and the danger being that we imagine those technologies to be objective. And so this gives us a language to be able to name this phenomenon so that we can address it and change it under this larger umbrella of the new Jim Code are four distinct ways that this phenomenon takes shape from the more obvious engineered inequity. Those were the kinds of inequalities tech mediated inequalities that we can generally see coming. They're kind of obvious. But then we go down the line and we see it becomes harder to detect. It's happening in our own backyards. It's happening around us, and we don't really have a view into the black box, and so it becomes more insidious. And so in the remaining couple minutes, I'm just just going to give you a taste of the last three of these, and then a move towards conclusion that we can start chatting. So when it comes to default discrimination. This is the way that social inequalities become embedded in emerging technologies because designers of these technologies aren't thinking carefully about history and sociology. Ah, great example of this came Thio headlines last fall when it was found that widely used healthcare algorithm affecting millions of patients, um, was discriminating against black patients. And so what's especially important to note here is that this algorithm healthcare algorithm does not explicitly take note of race. That is to say, it is race neutral by using cost to predict healthcare needs. This digital triaging system unwittingly reproduces health disparities because, on average, black people have incurred fewer costs for a variety of reasons, including structural inequality. So in my review of this study by Obermeyer and colleagues, I want to draw attention to how indifference to social reality can be even more harmful than malicious intent. It doesn't have to be the intent of the designers to create this effect, and so we have to look carefully at how indifference is operating and how race neutrality can be a deadly force. When we move on to the next iteration of the new Jim code coded exposure, there's attention because on the one hand, you see this image where the darker skin individual is not being detected by the facial recognition system, right on the camera or on the computer. And so coated exposure names this tension between wanting to be seen and included and recognized, whether it's in facial recognition or in recommendation systems or in tailored advertising. But the opposite of that, the tension is with when you're over included. When you're surveiled when you're to centered. And so we should note that it's not simply in being left out, that's the problem. But it's in being included in harmful ways. And so I want us to think carefully about the rhetoric of inclusion and understand that inclusion is not simply an end point. It's a process, and it is possible to include people in harmful processes. And so we want to ensure that the process is not harmful for it to really be effective. The last iteration of the new Jim Code. That means the the most insidious, let's say, is technologies that are touted as helping US address bias, so they're not simply including people, but they're actively working to address bias. And so in this case, There are a lot of different companies that are using AI to hire, create hiring software and hiring algorithms, including this one higher view. And the idea is that there there's a lot that AI can keep track of that human beings might miss. And so so the software can make data driven talent decisions. After all, the problem of employment discrimination is widespread and well documented. So the logic goes, Wouldn't this be even more reason to outsource decisions to AI? Well, let's think about this carefully. And this is the look of the idea of techno benevolence trying to do good without fully reckoning with what? How technology can reproduce inequalities. So some colleagues of mine at Princeton, um, tested a natural learning processing algorithm and was looking to see whether it exhibited the same, um, tendencies that psychologists have documented among humans. E. And what they found was that in fact, the algorithm associating black names with negative words and white names with pleasant sounding words. And so this particular audit builds on a classic study done around 2003, before all of the emerging technologies were on the scene where two University of Chicago economists sent out thousands of resumes to employers in Boston and Chicago, and all they did was change the names on those resumes. All of the other work history education were the same, and then they waited to see who would get called back. And the applicants, the fictional applicants with white sounding names received 50% more callbacks than the black applicants. So if you're presented with that study, you might be tempted to say, Well, let's let technology handle it since humans are so biased. But my colleagues here in computer science found that this natural language processing algorithm actually reproduced those same associations with black and white names. So, too, with gender coded words and names Amazon learned a couple years ago when its own hiring algorithm was found discriminating against women. Nevertheless, it should be clear by now why technical fixes that claim to bypass human biases are so desirable. If Onley there was a way to slay centuries of racist and sexist demons with a social justice box beyond desirable, more like magical, magical for employers, perhaps looking to streamline the grueling work of recruitment but a curse from any jobseekers, as this headline puts it, your next interview could be with a racist spot, bringing us back to that problem space we started with just a few minutes ago. So it's worth noting that job seekers are already developing ways to subvert the system by trading answers to employers test and creating fake applications as informal audits of their own. In terms of a more collective response, there's a federation of European Trade unions call you and I Global that's developed a charter of digital rights for work, others that touches on automated and a I based decisions to be included in bargaining agreements. And so this is one of many efforts to change their ecosystem to change the context in which technology is being deployed to ensure more protections and more rights for everyday people in the US There's the algorithmic accountability bill that's been presented, and it's one effort to create some more protections around this ubiquity of automated decisions, and I think we should all be calling from more public accountability when it comes to the widespread use of automated decisions. Another development that keeps me somewhat hopeful is that tech workers themselves are increasingly speaking out against the most egregious forms of corporate collusion with state sanctioned racism. And to get a taste of that, I encourage you to check out the hashtag Tech won't build it. Among other statements that they have made and walking out and petitioning their companies. Who one group said, as the people who build the technologies that Microsoft profits from, we refuse to be complicit in terms of education, which is my own ground zero. Um, it's a place where we can we can grow a more historically and socially literate approach to tech design. And this is just one, um, resource that you all can download, Um, by developed by some wonderful colleagues at the Data and Society Research Institute in New York and the goal of this interventionist threefold to develop an intellectual understanding of how structural racism operates and algorithms, social media platforms and technologies, not yet developed and emotional intelligence concerning how to resolve racially stressful situations within organizations, and a commitment to take action to reduce harms to communities of color. And so as a final way to think about why these things are so important, I want to offer a couple last provocations. The first is for us to think a new about what actually is deep learning when it comes to computation. I want to suggest that computational depth when it comes to a I systems without historical or social depth, is actually superficial learning. And so we need to have a much more interdisciplinary, integrated approach to knowledge production and to observing and understanding patterns that don't simply rely on one discipline in order to map reality. The last provocation is this. If, as I suggested at the start, inequity is woven into the very fabric of our society, it's built into the design of our. Our policies are physical infrastructures and now even our digital infrastructures. That means that each twist, coil and code is a chance for us toe. We've new patterns, practices and politics. The vastness of the problems that we're up against will be their undoing. Once we accept that we're pattern makers. So what does that look like? It looks like refusing color blindness as an anecdote to tech media discrimination rather than refusing to see difference. Let's take stock of how the training data and the models that we're creating have these built in decisions from the past that have often been discriminatory. It means actually thinking about the underside of inclusion, which can be targeting. And how do we create a more participatory rather than predatory form of inclusion? And ultimately, it also means owning our own power in these systems so that we can change the patterns of the past. If we're if we inherit a spiked bench, that doesn't mean that we need to continue using it. We can work together to design more just and equitable technologies. So with that, I look forward to our conversation. >>Thank you, Ruth. Ha. That was I expected it to be amazing, as I have been devouring your book in the last few weeks. So I knew that would be impactful. I know we will never think about park benches again. How it's art. And you laid down the gauntlet. Oh, my goodness. That tech won't build it. Well, I would say if the thoughts about team has any saying that we absolutely will build it and will continue toe educate ourselves. So you made a few points that it doesn't matter if it was intentional or not. So unintentional has as big an impact. Um, how do we address that does it just start with awareness building or how do we address that? >>Yeah, so it's important. I mean, it's important. I have good intentions. And so, by saying that intentions are not the end, all be all. It doesn't mean that we're throwing intentions out. But it is saying that there's so many things that happened in the world, happened unwittingly without someone sitting down to to make it good or bad. And so this goes on both ends. The analogy that I often use is if I'm parked outside and I see someone, you know breaking into my car, I don't run out there and say Now, do you feel Do you feel in your heart that you're a thief? Do you intend to be a thief? I don't go and grill their identity or their intention. Thio harm me, but I look at the effect of their actions, and so in terms of art, the teams that we work on, I think one of the things that we can do again is to have a range of perspectives around the table that can think ahead like chess, about how things might play out, but also once we've sort of created something and it's, you know, it's entered into, you know, the world. We need to have, ah, regular audits and check ins to see when it's going off track just because we intended to do good and set it out when it goes sideways, we need mechanisms, formal mechanisms that actually are built into the process that can get it back on track or even remove it entirely if we find And we see that with different products, right that get re called. And so we need that to be formalized rather than putting the burden on the people that are using these things toe have to raise the awareness or have to come to us like with the apple card, Right? To say this thing is not fair. Why don't we have that built into the process to begin with? >>Yeah, so a couple things. So my dad used to say the road to hell is paved with good intentions, so that's >>yes on. In fact, in the book, I say the road to hell is paved with technical fixes. So they're me and your dad are on the same page, >>and I I love your point about bringing different perspectives. And I often say this is why diversity is not just about business benefits. It's your best recipe for for identifying the early biases in the data sets in the way we build things. And yet it's such a thorny problem to address bringing new people in from tech. So in the absence of that, what do we do? Is it the outside review boards? Or do you think regulation is the best bet as you mentioned a >>few? Yeah, yeah, we need really need a combination of things. I mean, we need So on the one hand, we need something like a do no harm, um, ethos. So with that we see in medicine so that it becomes part of the fabric and the culture of organizations that that those values, the social values, have equal or more weight than the other kinds of economic imperatives. Right. So we have toe have a reckoning in house, but we can't leave it to people who are designing and have a vested interest in getting things to market to regulate themselves. We also need independent accountability. So we need a combination of this and going back just to your point about just thinking about like, the diversity on teams. One really cautionary example comes to mind from last fall, when Google's New Pixel four phone was about to come out and it had a kind of facial recognition component to it that you could open the phone and they had been following this research that shows that facial recognition systems don't work as well on darker skin individuals, right? And so they wanted Thio get a head start. They wanted to prevent that, right? So they had good intentions. They didn't want their phone toe block out darker skin, you know, users from from using it. And so what they did was they were trying to diversify their training data so that the system would work better and they hired contract workers, and they told these contract workers to engage black people, tell them to use the phone play with, you know, some kind of app, take a selfie so that their faces would populate that the training set, But they didn't. They did not tell the people what their faces were gonna be used for, so they withheld some information. They didn't tell them. It was being used for the spatial recognition system, and the contract workers went to the media and said Something's not right. Why are we being told? Withhold information? And in fact, they told them, going back to the park bench example. To give people who are homeless $5 gift cards to play with the phone and get their images in this. And so this all came to light and Google withdrew this research and this process because it was so in line with a long history of using marginalized, most vulnerable people and populations to make technologies better when those technologies are likely going toe, harm them in terms of surveillance and other things. And so I think I bring this up here to go back to our question of how the composition of teams might help address this. I think often about who is in that room making that decision about sending, creating this process of the contract workers and who the selfies and so on. Perhaps it was a racially homogeneous group where people didn't want really sensitive to how this could be experienced or seen, but maybe it was a diverse, racially diverse group and perhaps the history of harm when it comes to science and technology. Maybe they didn't have that disciplinary knowledge. And so it could also be a function of what people knew in the room, how they could do that chest in their head and think how this is gonna play out. It's not gonna play out very well. And the last thing is that maybe there was disciplinary diversity. Maybe there was racial ethnic diversity, but maybe the workplace culture made it to those people. Didn't feel like they could speak up right so you could have all the diversity in the world. But if you don't create a context in which people who have those insights feel like they can speak up and be respected and heard, then you're basically sitting on a reservoir of resource is and you're not tapping into it to ensure T to do right by your company. And so it's one of those cautionary tales I think that we can all learn from to try to create an environment where we can elicit those insights from our team and our and our coworkers, >>your point about the culture. This is really inclusion very different from just diversity and thought. Eso I like to end on a hopeful note. A prescriptive note. You have some of the most influential data and analytics leaders and experts attending virtually here. So if you imagine the way we use data and housing is a great example, mortgage lending has not been equitable for African Americans in particular. But if you imagine the right way to use data, what is the future hold when we've gotten better at this? More aware >>of this? Thank you for that question on DSO. You know, there's a few things that come to mind for me one. And I think mortgage environment is really the perfect sort of context in which to think through the the both. The problem where the solutions may lie. One of the most powerful ways I see data being used by different organizations and groups is to shine a light on the past and ongoing inequities. And so oftentimes, when people see the bias, let's say when it came to like the the hiring algorithm or the language out, they see the names associated with negative or positive words that tends toe have, ah, bigger impact because they think well, Wow, The technology is reflecting these biases. It really must be true. Never mind that people might have been raising the issues in other ways before. But I think one of the most powerful ways we can use data and technology is as a mirror onto existing forms of inequality That then can motivate us to try to address those things. The caution is that we cannot just address those once we come to grips with the problem, the solution is not simply going to be a technical solution. And so we have to understand both the promise of data and the limits of data. So when it comes to, let's say, a software program, let's say Ah, hiring algorithm that now is trained toe look for diversity as opposed to homogeneity and say I get hired through one of those algorithms in a new workplace. I can get through the door and be hired. But if nothing else about that workplace has changed and on a day to day basis I'm still experiencing microaggressions. I'm still experiencing all kinds of issues. Then that technology just gave me access to ah harmful environment, you see, and so this is the idea that we can't simply expect the technology to solve all of our problems. We have to do the hard work. And so I would encourage everyone listening to both except the promise of these tools, but really crucially, um, Thio, understand that the rial kinds of changes that we need to make are gonna be messy. They're not gonna be quick fixes. If you think about how long it took our society to create the kinds of inequities that that we now it lived with, we should expect to do our part, do the work and pass the baton. We're not going to magically like Fairy does create a wonderful algorithm that's gonna help us bypass these issues. It can expose them. But then it's up to us to actually do the hard work of changing our social relations are changing the culture of not just our workplaces but our schools. Our healthcare systems are neighborhoods so that they reflect our better values. >>Yeah. Ha. So beautifully said I think all of us are willing to do the hard work. And I like your point about using it is a mirror and thought spot. We like to say a fact driven world is a better world. It can give us that transparency. So on behalf of everyone, thank you so much for your passion for your hard work and for talking to us. >>Thank you, Cindy. Thank you so much for inviting me. Hey, I live back to you. >>Thank you, Cindy and rou ha. For this fascinating exploration of our society and technology, we're just about ready to move on to our final session of the day. So make sure to tune in for this customer case study session with executives from Sienna and Accenture on driving digital transformation with certain AI.

>> From the SiliconANGLE Media office in Boston, Massachusetts, it's theCube! (funky electronic music) Now, here's your host, Dave Vellante! >> Welcome, everybody, to this Cube conversation here in our Marlborough offices. I am very excited today, I spent a number of years at IDC, which, of course, is owned by IDG. And there's a new book out, relatively new, called Future Forward: Leadership Lessons from Patrick McGovern, the Visionary Who Circled the Globe and Built a Technology Media Empire. And it's a great book, lotta stories that I didn't know, many that I did know, and the author of that book, Glenn Rifkin, is here to talk about not only Pat McGovern but also some of the lessons that he put forth to help us as entrepreneurs and leaders apply to create better businesses and change the world. Glenn, thanks so much for comin' on theCube. >> Thank you, Dave, great to see ya. >> So let me start with, why did you write this book? >> Well, a couple reasons. The main reason was Patrick McGovern III, Pat's son, came to me at the end of 2016 and said, "My father had died in 2014 and I feel like his legacy deserves a book, and many people told me you were the guy to do it." So the background on that I, myself, worked at IDG back in the 1980s, I was an editor at Computerworld, got to know Pat during that time, did some work for him after I left Computerworld, on a one-on-one basis. Then I would see him over the years, interview him for the New York Times or other magazines, and every time I'd see Pat, I'd end our conversation by saying, "Pat, when are we gonna do your book?" And he would laugh, and he would say, "I'm not ready to do that yet, there's just still too much to do." And so it became sort of an inside joke for us, but I always really did wanna write this book about him because I felt he deserved a book. He was just one of these game-changing pioneers in the tech industry. >> He really was, of course, the book was even more meaningful for me, we, you and I started right in the same time, 1983-- >> Yeah. >> And by that time, IDG was almost 20 years old and it was quite a powerhouse then, but boy, we saw, really the ascendancy of IDG as a brand and, you know, the book reviews on, you know, the back covers are tech elite: Benioff wrote the forward, Mark Benioff, you had Bill Gates in there, Walter Isaacson was in there, Guy Kawasaki, Bob Metcalfe, George Colony-- >> Right. >> Who actually worked for a little stint at IDC for a while. John Markoff of The New York Times, so, you know, the elite of tech really sort of blessed this book and it was really a lot to do with Pat McGovern, right? >> Oh, absolutely, I think that the people on the inside understood how important he was to the history of the tech industry. He was not, you know, a household name, first of all, you didn't think of Steve Jobs, Bill Gates, and then Pat McGovern, however, those who are in the know realize that he was as important in his own way as they were. Because somebody had to chronicle this story, somebody had to share the story of the evolution of this amazing information technology and how it changed the world. And Pat was never a front-of-the-TV-camera guy-- >> Right. >> He was a guy who put his people forward, he put his products forward, for sure, which is why IDG, as a corporate name, you know, most people don't know what that means, but people did know Macworld, people did know PCWorld, they knew IDC, they knew Computerworld for sure. So that was Pat's view of the world, he didn't care whether he had the spotlight on him or not. >> When you listen to leaders like Reed Hoffman or Eric Schmidt talk about, you know, great companies and how to build great companies, they always come back to culture. >> Yup. >> The book opens with a scene of, and we all, that I usually remember this, well, we're just hangin' around, waitin' for Pat to come in and hand out what was then called the Christmas bonus-- >> Right. >> Back when that wasn't politically incorrect to say. Now, of course, it's the holiday bonus. But it was, it was the Christmas bonus time and Pat was coming around and he was gonna personally hand a bonus, which was a substantial bonus, to every single employee at the company. I mean, and he did that, really, literally, forever. >> Forever, yeah. >> Throughout his career. >> Yeah, it was unheard of, CEOs just didn't do that and still don't do that, you were lucky, you got a message on the, you know, in the lunchroom from the CEO, "Good work, troops! Keep up the good work!" Pat just had a really different view of the culture of this company, as you know from having been there, and I know. It was very familial, there was a sense that we were all in this together, and it really was important for him to let every employee know that. The idea that he went to every desk in every office for IDG around the United States, when we were there in the '80s there were probably 5,000 employees in the US, he had to devote substantial amount-- >> Weeks and weeks! >> Weeks at a time to come to every building and do this, but year after year he insisted on doing it, his assistant at the time, Mary Dolaher told me she wanted to sign the cards, the Christmas cards, and he insisted that he ensign every one of them personally. This was the kind of view he had of how you keep employees happy, if your employees are happy, the customers are gonna be happy, and you're gonna make a lot of money. And that's what he did. >> And it wasn't just that. He had this awesome holiday party that you described, which was epic, and during the party, they would actually take pictures of every single person at the party and then they would load the carousel, you remember the 35-mm. carousel, and then, you know, toward the end of the evening, they would play that and everybody was transfixed 'cause they wanted to see their, the picture of themselves! >> Yeah, yeah. (laughs) >> I mean, it was ge-- and to actually pull that off in the 1980s was not trivial! Today, it would be a piece of cake. And then there was the IDG update, you know, the Good News memos, there was the 10-year lunch, the 20-year trips around the world, there were a lot of really rich benefits that, you know, in and of themselves maybe not a huge deal, but that was the culture that he set. >> Yeah, there was no question that if you talked to anybody who worked in this company over, say, the last 50 years, you were gonna get the same kind of stories. I've been kind of amazed, I'm going around, you know, marketing the book, talking about the book at various events, and the deep affection for this guy that still holds five years after he died, it's just remarkable. You don't really see that with the CEO class, there's a couple, you know, Steve Jobs left a great legacy of creativity, he was not a wonderful guy to his employees, but Pat McGovern, people loved this guy, and they st-- I would be signing books and somebody'd say, "Oh, I've been at IDG for 27 years and I remember all of this," and "I've been there 33 years," and there's a real longevity to this impact that he had on people. >> Now, the book was just, it was not just sort of a biography on McGovern, it was really about lessons from a leader and an entrepreneur and a media mogul who grew this great company in this culture that we can apply, you know, as business people and business leaders. Just to give you a sense of what Pat McGovern did, he really didn't take any outside capital, he did a little bit of, you know, public offering with IDG Books, but, really, you know, no outside capital, it was completely self-funded. He built a $3.8 billion empire, 300 publications, 280 million readers, and I think it was almost 100 or maybe even more, 100 countries. And so, that's an-- like you were, used the word remarkable, that is a remarkable achievement for a self-funded company. >> Yeah, Pat had a very clear vision of how, first of all, Pat had a photographic memory and if you were a manager in the company, you got a chance to sit in meetings with Pat and if you didn't know the numbers better than he did, which was a tough challenge, you were in trouble! 'Cause he knew everything, and so, he was really a numbers-focused guy and he understood that, you know, his best way to make profit was to not be looking for outside funding, not to have to share the wealth with investors, that you could do this yourself if you ran it tightly, you know, I called it in the book a 'loose-tight organization,' loose meaning he was a deep believer in decentralization, that every market needed its own leadership because they knew the market, you know, in Austria or in Russia or wherever, better than you would know it from a headquarters in Boston, but you also needed that tightness, a firm grip on the finances, you needed to know what was going on with each of the budgets or you were gonna end up in big trouble, which a lot of companies find themselves in. >> Well, and, you know, having worked there, I mean, essentially, if you made your numbers and did so ethically, and if you just kind of followed some of the corporate rules, which we'll talk about, he kind of left you alone. You know, you could, you could pretty much do whatever you wanted, you could stay in any hotel, you really couldn't fly first class, and we'll maybe talk about that-- >> Right. >> But he was a complex man, I mean, he was obviously wealthy, he was a billionaire, he was very generous, but at the same time he was frugal, you know, he drove, you know, a little, a car that was, you know, unremarkable, and we had buy him a car. He flew coach, and I remember one time, I was at a United flight, and I was, I had upgraded, you know, using my miles, and I sat down and right there was Lore McGovern, and we both looked at each other and said right at the same time, "I upgraded!" (laughs) Because Pat never flew up front, but he would always fly with a stack of newspapers in the seat next to him. >> Yeah, well, woe to, you were lucky he wasn't on the plane and spotted you as he was walking past you into coach, because he was not real forgiving when he saw people, people would hide and, you know, try to avoid him at all cost. And, I mean, he was a big man, Pat was 6'3", you know, 250 lbs. at least, built like a linebacker, so he didn't fit into coach that well, and he wasn't flying, you know, the shuttle to New York, he was flyin' to Beijing, he was flyin' to Moscow, he was going all over the world, squeezing himself into these seats. Now, you know, full disclosure, as he got older and had, like, probably 10 million air miles at his disposal, he would upgrade too, occasionally, for those long-haul flights, just 'cause he wanted to be fresh when he would get off the plane. But, yeah, these are legends about Pat that his frugality was just pure legend in the company, he owned this, you know, several versions of that dark blue suit, and that's what you would see him in. He would never deviate from that. And, but, he had his patterns, but he understood the impact those patterns had on his employees and on his customers. >> I wanna get into some of the lessons, because, really, this is what the book is all about, the heart of it. And you mentioned, you know, one, and we're gonna tell from others, but you really gotta stay close to the customer, that was one of the 10 corporate values, and you remember, he used to go to the meetings and he'd sometimes randomly ask people to recite, "What's number eight?" (laughs) And you'd be like, oh, you'd have your cheat sheet there. And so, so, just to give you a sense, this man was an entrepreneur, he started the company in 1964 with a database that he kind of pre-sold, he was kind of the sell, design, build type of mentality, he would pre-sold this thing, and then he started Computerworld in 1967, so it was really only a few years after he launched the company that he started the Computerworld, and other than Data Nation, there was nothing there, huge pent-up demand for that type of publication, and he caught lightning in a bottle, and that's really how he funded, you know, the growth. >> Yeah, oh, no question. Computerworld became, you know, the bible of the industry, it became a cash cow for IDG, you know, but at the time, it's so easy to look in hindsight and say, oh, well, obviously. But when Pat was doing this, one little-known fact is he was an editor at a publication called Computers and Automation that was based in Newton, Massachusetts and he kept that job even after he started IDC, which was the original company in 1964. It was gonna be a research company, and it was doing great, he was seeing the build-up, but it wasn't 'til '67 when he started Computerworld, that he said, "Okay, now this is gonna be a full-time gig for me," and he left the other publication for good. But, you know, he was sorta hedging his bets there for a little while. >> And that's where he really gained respect for what we'll call the 'Chinese Wallet,' the, you know, editorial versus advertising. We're gonna talk about that some more. So I mentioned, 1967, Computerworld. So he launched in 1964, by 1971, he was goin' to Japan, we're gonna talk about the China Stories as well, so, he named the company International Data Corp, where he was at a little spot in Newton, Mass.-- >> Right, right. >> So, he had a vision. You said in your book, you mention, how did this gentleman get it so right for so long? And that really leads to some of the leadership lessons, and one of them in the book was, sort of, have a mission, have a vision, and really, Pat was always talking about information, about information technology, in fact, when Wine for Dummies came out, it kind of created a little friction, that was really off the center. >> Or Wine for Dummies, or Sex for Dummies! >> Yeah, Sex for Dummies, boy, yeah! >> With, that's right, Ruth Westheimer-- >> Dr. Ruth Westheimer. >> But generally speaking, Glenn, he was on that mark, he really didn't deviate from that vision. >> Yeah, no, it was very crucial to the development of the company that he got people to, you know, buy into that mission, because the mission was everything. And he understood, you know, he had the numbers, but he also saw what was happening out there, from the 1960s, when IBM mainframes filled a room, and, you know, only the high priests of data centers could touch them. He had a vision for, you know, what was coming next and he started to understand that there would be many facets to this information about information technology, it wasn't gonna be boring, if anything, it was gonna be the story of our age and he was gonna stick to it and sell it. >> And, you know, timing is everything, but so is, you know, Pat was a workaholic and had an amazing mind, but one of the things I learned from the book, and you said this, Pat Kenealy mentioned it, all American industrial and social revolutions have had a media company linked to them, Crane and automobiles, Penton and energy, McGraw-Hill and aerospace, Annenberg, of course, and TV, and in technology, it was IDG. >> Yeah, he, like I said earlier, he really was a key figure in the development of this industry and it was, you know, one of the key things about that, a lot publications that came and went made the mistake of being platform or, you know, vertical market specific. And if that market changed, and it was inevitably gonna change in high tech, you were done. He never, you know, he never married himself to some specific technology cycle. His idea was the audience was not gonna change, the audience was gonna have to roll with this, so, the company, IDG, would produce publications that got that, you know, Computerworld was actually a little bit late to the PC game, but eventually got into it and we tracked the different cycles, you know, things in tech move in sine waves, they come and go. And Pat never was, you know, flustered by that, he could handle any kind of changes from the mainframes down to the smartphone when it came. And so, that kind of flexibility, and ability to adjust to markets, really was unprecedented in that particular part of the market. >> One of the other lessons in the book, I call it 'nation-building,' and Pat shared with you that, look, that you shared, actually, with your readers, if you wanna do it right, you've gotta be on the ground, you've gotta be there. And the China story is one that I didn't know about how Pat kind of talked his way into China, tell us, give us a little summary of that story. >> Sure, I love that story because it's so Pat. It was 1978, Pat was in Tokyo on a business trip, one of his many business trips, and he was gonna be flying to Moscow for a trade show. And he got a flight that was gonna make a stopover in Beijing, which in those days was called Peking, and was not open to Americans. There were no US and China diplomatic relations then. But Pat had it in mind that he was going to get off that plane in Beijing and see what he could see. So that meant that he had to leave the flight when it landed in Beijing and talk his way through the customs as they were in China at the time with folks in the, wherever, the Quonset hut that served for the airport, speaking no English, and him speaking no Chinese, he somehow convinced these folks to give him a day pass, 'cause he kept saying to them, "I'm only in transit, it's okay!" (laughs) Like, he wasn't coming, you know, to spy on them on them or anything. So here's this massive American businessman in his dark suit, and he somehow gets into downtown Beijing, which at the time was mostly bicycles, very few cars, there were camels walking down the street, they'd come with traders from Mongolia. The people were still wearing the drab outfits from the Mao era, and Pat just spent the whole day wandering around the city, just soaking it in. He was that kind of a world traveler. He loved different cultures, mostly eastern cultures, and he would pop his head into bookstores. And what he saw were people just clamoring to get their hands on anything, a newspaper, a magazine, and it just, it didn't take long for the light bulb to go on and said, this is a market we need to play in. >> He was fascinated with China, I, you know, as an employee and a business P&L manager, I never understood it, I said, you know, the per capita spending on IT in China was like a dollar, you know? >> Right. >> And I remember my lunch with him, my 10-year lunch, he said, "Yeah, but, you know, there's gonna be a huge opportunity there, and yeah, I don't know how we're gonna get the money out, maybe we'll buy a bunch of tea and ship it over, but I'm not worried about that." And, of course, he meets Hugo Shong, which is a huge player in the book, and the home run out of China was, of course, the venture capital, which he started before there was even a stock market, really, to exit in China. >> Right, yeah. No, he was really a visionary, I mean, that word gets tossed around maybe more than it should, but Pat was a bonafide visionary and he saw things in China that were developing that others didn't see, including, for example, his own board, who told him he was crazy because in 1980, he went back to China without telling them and within days he had a meeting with the ministry of technology and set up a joint venture, cost IDG $250,000, and six months later, the first issue of China Computerworld was being published and within a couple of years it was the biggest publication in China. He said, told me at some point that $250,0000 investment turned into $85 million and when he got home, that first trip, the board was furious, they said, "How can you do business with the commies? You're gonna ruin our brand!" And Pat said, "Just, you know, stick with me on this one, you're gonna see." And the venture capital story was just an offshoot, he saw the opportunity in the early '90s, that venture in China could in fact be a huge market, why not help build it? And that's what he did. >> What's your take on, so, IDG sold to, basically, Chinese investors. >> Yeah. >> It's kind of bittersweet, but in the same time, it's symbolic given Pat's love for China and the Chinese people. There's been a little bit of criticism about that, I know that the US government required IDC to spin out its supercomputer division because of concerns there. I'm always teasing Michael Dow that at the next IDG board meeting, those Lenovo numbers, they're gonna look kinda law. (laughs) But what are your, what's your, what are your thoughts on that, in terms of, you know, people criticize China in terms of IP protections, etc. What would Pat have said to that, do you think? >> You know, Pat made 130 trips to China in his life, that's, we calculated at some point that just the air time in planes would have been something like three and a half to four years of his life on planes going to China and back. I think Pat would, today, acknowledge, as he did then, that China has issues, there's not, you can't be that naive. He got that. But he also understood that these were people, at the end of the day, who were thirsty and hungry for information and that they were gonna be a player in the world economy at some point, and that it was crucial for IDG to be at the forefront of that, not just play later, but let's get in early, let's lead the parade. And I think that, you know, some part of him would have been okay with the sale of the company to this conglomerate there, called China Oceanwide. Clearly controversial, I mean, but once Pat died, everyone knew that the company was never gonna be the same with the leader who had been at the helm for 50 years, it was gonna be a tough transition for whoever took over. And I think, you know, it's hard to say, certainly there's criticism of things going on with China. China's gonna be the hot topic page one of the New York Times almost every single day for a long time to come. I think Pat would have said, this was appropriate given my love of China, the kind of return on investment he got from China, I think he would have been okay with it. >> Yeah, and to invoke the Ben Franklin maxim, "Trading partners seldom wage war," and so, you know, I think Pat would have probably looked at it that way, but, huge home run, I mean, I think he was early on into Baidu and Alibaba and Tencent and amazing story. I wanna talk about decentralization because that was always something that was just on our minds as employees of IDG, it was keep the corporate staff lean, have a flat organization, if you had eight, 10, 12 direct reports, that was okay, Pat really meant it when he said, "You're the CEO of your own business!" Whether that business was, you know, IDC, big company, or a manager at IDC, where you might have, you know, done tens of millions of dollars, but you felt like a CEO, you were encouraged to try new things, you were encouraged to fail, and fail fast. Their arch nemesis of IDG was Ziff Davis, they were a command and control, sort of Bill Ziff, CMP to a certain extent was kind of the same way out of Manhasset, totally different philosophies and I think Pat never, ever even came close to wavering from that decentralization philosophy, did he? >> No, no, I mean, I think that the story that he told me that I found fascinating was, he didn't have an epiphany that decentralization would be the mechanism for success, it was more that he had started traveling, and when he'd come back to his office, the memos and requests and papers to sign were stacked up two feet high. And he realized that he was holding up the company because he wasn't there to do this and that at some point, he couldn't do it all, it was gonna be too big for that, and that's when the light came on and said this decentralization concept really makes sense for us, if we're gonna be an international company, which clearly was his mission from the beginning, we have to say the people on the ground in those markets are the people who are gonna make the decisions because we can't make 'em from Boston. And I talked to many people who, were, you know, did a trip to Europe, met the folks in London, met the folks in Munich, and they said to a person, you know, it was so ahead of its time, today it just seems obvious, but in the 1960s, early '70s, it was really not a, you know, a regular leadership tenet in most companies. The command and control that you talked about was the way that you did business. >> And, you know, they both worked, but, you know, from a cultural standpoint, clearly IDG and IDC have had staying power, and he had the three-quarter rule, you talked about it in your book, if you missed your numbers three quarters in a row, you were in trouble. >> Right. >> You know, one quarter, hey, let's talk, two quarters, we maybe make some changes, three quarters, you're gone. >> Right. >> And so, as I said, if you were makin' your numbers, you had wide latitude. One of the things you didn't have latitude on was I'll call it 'pay to play,' you know, crossing that line between editorial and advertising. And Pat would, I remember I was at a meeting one time, I'm sorry to tell these stories, but-- >> That's okay. (laughs) >> But we were at an offsite meeting at a woods meeting and, you know, they give you a exercise, go off and tell us what the customer wants. Bill Laberis, who's the editor-in-chief at Computerworld at the time, said, "Who's the customer?" And Pat said, "That's a great question! To the publisher, it's the advertiser. To you, Bill, and the editorial staff, it's the reader. And both are equally important." And Pat would never allow the editorial to be compromised by the advertiser. >> Yeah, no, he, there was a clear barrier between church and state in that company and he, you know, consistently backed editorial on that issue because, you know, keep in mind when we started then, and I was, you know, a journalist hoping to, you know, change the world, the trade press then was considered, like, a little below the mainstream business press. The trade press had a reputation for being a little too cozy with the advertisers, so, and Pat said early on, "We can't do that, because everything we have, our product is built, the brand is built on integrity. And if the reader doesn't believe that what we're reporting is actually true and factual and unbiased, we're gonna lose to the advertisers in the long run anyway." So he was clear that that had to be the case and time and again, there would be conflict that would come up, it was just, as you just described it, the publishers, the sales guys, they wanted to bring in money, and if it, you know, occasionally, hey, we could nudge the editor of this particular publication, "Take it a little bit easier on this vendor because they're gonna advertise big with us," Pat just would always back the editor and say, "That's not gonna happen." And it caused, you know, friction for sure, but he was unwavering in his support. >> Well, it's interesting because, you know, Macworld, I think, is an interesting case study because there were sort of some backroom dealings and Pat maneuvered to be able to get the Macworld, you know, brand, the license for that. >> Right. >> But it caused friction between Steve Jobs and the writers of Macworld, they would write something that Steve Jobs, who was a control freak, couldn't control! >> Yeah. (laughs) >> And he regretted giving IDG the license. >> Yeah, yeah, he once said that was the worst decision he ever made was to give the license to Pat to, you know, Macworlld was published on the day that Mac was introduced in 1984, that was the deal that they had and it was, what Jobs forgot was how important it was to the development of that product to have a whole magazine devoted to it on day one, and a really good magazine that, you know, a lot of people still lament the glory days of Macworld. But yeah, he was, he and Steve Jobs did not get along, and I think that almost says a lot more about Jobs because Pat pretty much got along with everybody. >> That church and state dynamic seems to be changing, across the industry, I mean, in tech journalism, there aren't any more tech journalists in the United States, I mean, I'm overstating that, but there are far fewer than there were when we were at IDG. You're seeing all kinds of publications and media companies struggling, you know, Kara Swisher, who's the greatest journalist, and Walt Mossberg, in the tech industry, try to make it, you know, on their own, and they couldn't. So, those lines are somewhat blurring, not that Kara Swisher is blurring those lines, she's, you know, I think, very, very solid in that regard, but it seems like the business model is changing. As an observer of the markets, what do you think's happening in the publishing world? >> Well, I, you know, as a journalist, I'm sort of aghast at what's goin' on these days, a lot of my, I've been around a long time, and seeing former colleagues who are no longer in journalism because the jobs just started drying up is, it's a scary prospect, you know, unlike being the enemy of the people, the first amendment is pretty important to the future of the democracy, so to see these, you know, cutbacks and newspapers going out of business is difficult. At the same time, the internet was inevitable and it was going to change that dynamic dramatically, so how does that play out? Well, the problem is, anybody can post anything they want on social media and call it news, and the challenge is to maintain some level of integrity in the kind of reporting that you do, and it's more important now than ever, so I think that, you know, somebody like Pat would be an important figure if he was still around, in trying to keep that going. >> Well, Facebook and Google have cut the heart out of, you know, a lot of the business models of many media companies, and you're seeing sort of a pendulum swing back to nonprofits, which, I understand, speaking of folks back in the mid to early 1900s, nonprofits were the way in which, you know, journalism got funded, you know, maybe it's billionaires buying things like the Washington Post that help fund it, but clearly the model's shifting and it's somewhat unclear, you know, what's happening there. I wanted to talk about another lesson, which, Pat was the head cheerleader. So, I remember, it was kind of just after we started, the Computerworld's 20th anniversary, and they hired the marching band and they walked Pat and Mary Dolaher walked from 5 Speen Street, you know, IDG headquarters, they walked to Computerworld, which was up Old, I guess Old Connecticut Path, or maybe it was-- >> It was actually on Route 30-- >> Route 30 at the time, yeah. And Pat was dressed up as the drum major and Mary as well, (laughs) and he would do crazy things like that, he'd jump out of a plane with IDG is number one again, he'd post a, you know, a flag in Antarctica, IDG is number one again! It was just a, it was an amazing dynamic that he had, always cheering people on. >> Yeah, he was, he was, when he called himself the CEO, the Chief Encouragement Officer, you mentioned earlier the Good News notes. Everyone who worked there, at some point received this 8x10" piece of paper with a rainbow logo on it and it said, "Good News!" And there was a personal note from Pat McGovern, out of the blue, totally unexpected, to thank you and congratulate you on some bit of work, whatever it was, if you were a reporter, some article you wrote, if you were a sales guy, a sale that you made, and people all over the world would get these from him and put them up in their cubicles because it was like a badge of honor to have them, and people, I still have 'em, (laughs) you know, in a folder somewhere. And he was just unrelenting in supporting the people who worked there, and it was, the impact of that is something you can't put a price tag on, it's just, it stays with people for all their lives, people who have left there and gone on to four or five different jobs always think fondly back to the days at IDG and having, knowing that the CEO had your back in that manner. >> The legend of, and the legacy of Patrick J. McGovern is not just in IDG and IDC, which you were interested in in your book, I mean, you weren't at IDC, I was, and I was started when I saw the sort of downturn and then now it's very, very successful company, you know, whatever, $3-400 million, throwin' off a lot of profits, just to decide, I worked for every single CEO at IDC with the exception of Pat McGovern, and now, Kirk Campbell, the current CEO, is moving on Crawford del Prete's moving into the role of president, it's just a matter of time before he gets CEO, so I will, and I hired Crawford-- >> Oh, you did? (laughs) >> So, I've worked for and/or hired every CEO of IDC except for Pat McGovern, so, but, the legacy goes beyond IDG and IDC, great brands. The McGovern Brain Institute, 350 million, is that right? >> That's right. >> He dedicated to studying, you know, the human brain, he and Lore, very much involved. >> Yup. >> Typical of Pat, he wasn't just, "Hey, here's the check," and disappear. He was goin' in, "Hey, I have some ideas"-- >> Oh yeah. >> Talk about that a little. >> Yeah, well, this was a guy who spent his whole life fascinated by the human brain and the impact technology would have on the human brain, so when he had enough money, he and Lore, in 2000, gave a $350 million gift to MIT to create the McGovern Institute for Brain Research. At the time, the largest academic gift ever given to any university. And, as you said, Pat wasn't a guy who was gonna write a check and leave and wave goodbye. Pat was involved from day one. He and Lore would come and sit in day-long seminars listening to researchers talk about about the most esoteric research going on, and he would take notes, and he wasn't a brain scientist, but he wanted to know more, and he would talk to researchers, he would send Good News notes to them, just like he did with IDG, and it had same impact. People said, "This guy is a serious supporter here, he's not just showin' up with a checkbook." Bob Desimone, who's the director of the Brain Institute, just marveled at this guy's energy level, that he would come in and for days, just sit there and listen and take it all in. And it just, it was an indicator of what kind of person he was, this insatiable curiosity to learn more and more about the world. And he wanted his legacy to be this intersection of technology and brain research, he felt that this institute could cure all sorts of brain-related diseases, Alzheimer's, Parkinson's, etc. And it would then just make a better future for mankind, and as corny as that might sound, that was really the motivator for Pat McGovern. >> Well, it's funny that you mention the word corny, 'cause a lot of people saw Pat as somewhat corny, but, as you got to know him, you're like, wow, he really means this, he loves his company, the company was his extended family. When Pat met his untimely demise, we held a crowd chat, crowdchat.net/thankspat, and there's a voting mechanism in there, and the number one vote was from Paul Gillen, who posted, "Leo Durocher said that nice guys finish last, Pat McGovern proved that wrong." >> Yeah. >> And I think that's very true and, again, awesome legacy. What number book is this for you? You've written a lot of books. >> This is number 13. >> 13, well, congratulations, lucky 13. >> Thank you. >> The book is Fast Forward-- >> Future Forward. >> I'm sorry, Future Forward! (laughs) Future Forward by Glenn Rifkin. Check out, there's a link in the YouTube down below, check that out and there's some additional information there. Glenn, congratulations on getting the book done, and thanks so much for-- >> Thank you for having me, this is great, really enjoyed it. It's always good to chat with another former IDGer who gets it. (laughs) >> Brought back a lot of memories, so, again, thanks for writing the book. All right, thanks for watching, everybody, we'll see you next time. This is Dave Vellante. You're watchin' theCube. (electronic music)

>> Live from Las Vegas, it's theCUBE! Covering AWS re:Invent 2018. Brought to you by Amazon web services, Intel, and their ecosystem partners. >> Hey welcome back everyone, here at AWS re:Invent 2018, their sixth year of theCUBE coverage, two sets wall-to-wall coverage here, two more sets in other locations, getting all the content, bringing it in, ingesting it into our video cloud service on AWS, ah, Dave, >> Lot of content, John. >> Lot of people don't know that we have that video cloud service, but we're going to have a lot of fun, ton of content, ton of stories, and a special analyst segment, Jerry Chen, guest here today, CUBE alumni, famous Venture Capitalist and Greylock partners, partnering with Reid Hoffman, the founder of LinkedIn, great set of partners at Greylock , great firm, tier one, doing a lot of great deals, Rockset, recent one. >> Thanks, yeah. >> You're also, on the record, these six years ago, calling the shot of Babe Ruth predicting the future. You've got a good handle on, you've got VM where you have the cloud business, now you're making investments, you're seeing a lot of stuff on the landscape, certainly, as a Venture Capitalist, you're funding projects, what better time now of innovation to actually put money to work, to hit market share, and then the big guys are getting bigger, they're creating more robust platforms, game is changing big-time, want to get your perspective, Dave, so, Jerry, what's your take on the announcements, slew of announcements, which ones jumped out at you? >> I think there's kind of two or three areas, there's definitely the hybrid cloud story with the Outpost, there's a bunch of stuff around ML and AI services, and a bunch of stuff on data and storage, and for me I think what they're doing around the ML services, the prediction, the personalization, the text OCR, what Amazon's doing at that app layer is now creating AI building blocks for modern application, so you want to do forecasts, you want to do personalization, you want to do text analysis, you have a simple API to basically build these modern apowered apps, he's doing to the app infrastructure layer what he's done to the cloud infrastructure layer, by deconstructing these services. >> And API is also the center, that's what web services are, so question for you is, do you see that the core cloud players, Aussie, Amazon, Bigly, Google, Microsoft, others, it's a winner take most, you called that six years ago, and that's true, but as they grow there's going to be now a new cloudification going on for business apps, new entrepreneurs coming to market, who's vulnerable, who wins, who loses, as this evolution continues because it's going to enable a lot of opportunity. >> Yeah, well I mean Amazon in cloud in general is going to create a lot of winners and losers, like you said, so I think you have a shift of dollars from on prem and old legacy vendors, databay storage, compute, to the cloud, so I think there's a shift of dollars, there are winner and losers, but I think what's going to happen is, with all these services around AI, ML, and Cloud as a distribution model, a lot of applications are going to be rebuilt. So I think that the entire application stack from all the big SaaS players to small SaaS companies, you're going to see this kind of a long tale of new SaaS applications being built on top of the Cloud that you didn't see in the past. >> And the ability to get to markets faster, so the question I have for you is, if you're an entrepreneur out there, looking for funding and I can to market quicker, what's the playbook, and two, Jassie talked on stage about a new persona, a new kind of developer, one that can rethink and reimagine and reinvent something that someone else has already done, so if you're an entrepreneur, you got to think to take someone else's territory, so how does an entrepreneur go out and identify whose lunch to eat, so if I want to take down a company, I got to have a strategy, how do I use the cloud to >> I think it's always a combination when a founder in a thing attacks your market it's a combination of where are the dollars, where can I create some advantage IP or advantage angle, and thirdly where do I have a distribution advantage, how can I actually get my product in the hands of the users differently? And so I think those are the three things, you find intersection of a great market, you have a unique angle, and you have a unique route to market, then you have a powerful story. So, you think about cloud changing the game, think about the mobile app you can consist of, for consumers, that is also a new platform, a new distribution method, the mobile app stores, and so what happened, you had a new category of developers, mode developers, creating this long tale, a thousand thousand apps, for everything from groceries to cars to your Fantasy Football score. So I think you're going to see distribution in the cloud, making it easy to get your apps out there, going to see a bunch of new markets open up, because we're seeing verticals like healthcare, construction, financial services, that didn't have special apps beforehand, be disrupted with technology. Autodesk just bought PlanGrid for 800 million dollars, I mean that's unheard of, construction software company. So you can see a bunch of new inverdics like that be opened up, and then I think with this cloud technology, with compute storage network becomes free and you have this AI layer on top of it, you can power these new applications using AI, that I think is pretty damn exciting. >> Yes, you described this sort of, we went from client server to the cloud, brought a whole bunch of new app providers, obviously Salesforce was there but Workday, Service Now, what you described is a set of composeable digital services running on top of a cloud, so that's ripe for disruption, so do I have to own my own data centers if I'm big SaaS company, what happens to those big guys? >> I don't think you have to, well, you don't have to own your own data center as a company, but you could if you wanted to, right, so at some point in scale, a lot of big players build their own data centers, like AirBNB is on Amazon, but Dropbox built their own storage on Amazon early, then their own data center later. Uber has their own data center, right, so you can argue that at some point of scale it makes sense to build your own, so you don't need to be on Amazon or Google as your start, but it does give you a head start. Now the question is, in the future, can you build a SaaS application entirely on Amazon, Azure, or Google, without any custom code, right, can you hide read write call private SaaS, like a single instance of my SaaS application for you, John, or for you, Dave, that's your data, your workflow, your information personalized for you, so instead of this multi-tenet CRM system like Salesforce, I have a custom CRM system just for Dave, just for Jeff, just for Jerry, just for theCUBE, right? >> I think yes, for that, I think that's definitely a trend I would see happening. >> It's what Infor is trying to do, right, Charles Phillips says "Friends don't let friends "build data centers," but they've still got a big loss in legacy there, but it's an interesting model, focused on verticals or microverticals or like the healthcare example that you're giving, and lot of potential for something. >> Well here's why I think I like this because, I think, and I said this before in theCUBE maybe it's not the best way to say it is that, if you look at the benefit of AI, data-driven, the quality of the data and the power of the compute has to be there. AI will work well with all that stuff, but it's also specialized around the application's use case. So you have specialism around the application, but you don't have to build a full stack to do that, you could use a horizontally scalable cloud distribution system in your word, and then only create custom unique workloads for the app, where machine learning's involved, and AI, that's unique to the app, that's differentiation, that could be the business model, or the utility. So, multitenancy could exist in theory, at the scalable level, but unique at the top of the level so yes I would say I'd want that hosted in the most customized, agile, flexible way. So I would argue that that's the scenario. >> I think that's the future, I mean one of my, I think you were saying, Dave, friends don't let friends build data centers anymore, it's you probably don't need to build a data center anymore because you can actually build your own application on top of one of the two or three large cloud providers. So it's interesting to see what happens the next three, four years, we're going to see kind of a thousand flowers bloom of different apps, not everyone's going to make it, not everyone's going to be a huge Salesforce-like outcome, but there'll be a bunch of applications out there. >> And the IoT stuff is interesting to me, so observing a lot of what the IT guys are doing, it reminds me of people trying to make the Windows mobile phone, they're just trying to force IT standards down the IoT, what I've seen from AWS today is more of a bottoms up approach, build applications for operations technology people, which I think is the right way to go, what do you see in an IoT, IoT apps, what's the formula there? >> I think what Amazon announced today with their time series database, right, their Timestream prediction engine, plus their Outpost offering with the Vmware themselves, you're really seeing a combination of IoT and Edge, right, it's the whole idea is, one, there's a bunch of use cases for time series in IoT, because sentry data, cameras, self-driving cars, drones, et cetera, there's more data coming at you, it adds all of that. >> And Splunk has proven that big-time. >> Correct, Splunk's let 18 billion Marcap company, all on time series data, but number two, what's happening is, it's not necessarily centralized data, right, it's happening at the edge, your self-driving car, your cell phone, et cetera, so Outpost is really a way for Amazon to get closer to the edge, by pushing their compute towards your data center, towards remote office, branch office, and get closer to where the data is, so I think that'll be super interesting. >> Well the Elastic Inference engine is critical, now we got elasticity around inference, and then they got the chip set that worked Inferentia, that can work with the elastic service. That's a powerful combination. >> The AI plumbing war between Google and TetraFlow as technology there's like PyTorch, Google TPUs versus what Amazon is doing with inference chips today, versus what I'm sure Microsoft and else is doing, is fascinating to watch in terms of how you had a kind of a Intel Nvidia duopoly for a long time, and now you have Intel, Nvidia, and then everyone from Amazon, Google, Microsoft doing their own soul again, it's pretty fascinating to watch. >> What was the stat, he said 85% of the TensorFlow, cloud TensorFlow's running on AWS? >> Makes a lot of sense, I think he said Aurora's customers logoslide doubled, but let's break down real quick, to end the segment with the key areas that we see going on, at least my perspective, I want to get your reaction. Storage, major disruption, he emphasized a lot of that in the keynote, spent a lot of time on stores, actually I think more than EC2 if you look at it, two, databases, database war, storage rate configuration, and a holy trinity of networking, storage, and compute, that's evolving, databases, SageMaker, machine learning. All there and then over the top, yesterday's announcement of satellite as a service, that essentially kills the edge of the network, cause there is no edge if we have space satellites shooting connectivity to any device the world is now, there's no more edge, it's everywhere. So, your thoughts, those areas. Which one pops out as the most surprising or most relevant? >> I think it's consistent Amazon strategy, on the lowest layer they're trying to draw the cost to zero, so on storage, cheaper cheaper cheaper, they're driving the bottom layer to zero to get all your data. I think the second thing, the database layer, it makes sense, it's not open-source, right, time scale or time series, it's not, Timestream's not their open-source database, it's their own, so open-source, low cost, the lowest layer, their database stuff is mostly their own, Aurora, Dynamo, Timestream, right, because there's some level lock in there, which I think customers are worried about, so that's clever, it's not by accident, that's all proprietary, and then ML Services, on top of that, that's all cares with developers, and it's API locking, so clearly low-cost open-source for the bottom, proprietary data services that they're trying to own, and then API's on top of it. And so the higher up in the stack, the more and more Amazon, you look, the more and more Amazon you have to adopt as kind of a lock in stack, so it's a brilliant strategy the guys have been executing for the past six, seven years as you guys have seen firsthand, I think the most exciting thing, and the most shocking thing to me is this move towards this battle for the AI front, this ML AI front, I think we saw ML's the new sequel, right, that's the new war, right, against Amazon, Google, and Microsoft. >> And that's the future of applications, cause this is >> But you're right on, it's a knife fight for the data, and then you layer on machine intelligence on top of that, and you get cloud scale, and that's the innovation engine for the next 10 years. >> Alright Jerry Chen just unpacked the State of the Union of cloud, of course as an investor I got to ask the final question, how are you investing to take advantage of this wave, versus being on the wrong side of history? >> I have framers for everything, there's a framer on how to attack the cloud vendors, and so I'm looking at a couple things, one, a seams in between the clouds, right, or in between services, because they can't do everything well, and there were kind of these large continents, Amazon, Google, Azure, so I'm looking for seams between the three of them, I'm looking for two, deep areas of IP that they're not going into that you actually have proprietary tap, and then verticals of data, like source of the data, or workflows that these guys aren't great, and then finally kind of cross-data cross-cloud solution, so, something that gives you the ability to run on prem, off prem, Microsoft, Google, Azure. >> Yeah, fill in the white spaces, there are big white spaces, and then hope that could develop into, good. Jerry Chen, partner in Greylock , partners formerly Vmware part of the V Mafia, friend of theCUBE, great guest analysis here, with Dave Vellante and John Furrier, thanks for watching us, stay with us, more live coverage, day two of three days of wall-to-wall coverage at re:Invent, 52,000 people, the whole industry's here, you can see the formations, we're getting all of the data, we're bringing it to you, stay with us.

>> Live, from Toronto, Canada, it's theCUBE! Covering Global Cloud and Blockchain Summit 2018, brought to you by theCUBE. >> So, welcome to the Global Cloud and Blockchain Summit. I'm about to hand you over to John Furrier, who is the Co-Founder and Co-CEO of SiliconANGLE Media and Executive Editor at theCUBE, he's about to do a Fireside Chat with Al and Mathew, I'll let him introduce you to them as well. He's also involved in a major blockchain project himself, so he's going to get into that with those guys as well. So, and tomorrow we start at nine, in the meantime, enjoy the evening, enjoy the food, enjoy the chat, and I'll let you go. >> Okay. Hello? Thank you Ruth, appreciate it, thanks everyone for being part of this panel, Fireside Chat, want to make it loose, but high impact for you guys, I know, having some cocktails, having a good time. If there's any questions during, then at the end we'll pass the mic around, but. We want to have a conversation, kind of like we always do down in the lobby bar, just talking about crypto and cloud, and we ended up talking about cloud computing and crypto a lot because those are two areas that are kind of converging, and the purpose of this event. So we really wanted to share some thoughts around those two massively growing markets, one is already growing, it's continuing to be great: the cloud, and blockchain certainly is changing everything. These two important topics, we want to flesh them out, Al Burgio is the Serial Entrepreneur/Founder of DigitalBits, he's founded companies both in cloud and blockchain, so he brings a great perspective. And Matt Roszak, leading crypto investor, entrepreneur and advocate, well known in the crypto space for goin' way back, I think you gave a couple bitcoins to some very famous people early on, we'll get into that a little bit later. So guys, thanks for being part of the panel and Fireside. First question is: we know how big the money is, I mean the money is crypto is is flowin' around the world, and cloud computing we've seen specifically, and certainly in coverage now with Amazon's success, Amazon Web Services, and Microsoft and others. Trillions of dollars being disrupted in the traditional kind of the enterprise, data center area, and blockchain is doing that too, so we want to get into that. But first, before we get into it, I want you guys to take a minute to explain for the folks, just to set the context, the kinds of projects you're working on. Now Al, you have DigitalBits, Matt you're investing and you're finding a lot of interesting token dynamics. So just take a minute. Al, start. >> (mic off) So-- Everybody hear me okay? Alright, perfect. Well thanks for that lovely intro. Yes, my name is Al Burgio, I'm, I've founded a few companies, as John mentioned. Before the cloud there was internet, (light laugh) and so it started for me in the late '90s in the e-commerce era. But more recently I pioneered what's known as Interconnection 2.0, and I did that with the company called Console, for those that may know PCCW, recently it was acquired by PCCW. And with that we disrupted the way networks at the core of the internet were connected together More recently I've founded the DigitalBits project, and now DigitalBits blockchain network, and with that, you can kind of think of that as the trading and transaction layer for the points economy and other digital assets, and you can do a lot of really interesting thing with that, it's really about bringing blockchain to the masses. >> Matt, what're you workin' on? >> So, Matthew Roszak, Co-Founder and Chairman of Bloq. Bloq is a enterprise software company, we do two things, the premise is the tokenization of things, so we think the money identity, new layers of the internet are going to be tokenized. And so, we go to market in two ways, one is through Bloq Enterprise, and these are all the software layers you need to to connect to tokenized networks, so think a wallet, a node, a router, etc. And then Bloq Labs we build, and partner with, some of the leading tokenize networks and applications, so we build a connective tissue and then we actually build these new networks. I started this space as an investor over five/six years ago, investing in some of the best entrepreneurs and technologists in the space build a great network. But I love building companies, and so my Co-Founder and I, Jeff Garzik, built Bloq two and a half years ago. And then lastly, also serve of Chairman of the Chamber of Digital Commerce, so, so if you believe in these new tokenized money layers, identity layers, etc, regulation comes into play. Certainly today from an institutional adoption level, and so if you care about this space, you need to spend time to kind of help that dialogue improve; this technology moves way faster than folks in DC and elsewhere, so. >> And the project that we're workin' on at SiliconANGLE, is we've tokenized our media platform, and we're opening it up to a token model, and have kind of changed the game. So all three of us have projects, want to put those in context, we build everything on Amazon Web Services, so, the view of the cloud, we also cover it. The cloud computing market is booming, we see that Amazon Web Services numbers empower the earnings for Amazon's company, obviously Apple's trillion dollar evaluation those are clear case studies; but blockchain could potentially disrupt it all, and Al, I want to get your thoughts, because even today in the news at Microsoft Azure, which is their big cloud provider, announced blockchain as a service. And folks that are in either the data center business or in cloud know the shift that's happening in the IT world, but no ones really connected the dots on where blockchain intersects, and also, is it an opportunity for the cloud guys, what's the landscape look like, so. What's your thoughts on that, how are they connected, what does it mean, how does a cloud company maintain their relevance and competitiveness with blockchain? >> Well, just pointing on the fact that, you know, today we had that new Microsoft, the Azure cloud, their support and evangelism for blockchain. You know, a company, I think it's very important that this isn't an ICO, two kids in a garage saying their doing something blockchain this is a massive, multi-billion dollar company; and making a decision like that is not trivial, it's many, many departments, a lot of resources, before such a thing's announced. So, that's, not only is it validation, but it's a leading indicator as to this trend, that this is clearly something that's important. And a lot of people, if you're not paying attention, you need to be paying attention, including if you're in the cloud industry, 'cause many companies obviously do compete with, with Microsoft and AWS, so. It may be still early, but it's not that early, in light of the news that we saw today. With that, I would say that, a lot of the parallels I like to kind of, if I was an infrastructure provider I'd look at this from the standpoint of the emergence of Linux when it first came on the scene. What was important for companies like Red Hat to be successful, they had competition at the time, and you had shortages of Linux, let's say engineers, and what have you. And so, a company like Red Hat built a business around that, and they did that by how they kind of surfaced and validated themselves to the enterprise of that era, was partnering with hardware companies, so, it was Intel, IBM, and then Dell, HP, and they all followed, and then all of a sudden, which version of Linux do you want to use? It's Red Hat, you're paying for that support, you're paying Red Hat. And, you know, then they had their hockey stick moment. Today, you know, it's not about hardware companies per se, it's about the cloud, right? So cloud is the new hardware per se, and many enterprises obviously are looking at cloud computing companies and cloud computing providers, infrastructure providers, as the company that they need to support them with the infrastructure that they use, or sorry the technologies that they use, right? Because they're not necessarily supporting these things and making sure that they're always on within the basement of that enterprise, they're depending, or outsourcing, to depending on these managed IT providers. This was very important that whatever technologies they're using in the lab, that ultimately their infrastructure partners are able to support the implementation, the integration, the ongoing support of these technologies. So if you think of blockchain like an operating system or a database technology, or whatever you want to call it, it's important that you're able to really identify these key trends, and be able to support your customer and what they're going to need, and ultimately for them, they can't have a clog in their digital supply chain, right? So, it's clearly emerging. Microsoft is validating that today, you know, clearly they have the data, that they're seeing for their existing enterprise customers, and they don't want to lose them. >> Yeah, but remember when cloud came out; you and I have talked about this many times Al that it wasn't easy to use, I remember when Amazon Web Services came out, it was just basically, it was hard to command line, basically you had to use it, so, it became easier now, it's so easy and consumable. Blockchain, similar growing pains, but, we don't want to judge it too early with the opportunity that it has, it's going to get easier, what're your thoughts? And it has to scale by the way, Amazon, at a large scale. >> Yeah, I mean-- >> So blockchain has to scale and be easier, your thoughts? >> Another kind of way to think of it is, to not necessarily think of cloud computing, but the evolution the internet went, you know, in Internet 1.0, you know, we went through this dial-up modem era, things were very raw back then; great visions we had of the future, like, it's going to be amazing for video one day! But, not during dial-up modem era, and eventually, you know, it eventually happened. And user interfaces improved, and tool sets improved and so forth. You know, fast forward to today, we have all of that innovation to leverage, so things will move a lot faster with blockchain, it did start very raw, but it's, it's moving much faster than anything we've seen definitely in the '90s and in the last decade, so. It's just, you know, it's a matter of moments, not years. >> And I think Al brings up a great point on leverage, because Amazon leverages infrastructure to a point where it's larger than Google, Azure, and IBM's public cloud combined, and so yeah, massive leverage there. And so, when these big cloud providers provide this blockchain as a service, it is instrumented and built on top of their existing infrastructure, not necessarily on blockchain infrastructure. So, it's an interesting dynamic where they're putting it on top of existing infrastructure that's there, but what's being build right now is the decentralized Amazon Web Services. So you have every layer of Amazon being re-imagined, like, and incentivized so you have distributed compute and access and storage and database. And so, what will be interesting to see is that, given this massive opportunity, will Amazon and some of these other incumbent cloud providers become the provisioning networks of the future? Of all this new decentralized resources that get, again, if you want storage, you have to start having smarts to say: if I'm going to go to Sia or Filecoin or Genaro or Storj, compute, etc; you have to start being a provisioning layer on top of that to kind of, you know, make that blockchain essentially work. So, it'll be interesting to see the transition 'cause today the lightweight versions to say yeah, I have a blockchain as a service strategy, and that's like, well done, and check the box. Now, the question is how far in this new world will they go down? And, as it gets more decentralized, as universities and governments, corporations, plug their access utility into these networks, and to see how that changes. That is much bigger than the Amazon of today. >> I think that's an interesting point, I want to just drill down on that if you don't mind, 'cause I think that's a fundamental observation that every layer's going to be decentralized. The questions I think I'm asking and I'm seeing is: How does it all work together? And then what's the priorities? And the old model was easy; got to get the infrastructure, got to get servers, (laughs lightly) and you know, work your way up to the top of the stack. What cloud brings also is that: a software developer can whip up an application, maybe a dApp on a test network and go viral, and the next thing you know they have a great opportunity, and then they got to build down. So the question is: What are you seeing in terms of priorities on stacks, portions of the stack that are being decentralized and tokenized, do you see patterns, trends, as an investor, is there a hotter (laughs) area than others, how do you look at that? >> Well, I think it's, it's in motion right now it's, like I said, every layer of AWS is getting thought through in how to create these digital cooperatives, I have excess storage, I'm going to contribute it to this network, and I'm going to get paid in tokens when a user uses that storage network, and pays for it in those native tokens and so that, coupled with all the other layers, is happening. From a user perspective, we may not want to be going to pick a database provider, a storage, a compute, etc, we're likely going to say: I want a provisioning layer, and provision this and execute this, much like if we, you know, there'll be new provisioning layers for moving money, I don't care if routes through Lightning or Litecoin or Doge or whatever, as long as the value gets across the pond or the app gets provisioned appropriately based on you know, time, security, and cost, and whatever other tendance are important, that's all I care about, but; given the depth and the market for all that, I think it'll be interesting to see how these are developed with the provisioning layers, and I would think Amazon or Azure, the future of that is, is more provisioning than actually going and doing all that at the end of the day. >> That's great. I want to get your thoughts guys on innovation. My good friend Andy Kessler wrote an op-ed in today's Wall Street Journal around, an article around the government, the US government getting involved. You know, there's Twitter, Facebook, the big platforms, in terms of how they're handling their media, but it brings up a good point that with more regulation, there's less innovation. You mentioned some things outside the United States, it's a global cloud, cloud's operating globally with regions, it's a global fabric. Startups are really hot in this area so; how do you view the ecosystems of startups, in terms of being innovative, things happening that you think that're good, and things that aren't good, obviously I'm not a big of the government getting involved, and managing startups, the ecosystems but, blockchain has a lot of alpha entrepreneurs jumping in, you've looked at all the top ventures, the legit ventures, they're all alpha entrepreneurs, multi-time serial entrepreneurs, they see the opportunity and they go for it. Is the startup environment good, is there enough innovation opportunities, what're you thoughts on the opportunity to be innovative? >> Yeah, Al and I were just talking about this before the panel here, and were talking about our travels in Asia, and when we go there it is 10, 100 X of energy and get-it factor, and capital, and the markets are just wildly more vibrant than you know, going to some typical markets here in San Fran and New York in North America, and, so it's interesting to see that when you heat map the world, what's really happening. And you know, people are always saying: oh well this, this FinTech, or InsurTech, or whatever tech, is going to make a dent in Silicon Valley or Wall Street. This technology, this new frontier, is definitely going to do that. I think some of that will get put into more focus based on regulation, and there's two things that will happen; there's obviously a lot of whippersnapper countries that are promoting a safe place to innovate with crypto, I think Malta, Gibraltar, Barbados, etc, and there were-- >> Even Bermuda's getting in on the mix now. >> Yeah! I mean so there's no shortage of that, and so, and obviously this ecosystem outpaces the pace of regulation and then we'll see like the US doing something, or you know, other fast followers to try and catch up, and say hey, we're going to do the cryptocurrency act of 2022, miners get free power, tax-free, you know crypto trading, you know just try and play catch up. 'Cause it's kind of hard in the last year or 18 months we've seen this ecosystem go from this groundswell to this now institutional discussion; and how do you back end the the banking, the custody, all these form factors that are still relatively absent. And so, you know, we're right in the middle of it. >> It's a whole new way, you got to follow the money, right? Al, you and I talked about this; capital markets, you know entrepreneurs need to raise money and that's a good thing, you need to get capital to do stuff. >> Yeah, this is a new phenomenon that the world has never experienced before, it's awesomeness when it comes to capital formation; you know, without capital formation there is no innovation. And so the fact that more capital can be raised, it's the ultimate crowd sourcing in such an efficient period of time, capital being able, the ability to track capital from various different corners of the world, and deploy that capital to try to fuel innovation. Of course, you know, not all startups or what have you succeed, but that was true yesterday, right? You know, 90% of startups fail, but they all will give it some meaningful amounts of checks, people were employed and innovation was tried; and every once in a while something emerges that's amazing. If you can do that faster, right, when you have the opportunity to produce more and more innovation. And, of course with something so new as cryptocurrency, things like ICOs and what have you, people may kind of refer to it as the wild wild West, it's not, it's an evolution. And you have-- >> It's still the wild west though, you got to admit. (laughs) >> Well, it is but, we're getting better at it, right? As a world, this isn't the Silicon Valley community getting better at venture capital or some other part of the United States or Canada getting better at venture capital; this is the world as a whole getting better at capital formation. >> Yeah, that's a great point. >> In the new way of capital formation. >> And I wanted to just get an observation on that. I moved to Silicon Valley 20 years ago, and I love it there, for venture capital and new startups, it's the best place in the world. And I've seen people try to replicate Silicon Valley, we're the Silicon Valley of Canada, we're the Silicon Valley of the East or Europe, and it's always been hard to replicate, because it was a venture model, and you needed venture capitalists and you need money, you need a community, the culture, the failure, the starting over, and just, you know, gettin' back on the horse kind of thing. Crypto is the first time that I've seen the replica of that Silicon Valley dynamic, in a new way, because the money's flowing, (laughs) and there's community involved in crypto, crypto has a big community aspect to it. Do you guys see that as well? I mean I'm seeing, outside the United States, a lot of activity. Is that something that you're seeing? >> So, the first time we saw, well, last time we saw everybody trying to replicate Silicon Valley was first internet, you know, there was Silicon Swamp, there was Silicon Alley, there was silicon this-- >> Prairie. >> Every city was >> Silicon Beach. >> A silicon version of something, and then the capital evaporated, right? We had a mass correction happen. What wasn't being disrupted was value exchange, right, and so this is being created now, it is now possible for this to happen, and it's happening, we're seeing amazing things, Matt said, you know, in Asia. It's a truly awesome force, if anybody has an opportunity to go, they should go, it's unbelievable to experience it, and it really opens your eyes. >> And you've lived through a lot of investments during those .com days and through history now, you've seen a lot of different things. Your observations with the current state of the capital formation, startup landscapes, the global ecosystem around crypto and how it's different from say venture or classic rolling up companies and those kinds of things? >> Yeah, you hear a lot of this, you know, we're in a bubble, it's speculative, etc. And I think that when you look back at history of infrastructure, whether it's railroads, telephony, internet, and now crypto and blockchain, it's interesting, like, if you said: it would take this amount of money to innovate and come out the other end of internet with this kind of infrastructure, these kinds of applications, with these kinds of lessons learned, nobody would sign up for that number, right? It needs this fear, and greed, and all the other effervescence of markets to kind of come out the other end and have innovation. I think we're going through a very similar dynamic here with crypto and blockchain where you know, everything's getting tokenized, everything's getting decentralized. We're talking about fundamental things like money, you know, it's not like we're talking about pet food and women's shoes and airline tickets, we are talking about money, identity, things that will enable like other curves to really come into focus like in and out of things and the kind of compounding of intersections when some of these things get right is pretty extraordinary. And so, but I like what Al said in terms of capital formation and that friction to get from, you know, idea to capital to building, is getting compressed Yes, there will be edge cases of people taking advantage of that, but at the other end of this flow will be some amazing innovation. >> What do you guys think about the, if you had to answer the question with one answer, of what is the high order bit of why blockchain's so important? For me, I see it, from my standpoint, I'll just start, I see it making inefficient things more efficient for any use case, and that's being re-imagined, which is everything from IOT or whatever. Efficiency is a big thing, at least I see that. What do you guys see as a high order bit in terms of you know, the one thing that you'd say blockchain really impacts the world in terms of you know, impact, financial, etc? >> Well, I think with decentralization and all these things that we're seeing it's kind of evened the playing field. It's allowing for participation where parts of the world were unable to participate. And it's doing a whole lot of things in that area. And that's truly awesome, to really grow the economy, grow the global market, and the number of participants in that market in all areas. That's the ultimate trend at what's happening here. >> And your information? >> Absolutely, and I think there's two things, there's this blockchain dialogue, and then there's this crypto decentralization, tokenization dialogue, and on the blockchain side you have lots of companies engaging in blockchain and trying to figure out how it applies to their business, and you hear everything from McKinsey and Goldman saying financial services will save 100 billion dollars in operating expenses by applying blockchain technology, and that's great. That is probably low in terms of what they'll save, it's, to me, is just not the point of the technology, I think that when you kind of distill that down to say hey, for a group of folks to use this technology as a shared services thing to lower opex a trading settlement and decrease that, that's great, that is a step stone to creating these tokenized economies, these digital cooperatives. Meaning you contribute something and then you get something back, and it's measured in the value that this token is, like a barometric kind of value of how healthy that ecosystem is. And so, regulated public enterprises, and EC consortiums around insurance and financial services and banking, that is all fantastic, and that gets them in the pool, gets them exercising on what blockchain is, what it isn't, how they apply it, but it's, at the end of the day for them it's cost reduction The minute there's growth or IP, or disruption on the table, they're all going back to their boardrooms to say: hey let's do this, this, or that, but, if there's a way, my favorite class in college was industrial organization, and it sounds weird but, it was, it kind of told ya like how to dissect an industry, you know, what makes them competitive, who the market leaders are, and then, if you overlay like blockchain networks with tokens, with incentives, interesting things could happen, right? And so that future is going to be real interesting to see how market leaders think about how to tokenize their network, how to be, how to say: no I don't want to own this whole industrial network, I have to engage with some other participants and make sure everybody is incentivized to climb on board. So that I think is going to be more of the interesting part than just blockchain-ifying a workflow. >> Well let's just quickly drill down on that, token economics, what you're getting to. So let's assume blockchain just happens, as evolution of technology, let's just assume for a second that it's going to happen in a big way, it's private, public, hybrid chains, with all that good stuff happening, but the token economics is where the business value starts to be extracted, so the question for you is: How do you describe that to someone to look for, what are the key elements of token economics? When does it matter, when is it in play, and how should they be thinking about it? >> Yeah, I mean token economic design and getting a flywheel going to create a network and network effects is really important. You could have great technology, but Al could be a better marketer, and he gets tokens adopted better, and his network will do better because, you know, he was better able to get people to adopt and market a particular, you know, layer application. And so, it's really important to think about how you get that flywheel going, and how you get that kindling going on a particularly new ecosystem, and get users adoption and growth. That is really hard to do these days because some people don't even know what Bitcoin is, let alone to say I'm going to tokenize this layer, and every time you contribute, every time you take an action, you're going to get rewarded for it, and you're share the value of this network. >> Can you give me a good example of what's happening today that you can point to and say: that's a great example of token economics? >> Well, you see, I mean the most basic one is shared file storage, right? You know, it's like the Filecoin, Sia, Genaro model where, you know, you contribute you know, the unused storage in your laptop or your university data center or a corporate data center, and you say I'm going to contribute this, and when it's used I get these tokens and, you know at the end of the day or week or year you see what these tokens are worth, and was that worth your contribution? And so as these markets develop, and as utility develops, we'll see what that holds. >> Al, you got an example you could share? DigitalBits is a good use case obviously. >> Actually, I'm not going to use DigitalBits (John laughs) just to be neutral. This is one that Matt will know very well, definitely better than I, but one that I've-- the simpler something is, the easier it is for people to understand, and its like oh that makes sense, you know. You know, Binance is one that's very simple, you know it's a payment token, if you pay with some other currency, you pay, you know, Pricex, if you pay in the next few years with their token, you'll get the service at a discount. And in addition to that, they're using a percentage of profits, I think it's every quarter, to buy back up to, ultimately up to, 50% of tokens that are in circulation. So, you know, it's driving value, and driving return, in essence, if I can use that word. So for a user it's simple to understand, for someone that likes to speculate it's easy for someone to understand in terms of how the whole model works, so it's not some insanely complicated mathematical equation, that we can yes we can trust the math. And so in some cases, some adoption is going to just be, you know, attract participants based on simplicity. In other cases the math is important, and people will care about that, so, you know not all things are necessarily equal, and not necessarily one method is right, but there are some simple examples out there that that have proven to be successful. >> That's awesome, one last question, before we open it up if anyone has any questions. If anyone has any questions, if they want to come up, grab the microphone, and ask the three of us if you've got anything on your mind. And while you're thinking about that I'll get the final question for these guys is: A lot of people ask me hey, I want to be on the right side of history, what side of the street should I be on when the reality comes down that decentralization, blockchain, token economics, decentralized applications, becomes the norm, and that re-imagining actually happens? I don't want to be on the wrong side of history. What should I be doing, how should I be thinking differently, who should I be following, what should I be paying attention to? How do you answer that question? >> I think, at the basic level, you know, turn off your phone, lock your door, and study this technology for a day, it's the best advice I could give. Two: buy some crypto. Once you kind of have crypto on your phone, in your wallet, something changes in your brain, I think you just feel like you-- >> You check the prices every day. (all laugh) >> You lose a lot of sleep. And then after that, you know, I think you start engaging in this space in a very different way. So I think starting small, starting basic, is an important tenet. And then, what's amazing about this space is that it attracts the best and brightest out of industry, and law, and government, and technology, and you name it, and I'm always fascinated the people that show up and they're like yeah, I'm in a 20 year, you know, veteran in this space and I want to get into blockchain, it just attracts some of the best and brightest. And, I think we're going to see a lot of experience coming into the space, you know, this has been a, what I'd say a bottoms up groundswell of crypto and blockchain and the evolution of the space. And I think we're starting to see more some more mature folks come in the space to to add some history and perspective and helpin' the build out of this, and to build a lot of these networks. I think that the kind of intersection of both is going to be very healthy for the space. >> Al, your thoughts? >> Definitely agree with Matt. Definitely to lock yourself up and just try to absorb information, everyone has access to the internet, there's plenty of information. If you don't like to read go watch a few YouTube videos, just people explaining the stuff, it's really fascinating, the various different use cases and so forth. You definitely have to buy some, and, you know, whether it's five dollars worth, just go through the whole experience of being able to trade something of value that a few years ago didn't exist, and be able to trade it for something else of value is a pretty phenomenal experience. Then trying to go buy something with it, it's even more of a fascinating experience, I just bought something that used, again, something that didn't exist a few years ago. But, what I would add to that as well, you really have to get out there; if you keep surrounding yourself with people saying aw, this is, eh, whatever, >> It's never going to work. >> It's crazy, it's for criminals, and all that fun stuff. You're going to be last place. So coming to conferences, obviously future's conference you're going to meet a lot of interesting, great people, and that consistent experience, you'll learn something every time. You know, at the end of the day, I remember, I'm sure all three of us remember, with the birth of the internet there was many people that said you know the internet thing, it's crap, it's for kids, you know. And we had first movers, we had willing followers, and then the unwilling followed, you don't want to end up being-- >> The unwilling followers. >> Yeah, the unwilling. >> Alright. Does anyone have any questions they'd like to ask? Come on up. Yeah. We're recording, so we want to get it on film. >> So I have two questions. The first one is for you, Al: Two years ago I interviewed with IIX before it was Console, and I want to know why you didn't hire me? (Sparse laughs) No I'm kidding! That was a joke. Actually, I thought each of you brought up some good points, minus you Al. (chuckles) I'm just kidding. But what I really wanted to ask you guys is: so you talk a lot about this, the tokenized economy and kind of the roadmap and the things to get there, you talk about sediment layer, right, Fiat to crypto, sediment layer, your identity protocols, your dApps, X, Y, Z, right? The whole web 3.0 stack, I want each of you, or I want at least input from both of you or all of you, what are the hurdles to getting to a full adoption of web 3.0 stack, and make a bold prediction on the timing before we have a full web 3.0 stack that we use every day. >> That is a awesome question actually, timelines. You could be, being in technology, being in venture, you could be right, and you could be off by three, five, seven, 10 years, and be so wrong, right? And then at your retirement dinner you could say: I was right, but Tommy wasn't right. So, this is really hard technology, in terms of building systems that are distributed, creating the economic models, the incentive models, it takes a lot to go right in the intersection of all this. But it's not a question like is this happening? No, this is happening, this is like, it's in motion. The timelines are going to be a little elusive, I'm way more pragmatic, I was one of the early guys in the early internet, and you know everything was going to be .com and awesome and fantastic. But the timelines were a little elusive then, right? You know, it's like when was, people are thinking of today's Amazon was going to be the 2005 Amazon, you know, it's like, that took about another decade to get there, right? And people could easily just buy stuff and a drone or a UPS guy would just deliver it, and so, similar things apply today. And you know at the same time we all have a super computer in our pocket, and so it's a lot different. At the same time we're dealing with trusted mediums right? The medium of money, the medium of identity, all these different things they're, they're things that you know if I say download Instagram, and let's share cat pictures or whatever, it's not a big deal, our trust is really low for that, let's do it. For money, it's a different mental state, it's a different dynamic, especially if you're an individual, a government, or an enterprise, you go through a whole different adoption curve on that, so, you know, it is at grand scale five to 10 years, right? In any meaningful way. And so we still have a lot of work to do. >> My answer to that question, it's a good one, your question was a good one, my answer's a little bit weird because it's multi-generational. The first generation pivot was when the internet was born was because of standards, right? The government had investment. The OSI model, open system interconnect, actually never happened, the seven layers didn't get standardized, only a few key ones did; that created a lot of great things. And then when the we came out, that was very interesting protocol development there, the TCP/IP stuff, I mean HTP stuff. I don't see the standardization happening, because cloud flipped the stack model upside down because Amazon and these guys let the software developers drive the value. It used to be infrastructure drove the value of what software could do, then software became so proliferated that that drove the value of the infrastructure, so the whole cloud computing equation is making the infrastructure programmable for the first time, not the other way around, so. The cloud phenomenon's all about software driving the value, and that's happening, so. It's interesting because with blockchain you can almost do levels of services in a cloud-like way with crypto, I mean with blockchain and token economics, and have a partial stack. So think that this whole web 3.0 might be something that no one's every seen before. So, that's kind of my answer, I don't really know if that's going to be right or not, but just looking at the future, connecting the dots, it's probably not going to look like what we've seen before, and if the cloud's an indicator it's probably going to be some weird looking stack where certain sections are working, and then evolution might fill in the other ones, so. I mean, that's my take, I mean, but standards will play a role, the communities will have to get involved around certain things, and I think that's a timeless concept. >> Timing. >> Oh, timing. I think it's going to be pretty quick, I think if you look at the years it took for internet, and then the web, everything's being compressed down, but I think it's going to be much shorter. If it was a 20 year cycle in the past, that gets shortened down to 15 with the internet, and this could be five years. So five to 10 years, that could be the impact in my mind. The question I always ask is: what year will banks no longer be involved in anything? Is that 20 years or 10 years? (laughs) Exactly, so, yeah, follow the money. >> So I would say that in terms of trying to keep your finger on the pulse with things and how you kind of things, see things evolve; things are definitely moving a lot faster, you know in the past you would probably say seven to 10, I'm not sure if I would say five, sorry five to 10, it definitely feels to me that it's five max til we could start to see some of these key things fall into place, so. >> So could you answer the first question? >> What was the first question? >> Why didn't you hire me? (audience cringes) >> We've met before? Sorry. (all laugh) >> I have a question, this is Dave Vellante, Co-Host of theCUBE. And I want to pick up on something John you just said, and Matt you were talking about Goldman Sachs and Morgan Stanley, it's not about them saving hundreds of millions of dollars, it's really about them transforming business, so. And John, you just asked the question about banks, I want to actually get your answer to this: Will traditional banks, in your opinion, lose control of payment systems? Not withstanding your bias. (laughter) >> Yeah, I am definitely biased on this. But, I mean, I've been in front of the C-suite of banks, credit card companies, etc, and I said, you know, in about a decade, the center of what you do and how you make money is going to be zero. And, 'cause there'll be networks, and ways to transmit money that'll be by far cheaper, or will be subsidized by other networks, meaning, and those networks are Apple, Amazon, Alibaba, you know, Tencent, whatever networks that're out there, that're engaging in collaboration and commerce and everything else, they will give away payments as just a courtesy, like people give away messaging or email or something, as a courtesy to that network, and will harden that network, and it'll be built and based on blockchain technology and cryptocurrencies, so they don't necessarily have to worry about, you know, kind of subtle payments. But these new networks will start to encroach on banks, the banks are not worried about other banks today, the banks should be worried about these new networks that're being developed. >> How many people still have a home phone line? >> That was elegant, I like that. >> You know, I mean there's a generation of people that still like going to banks, they'll keep them in business for a while. But I think that comes to an end. >> I mean, when we covered a lot of the big data market when it started, the argument was mobile will kill the banks outlets, and now with ATMs there's more bank, more baking branches than ever before, so I think the services piece is interesting. >> And also, if you look at even the cloud basis, the software as a service, SaaS space, a decade, decade and a half ago, you would ask SAP, Oracle, what have you, what's your cloud strategy? And they'd be like cloud? That's just more efficient delivery model, not interested. 90 some billion dollars of M and A later, SAP, Oracle, etc, are cloud companies, right? And so, if banks kind of get into that same mode to say well, yeah, we need to play catch up and buy digital currency exchanges and multi-currency wallets, and this infrastructure and plumbing to be relevant in the next world, that would be interesting. But I think technology companies have as much an advantage to do that as as financial services companies, so it'll be interesting to see who kind of goes into that, goes into the crypto ecosystem to make that their own. >> It's interesting. We were talking before we came on and the OSS market, operational support systems is booming, and that's traditionally been these big operational outsource companies would manage big projects, but, if you look at in the first half of 2018, there's been a greater than 20 billion dollar commercial exits of companies through private equity merchants, IPOs, around OSS, and that's where we see operational things happening, CoreOS, Alfresco, MuleSoft, Pivotal went public, Magneto, GitHub, Treasure Data, Fastly, Elastic, DataStax, they're all in the pipeline. These are all companies that aren't cloud, they're like running stuff in cloud, so, this could be a tell sign that potentially the the blockchain operating market is going to be potentially a big one. >> Yeah, and then even look at BitMate, the world's largest miner in crypto. So, they did about a billion dollars in profit last year, did about a billion dollars in profit just in the first quarter going public, just raised a billion dollars last month, at a reportedly 50 to 70 billion dollar evaluation in Hong Kong in the next month, and the amount of money they'll raise will eclipse what Facebook raised. And so I think the institutional, the hardware, the cloud computing, the whole ecosystem starts to like resonate and think about this space a lot differently, and we need these milestones, we need these, whether they're room huddles or data points to kind of like think about how this is going to affect your business and what you do tomorrow morning. >> Any more questions from the crowd? Audience? Okay, great, well thanks for attending, appreciate you guys watching and listening, and guys thanks for the conversation; cloud and blockchain convergence. Collision course, or is it going to happen nicely, Al? >> Yeah, I think it's going to be a convergence, I don't see it necessarily as a collision course. >> And a lot of money to be made on this opportunity these days, and cloud convergence with blockchain. >> I concur with Al, I think there's going to be convergence, I think us most smarter players will engage and figure out their models in this new crypto and tokenized era. >> Thanks so much guys, appreciate it, give these guys a round of applause. (audience applause) Thank you very much. (bubbly music)

(upbeat orchestral music) >> Welcome back everybody. Jeff Frick here with the CUBE. We're at our Palo Alto studios having a CUBE conversation about digital transformation, industrial internet, AI, ML, all things great, and we're really excited to have a representative of GE, one of our favorite companies to work with because they're at the cutting edge of old industrial stuff and new digital transformation and building a big software organization out in San Ramon. So we're so happy to have here first time Jeff Erhardt. He is the VP Intelligent Systems from GE Digital. Jeff, great to see you. >> Pleasure to be here. Thanks for having me. >> Absolutely, so how did you get into GE? You actually, a creature of the valley, you've been here a little while. How did you end up at GE? >> I have. I'm a new guy, so I've been here about a year and a half, I came in via the acquisition of a company called Wise IO where I was the CEO, so I've spent the last 10 years or so of my life building two different analytic startups. One was based around a very popular and powerful open source language called R and spent a lot of time working with much of the Fortune 500. Think the really data driven companies now that you would think of, the Facebooks, the Goldman Sachs, the Mercks, the Pfeizers helping them go through this data driven journey. Anyway, that company was acquired by Microsoft and is embedded into their products now. But the biggest thing I learned out about that was that even if you have really good data science teams, it's incredibly hard to go from white board into production. How do you take concepts and make them work reliably repeatably, scalably over time? And so, Wise IO was a machine learning company that was a spin out from Berkeley, and we spent time building what I now refer to as intelligent systems for the purposes of customer support automation within things like the sales force and Zendesk ecosystem, and it was really that capability that drew us to GE or drew GE to approach us, to think about how do we build that gap not just from algorithms, but into building true intelligent applications? >> Right, so GE is such a great company. They've been around for a hundred years, original DOW component, Jeff Immelt's not there now, but he was the CEO I think for 16 years. A long period of time. Beth Comstock, fantastic leader. Bill Ruth building this great organization. But it's all built around these industrial assets. But they've started, they did the industrial internet launch. We helped cover it in 2013. They have the Pridix Cloud, their own kind of industrial internet cloud, had a big developer conference. But I'm curious coming from kind of a small Silicon Valley startup situation. When you went into GE, what's kind of the state of their adoption, you know, kind of how had Bill's group penetrated the rest of GE and were they making process? We're people kinda getting it, or were you still doing some evangelical work out in the field? Absolutely both, meaning people understand it are implementing yet I think there was maybe misunderstandings about how to think about software data in particular analytics and AI machine learning. And so a big part of my first year at the company was to spend the time coming in really from the top down, from sort of the CEO and CDO levels across the different business understanding what was the state of data and data driven processes within their businesses. And what I learned really quickly was that the core of this business, and this is all public information been well publicized, is in things like GE Aviation. It's not necessarily the sale of the engine that is incredible profitable, but rather it's maintaining and servicing that over time. >> Right. >> And what organizations like them, like our oil and gas divisions, with things like their inspection capabilities like our power division had really done is they had created as a service businesses where they we're taking data across the customer base, running it through a data driven process, and then driving outcomes for our customers. And all of a sudden the aha moment was wow, wait a minute. This is the business model that every startup in the valley is getting funded to take down the traditional software players for. It's just not yet modern, scalable, repeatable, with AI machine learning built in, but that's the purpose and the value of building these common platforms with these applications on top that you can then make intelligent. >> Right. >> So, once we figure that out it was very easy to know where to focus and start building from that. >> So it's just, it's kinda weird I'm sure for people on the outside looking in to say data driven company. We all want to drive data driven companies. But then you say, well wait a minute, now GE builds jet engines. There's no greater example that's used at conferences as to the number of terabytes of data an engine throws off on a transcontinental flight. Or you think of a power plant or locomotion and you think of the control room with all this information so it probably seems counterintuitive to most that, didn't they have data, weren't they a data driven organization? How has the onset of machine learning and some of the modern architectures actually turned them into a data driven company, where before I think they were but really not to the level that we're specifying here. >> Yah, I-- >> What would be your objective, what are you trying to take on this? >> Absolutely, machine learning, AI, whatever buzz words you want to use is a fascinating topic. It's certainly come into vogue. like many things that are hyped, gets confused, gets misused, and gets overplayed. But, it has the potential to be both an incredibly simple technology as well as an incredibly powerful technology. So, one of the things I've most often seen cause people to go awry in this space is to try to think about what is the new things that I can do with machine learning? What is the green field opportunity? And whenever I'm talking to somebody at whatever level, but particularly at the higher levels of the company is I like to take a step back and I like to say, "What are the value producing, data driven workflows within your business?" And I say define for me the data that you have, how decisions are made upon it, and what outcome that you are driving for. And if you can do that, then what we can do is we can overlay machine learning as a technology to intelligently automate or augment those processes. And in turn what that's gonna do is it's gonna force you to standardize your infrastructure, standardize those workflows, quantify what you're trying to optimize for your customers. And if you do that in a standardized and incremental way, you can look backward having accomplished some very big things. >> Right, and those are such big foundational pieces that most people I think discount again, just the simple question of where is your data. >> That's right. >> What form is it in? So another interesting concept that we cover all the time with all the shows we go to is democratization, right? So it seems to me pretty simple, actually. How do you drive innovation, democratize the data, democratize the tool to manipulate the data, and democratize the ability to actually do something about it. That said, it's not that easy. And this kind of concept that we see evolving from citizen developer to citizen integrator to citizen data scientist is kinda where we all want to go to, but as you've experienced first hand it's not quite as easy as maybe it appears. >> Yah, I think that's a very fair statement and you know, one of the things, again I spend a lot of time talking about, is I like to think about getting the right people in the right roles, using the right tools. And the term data scientist has evolved over the past five plus years going from to give Drew Conway some credit of his Venn diagram of a program or a math kinda domain expert, into meaning anybody that's looking at data. And there's nothing wrong with that, but the concept of taking anybody that has ability to look at data within something like a BI or a Tableau tool, that is something that should absolutely be democratized and you can think about creating citizens for those people. On the flip side, though, how do you structure a true intelligent system that is running reliably, robustly, and particular in our field in mission critical, high risk, high stakes applications? There are bigger challenges than simply are the tools easy enough to use. It's very much more a software engineering problem than it is a data access or algorithmic problem. >> Right. >> And, so we need to build those bridges and think about where do we apply the citizens to for that understanding, and how do we build robust, reliable software over time? >> Right, so many places we can go, and we're gonna go a lot of them. But one of the things you touched on which also is now coming in vogue is kind of ML that you can, somebody else's ML, right? >> Mhmm. >> As you would buy an application at an app store, now there's all kinds of algorithmic equations out there that you can purchase and participate in. And that really begs an interesting question of kinda the classic buy versus build, or as you said before we turned on the cameras buy versus consume because with API economy with all these connected applications, it really opens up an opportunity that you can use a lot more than was produced inside your own four walls. >> Absolutely. >> For those applications. >> Yep. >> And are you seeing that? How's that kinda playing out? >> So we can parse that in a couple of different ways. So the first thing that I would say is there's a Google paper from a few years back that we love and it's required reading for every new employee that we bring on board. And the title of it was machine Learning is the High Interest Credit Card of Technical Debt. And one of the key points within that paper is that the algorithm piece is something like five percent of an overall production machine learning implementation. And so it gets back to the citizen piece. About it's not just making algorithms easier to use, but it's also about where do you consume things from an API economy? So that's the first thing I would think about. The second thing I would think about is there's different ways to use algorithms or APIs or pieces of information within an overall intelligent system. So you might think of speech to text or translation as capabilities. That's something where it probably absolutely makes sense to call an API from an Amazon or a Microsoft or a Google to do that, but then knowing how to integrate that reliably, robustly into the particular application or business problem that you have, is an important next step. >> Right. >> The third thing that I would think about is, it very much matters what your space is. And there's a difference between doing things like image classification on things like Imagenet which is publicly available images which are well documented. Is it a dog versus a cat? Is it a hot dog versus not? Versus some of the things that we face with an industrial context, which aren't really publicly available. So we deal with things like within our oil and gas business we have a very large pipeline inspection integrity business where the purpose of that is to send the equivalent of an MRI machine through the pipes and collect spectral images that collect across 14 different sensors. The ability to think that you're gonna take a pre trained algorithm based on deep learning and publicly available images to something that is noisy, dirty, has 14 different types of sensors on it and get a good answer-- >> Right. >> Is ridiculous. >> And there's not that many, right? >> And there's not that many. >> That's the other thing I think people underestimate the advantage that Google has we're all taking pictures of dogs and blueberries-- >> Correct. >> So that it's got so much more data to work with. >> That's right. >> As opposed to these industrial applications which are much smaller. >> That's right. >> Lets shift gears again, in terms of digital transformation one of the other often often said examples is when will the day come that GE doesn't sell just engines but actually sells propulsion miles? >> Yep. >> To really convert to a service. >> Yah. >> And that's ultimately where it needs to go cause it's kinda the next step beyond maintenance. >> Yep. >> How are you seeing that digital transformation play out? Do people kinda get it? Do the old line guys that run the jet engine see that this is really a better opportunity? >> Mhmm. >> Cause you guys have, and this is the broader theme, very uniques data and very unique expertise that you've aggregated across in the jet engines base all of your customers in all of the flying conditions and all of the types of airplanes where one individual mechanic or one individual airline just doesn't have an expertise. >> Yep. >> Huge opportunity. >> That's exactly right, and you can say the ame thing in our power space, in our power generation space. You can say the same thing in the one we we're just talking about, you know things like our inspection technology spaces. That's what makes the opportunity so powerful at GE and it's exactly the reason why I'm there because we can't get that any place else. It's both that history, it's that knowledge tied to the data, and very importantly it's what you hinted at that bares repeating is the customer relationships and the customer base upon which you can work together to aggregate all that data together. And if you look at what things are being done, they're already doing it. They are selling effectively, efficiency within a power plant. They are selling safety within certain systems, and again, coming back to why create a platform. Why create standardized applications? Why put these on top? Is if you standardize that, it gives you the ability to create derivative and adjacent products very easily, very efficiently, in ways that nobody else can match. >> Right, right. And I love the whole, for people who aren't familiar with the digital twin concept, but really leveraging this concept of a digital twin not to mimic kinda the macro level, but to mimic the micro level of a particular part unit engine in a particular ecosystem where you can now run simulations, you can run tests, you can do all kinds of stuff without actually having that second big piece of capital gear out there. >> That's right, and it's really hard to mimic those if you didn't start from the first phase of how did you design, build, and put it in to the field? >> Right, right. So, I want to shift gears a little bit just on to philosophical things that you've talked about and doing some research. One of them is that tech is the means to an end, and I know people talk about that all the time, but we're in the tech business. We're here in Silicon Valley. People get so enamored with the technology that they forget that it is a means to an end. It is now the end and to stay focused. >> That's right. >> How are you seeing that kind of play out in GE Digital? Obviously Bill built this humongous organization. I'm super impressed he was able to hire that many people within the last like four years in San Ramon. >> Yah. >> Originally I think just to build the internal software workings within the GE business units, but now really to go much further in terms of industrial internet connectivity, etc. So how do you see that really kinda playing out? >> Yah, I think one of my favorite quotes that I forget who it came from but I'll borrow it is, "Customers don't want to buy a one inch drill bit, they want to buy a one inch hole." >> Right. >> And I think there is both an art and a science and a degree of understanding that needs to go into what is the real customer problem that they are trying to solve for, and how do you peel the onion to understanding that versus just giving what they ask for? >> Right. >> And I think there's an organizational design to how do you get that right. So we had a visitor from Europe, the chairman of one of our large customers, who is going through this data driven journey, and they were at the stage of simply just collecting data off of their equipment. In this case it was elevators and escalators. And then understanding how was it being used? What does it mean for field maintenance, etcetera? But his guys wanted to move right to the end stage and they wanted to come in and say, "Hey, we want to build AI machine learning systems." And we spent some time talking through them about how this is a journey, how you step through it. And you could see the light bulb go off. That yes, I shouldn't try to jump right to that end state. There's a process of going through it, number one, and then the second thing we spent some time talking about was how he can think about structuring his company to create that bridge between the new technology people who are building and doing things in a certain way, and the people who have the legacy knowledge of how things are built, run, and operated? >> Right. >> And it's many times those organizational aspects that are as challenging or as big of barriers to getting it right as a specific technology. >> Oh, for sure, I mean people process and tech it's always the people that are the hard part. It's funny you bring up the elevator or escalator story, We did a show at Spunk many moons ago and we had a person on from an elevator company and the amazing insight they connected Spunk to it. They could actually tell the health of a building by the elevator traffic. >> Yah. >> Not the health of it's industrial systems and it's HVAC, but whether some of the tenants were in trouble. >> Yep. >> By watching the patterns that were coming off the elevator. While different kinda data driven value proposition than they had before. >> Yep. So again, if you could share some best practices really from your experiences with R and now kinda what you're doing at GE about how people should start those first couple of steps in being data driven beyond kinda the simple terms of getting your house in order, getting your data in order, where is it. >> Yah. >> Can you connect to it? Is it clean? >> Yah. >> How should they kinda think about prioritizing? Ho do they look for those easy wins cause at the end of the day it's always about the easiest wins to get the support to move to the next level. >> Yah, so I've sorta got a very simple Hilo play book and you know the first step is you have to know your business. And you have to really understand and prioritize. Again, sometimes I think about not the build, buy decision per say, but maybe the build consume decision. And again, where does it take the effort to go through hiring the people, understanding building those solutions, versus where is it just best to say, "I'm best to consume this product or service from somebody else." So that's number one, and you have to understand your business to do that, really well. The second one is, and we touched on this before, which is getting the right people in the right seats of the bus. Understanding who those citizen data scientists are versus who your developers are, who your analytics people are, who your machine learning people are, and making sure you've got the right people doing the right thing. >> Right. >> And then the last thing is to make sure, to understand that it is a journey. And we like to think about the journey that we go through in sort of three phases, right? Or sort of three swim lanes that could happen, both in parallel, but also as a journey. And we think about those as sort of basic BI and exploratory analytics. How do I learn is there any there there? And fundamentally you're saying, I want to ask and answer a question one time. Think about traditional business reporting. But once you've done that, your goal is always to put something into production. You say, "I've asked and answered once, now I want to ask and answer hundreds, millions, billions of times-- >> Right, right. >> In a row." And the goal is to codify that knowledge into a statistic, an analytic, a business role. And then, how do you start running those within a consistent system? And it's gonna do and force exactly what you just said. Do I have my data in one place? Is it scalable? Is it robust? Is it queryable? Where is it being consumed? How do I capture what's good or bad? And once I start to then define those, I can then start to standardize that within an application workflow and then move into, again, these complex, adaptive, intelligent systems powered by AI machine learning. And so, that's the way we think about it. Know your business, get the people right, understand that it's a systematic journey. >> Right, and then really bake it into the application. >> That's right. >> That's the thing, we don't want to make the same mistake that we do with big data, right? >> Yep. >> Just put it into the application. It's not this stand alone-- >> Correct. >> You know, kinda funny thing. >> Exactly. >> Alright, Jeff, I'll give you the last work before we wrap for the day. So you've been with GE now for about a year and a half, about halfway through 2018. What are your priorities for the next 12 months? If we sit down here, you know June one next year, what are you working on, what's kinda top of mind for you going forward? >> Yah, so top of the line for me, so as I mentioned sort of our first year here was really surveying the landscape, understanding how this company does business, where the opportunities are. Again, where those data driven work flows are. And we have an idea of of that with the core industrial. And so what we've been doing is getting that infrastructure right, getting those people right, getting the V ones of some very powerful systems set up. And so, what I'm gonna be doing over the next year or so is really working with them to scale those out within those core parts of the business, understand how we can create derivative and adjacent products over those, and then how we can take them to market more broadly based upon that, exactly as you said earlier, large scale data that we have available, that customer insight, and that knowledge of how we've been building the stuff, so. >> Alright, I look forward to it. >> I look forward to being back in a year. >> All right, Jeff Erhardt. Thanks for watching. I'm Jeff Frick. You're watching the CUBE from our Palo Alto studios. See you next time. (upbeat orchestra music)

>> Announcer: Live from Chicago, Illinois, it's theCUBE. Covering VeeamOn 2018. Brought to you by VeeamOn. >> We're back. VeeamOn 2018. You're watching theCUBE, the leader in live tech coverage, where we go out to the events and we extract the signal from the noise. Dave Vellante, with my co-host Stu Miniman and Marc Crespi is here. He's the Vice President of Sales Engineering at ExaGrid, another Mass boy. Welcome back to theCUBE. Good to see you again, Marc. >> Thanks, great to be with you guys again. Great to be on another fantastic VeeamOn in the world-class city of Chicago. >> Yeah, it's a great city. What's happening at VeeamOn for ExaGrid this year? >> Quite a few executive meetings, a lot of customer contact, existing customers, prospective customers, meeting with the joint sales teams and so on. We coordinate a lot with VeeamOn in the field and on an engineering level, so great to get off the phone and see each other face to face and really deepen the relationship. >> So, talk a little bit about what the conversation is like with customers, particularly as it relates to data protection. We're hearing a lot on cloud, multi-cloud, intelligent data management. What does that all mean to your customers? >> Sure. So, obviously VeeamOn provides a wealth of different functionality in all of those areas, whether it be the intelligent data management, which includes cloud components, et cetera. We at ExaGrid play a role, mostly on the on-premise side, to be honest, of the equation. And because we typically deal with a quite large customers, the use of the cloud is really, typically relegated for older, more archive oriented data, or long-term retention backup data than it is for primary data, or even primary copy for disaster recovery simply because of the logistics of managing that much data when you may need it. However, the cloud plays a very important role in those types of customers, as many of them have regulatory requirements, compliance requirements to keep data long-term that they may never need to access, or never need to touch. In which case tiering that out to the cloud is a potentially good strategy. >> Marc, one of the things we're watching at this show is how VeeamOn's trying to get deeper and broader into the enterprise. If you can, give us a little color as to how you're seeing, where is VeeamOn being successful, what are customers liking for that kind of solution? >> Sure. We're seeing a significant amount of traction with VeeamOn and enterprise customers. In fact, we met with a large travel agency out here at the show who's looking at both VeeamOn and ExaGrid as a combined solution. So we're working very closely. VeeamOn has a dedicated enterprise team in the field, and they're breaking down doors to a number of the different enterprises. And our solution, the way it scales and its performance profile is very well-suited to the enterprise. We are an enterprise-class company as well, so we're doing cross-introductions for each other and to each other's enterprise customer base as we go. >> Talk a little bit more about your solution, where the sweet spot is. We always talk about horses for courses on theCUBE. >> Marc: Sure. Yeah. >> What's your favorite course? >> So, we define a target customer, the first demographic that we use is typically the amount of data they have under management. Put another way, the amount of primary data they have, or the utilization on their primary storage. And where we typically live, these days is 50 terabyte is kind of the low end, all the way up to multiple petabytes of data being backed up. And we can store many, many weeks, or months, or years of that data because of the data deduplication impact. But that's our sweet spot. And typically that's the most key demographic for us to look at, is how much data they're managing. >> And you're an infrastructure provider, obviously. You have software, but you don't do backup software. That's not your specialty, right? >> That's correct. That's one of the reasons we have such a close relationship with VeeamOn. And, quite honestly, we partner with a number of folks, but VeeamOn is clearly one of our key, if not our key partner because they provide the data protection functionality, the management, et cetera, and we provide the intelligent hyperconverged secondary storage that can store all of that data, deduplicate it, replicate it, and also provide, uniquely, I might add; support for some of VeeamOn's really critical features, like Instant VM Recovery and Virtual Lab and SureBackup. Because of the way our product is architected those features work extremely well with us, where in some cases, in some solutions they don't quite work as well. >> I think back to a number of years ago deduplication was all the talk in the storage industry. How are the latest trends in everything from Flash's adoption, NVMe, and NVMe over fabric coming soon, how's that going to impact what customers are doing in your space? >> Sure, so first I'll tackle the deduplication part of it. There's no question that it's now become an accepted norm. It's rare these days that you're explaining what it is, or what it does. But there still is one left over misconception that I think it's really important for all of us who have deduplication to educate customers. And that is that not every type of deduplication is created equal. Sometimes people conflate it with compression. You know, all compression's kind of the same to a certain extent. The way deduplication is implemented, there are certain characteristics that will either increase the amount of data reduction you get or lessen the amount of data reduction you get. For customers it's really important to know what type of algorithm you're dealing with 'cause that's going to translate to cost over the long term. So that's the first thing. The other trends, the adoption of Flash and so on, really has been more on the primary storage side, where that level of performance is required for high transaction, high performance requiring applications and so on. Because Flash remains quite a bit more expensive than spinning disc is, it's inroads into backup or secondary storage have been somewhat more on a limited basis. >> So, if I understand you correctly, a large part of the data reduction is a function of the algorithm... I don't want to say not so much the workload, but I was always under the impression that the workload determined the sort of data reduction efficacy. >> Marc: Sure. >> Which I'm sure is true, but you're saying the algorithm also has a huge impact. >> It's a combination. So, there's no question that certain data types deduplicate extremely well, other types not as well, and some not at all. You know, pre-compressed, pre-encrypted data tends not to deduplicate well at all. Where the algorithm comes in is there's a couple of elements, not to get to get too much in the weeds, but something called block size, which is basically the size of the objects that you examine when you deduplicate, and then whether or not you do what's called variable-length analysis, which is adjusting to the fact that the data is expanding and shrinking as it's changing. Algorithm's that implement very large block sizes and avoid variable-length technology are going to get much lower deduplication ratios than algorithms that implement both of those elements, smaller object sizes, and variable-length technology. And we're in the latter category of the more aggressive form of deduplication. >> So, you've got greater granularity and the greater ability to drive data reduction ratios, assuming the workload is favorable to that. >> Exactly right. If you were to compare the same workload across the two algorithms, the less aggressive and the more aggressive, the more aggressive is going to do better on that workload than the less aggressive. >> And again, I know it depends on the workload, but are we talking about on a percentage basis 10% better, 20%, 50%, a 100%? >> Marc: Multiples better. Some cases five to 10 times better. >> Even an order of magnitude in some cases. >> Marc: An order of magnitude better, yes, in some cases. >> What about encryption? What's the state of encryption these days? What are you advising customers with regard to encryption? >> Well, for years we've been under the impression that everything's going to have to be encrypted at some point. It's been a slow journey. You know, there's PCI compliance, HIPPA compliance. Obviously, there's been some pretty infamous hacks that have happened and so on. So the way we look at encryption, we have encryption solutions, self-encrypting appliances, and we recommend to customers, even if you don't need encryption today, if there is a slight chance that you'll need it in the future, then go with our encrypting line of appliances. The cost difference is nominal. It's in single-digit, low single-digit percentages, and it's there when you need it. So you don't have to potentially swap after that. We also do encryption any time we move data over the LAN. So we're fully ready for all of these compliances. It's certified encryption, you know, federal level certification, et cetera, so-- >> Yeah, Marc, let us know what companies aren't aware of the need for encryption and I'm going to short those stocks. (laughing) >> Okay, you got it. Yeah, you might want to change your bank. >> All right. Got to ask you. Brady, if you were Robert Kraft, would you have traded Tom Brady? >> Absolutely not. >> That's unanimous, there. Three for three on that. >> Absolutely, no. >> Okay, why not? What would the rationale be? >> I think he's got a lot more to give yet. I think it would have been on par with the Babe Ruth trade. It would have been a historical disaster. You know, he got us to the Super Bowl last year. Granted, Philly inched us out, but I still think he's the GOAT and he's going to stay the GOAT. >> Giselle said Tom Brady can't catch the ball. I would say also, he can't play defense, so-- >> I would agree with that as well. >> All right, what about Garoppolo? Do you think it was the right move to hold onto him, essentially as an insurance policy in case Brady went down before the trade deadline, or should they have been more proactive and gotten more for him? >> I think it probably would have been the right move for the Patriots to hang on to Garoppolo, however, for Garoppolo himself, and for the fact that they needed to get at least something for him, I think it was the right move at the right time. He needs to play. He's a great quarterback. He's already turning that San Francisco franchise around. >> Right. >> So I'm happy to see him play. I actually now start watching 49ers games 'cause I want to root for him. >> Me, too. I'm a fan of Garoppolo. >> Marc: He's a son of the Patriots. >> I agree. I think it was the smart move, Stu to keep him as an insurance policy, just in case. You don't know. I mean, Brady, you know, 40 plus years old. I mean, look what happened last year. >> It's the economics, Dave, though. They weren't going to pay him what he needed to be able to be a backup, and I agree with Marc. He was ready to play, obviously and it is fun to watch him on the 49ers. >> No, we agree. One of 'em had to go, right? Okay, and now we're three for three. So Peter McKay, Patrick Osborne, and now Marc Crespi all say Brady should stay. Right move. We'll see. Hey, they're the favorite to win the Super Bowl next year. Hopefully, they can get there. >> Sounds like I'm in good company. >> Marc, thanks very much for coming back on theCUBE. >> Thank you. It's always a pleasure to see you guys. >> All right, keep it right there, everybody. We'll be back with our next guest right after this short break. You're watching theCUBE, from VeeamOn 2018. (upbeat music)

>> Announcer: Live from New York City It's TheCube. Covering CyberConnect 2017. Brought to you by Centrify and the Institute for Critical Infrastructure Technology. >> It got out of control, they were testing it. Okay, welcome back everyone. We are here live in New York City for CyberConnect 2017. This is Cube's coverage is presented by Centrify. It's an industry event, bringing all the leaders of industry and government together around all the great opportunities to solve the crisis of our generation. That's cyber security. We have Cricket Liu. Chief DNS architect and senior fellow at Infoblox. Cricket, great to see you again. Welcome to theCUBE. >> Thank you, nice to be back John. >> So we're live here and really this is the first inaugural event of CyberConnect. Bringing government and industry together. We saw the retired general on stage talking about some of the history, but also the fluid nature. We saw Jim from Aetna, talking about how unconventional tactics and talking about domains and how he was handling email. That's a DNS problem. >> Yeah, yeah. >> You're the DNS guru. DNS has become a role in this. What's going on here around DNS? Why is it important to CyberConnect? >> Well, I'll be talking tomorrow about the first anniversary, well, a little bit later than the first anniversary of the big DDoS attack on Dyn. The DNS hosting provider up in Manchester, New Hampshire. And trying to determine if we've actually learned anything, have we improved our DNS infrastructure in any way in the ensuing year plus? Are we doing anything from the standards, standpoint on protecting DNS infrastructure. Those sorts of things. >> And certainly one of the highlight examples was mobile users are masked by the DNS on, say, email for example. Jim was pointing that out. I got to ask you, because we heard things like sink-holing addresses, hackers create domain names in the first 48 hours to launch attacks. So there's all kinds of tactical things that are being involved with, lets say, domain names for instance. >> Cricket: Yeah, yeah. >> That's part of the critical infrastructure. So, the question is how, in DDoS attacks, denial-of-service attacks, are coming in in the tens of thousands per day? >> Yeah, well that issue that you talked about, in particular the idea that the bad guys register brand new domain names, domain names that initially have no negative reputation associated with them, my friend Paul Vixie and his new company Farsight Security have been working on that. They have what is called a -- >> John: What's the name of the company again? >> Farsight Security. >> Farsight? >> And they have what's called a Passive DNS Database. Which is a database basically of DNS telemetry that is accumulated from big recursive DNS servers around the internet. So they know when a brand new domain name pops up, somewhere on the internet because someone has to resolve it. And they pump all of these brand new domain names into what's called a response policy zone feed. And you can get for example different thresh holds. I want to see the brand new domain names created over the last 30 minutes or seen over the last 30 minutes. And if you block resolution of those brand new domain names, it turns out you block a tremendous amount of really malicious activity. And then after say, 30 minutes if it's a legitimate domain name it falls off the list and you can resolve it. >> So this says your doing DNS signaling as a service for new name registrations because the demand is for software APIs to say "Hey, I want to create some policy around some techniques to sink-hole domain address hacks. Something like that? >> Yeah, basically this goes hand in hand with this new system response policy zone which allows you to implement DNS policy. Something that we've really never before done with DNS servers, which that's actually not quite true. There have been proprietary solutions for it. But response policy zones are an open solution that give you the ability to say "Hey I do want to allow resolution of this domain name, but not this other domain name". And then you can say "Alright, all these brand new domain names, for the first 30 minutes of their existence I don't want-- >> It's like a background check for domain names. >> Yeah, or like a wait list. Okay, you don't get resolved for the first 30 minutes, that gives the sort of traditional, reputational, analyzers, Spamhaus and Serval and people like that a chance to look you over and say "yeah, it's malicious or it's not malicious". >> So serves to be run my Paul Vixie who is the contributor to the DNS protocol-- >> Right, enormous contributor. >> So we should keep an eye on that. Check it out, Paul Vixie. Alright, so DNS's critical infrastructure that we've been talking about, that you and I, love to riff about DNS and the role What's it enabled? Obviously it's ASCII, but I got to ask you, all these Unicode stuff about the emoji and the open source, really it highlight's the Unicode phenomenon. So this is a hacker potential haven. DNS and Unicode distinction. >> It's really interesting from a DNS standpoint, because we went to a lot of effort within the IETF, the Internet Engineering Task Force, some years ago, back when I was more involved in the IETF, some people spent a tremendous amount of effort coming up with a way to use allow people to use Unicode within domain name. So that you could type something into your browser that was in traditional or simplified Chinese or that was in Arabic or was in Hebrew or any number of other scripts. And you could type that in and it would be translated into something that we call puny code, in the DNS community, which is an ASCII equivalent to that. The issue with that though, becomes that there are, we would say glifs, most people I guess would say characters, but there are characters in Unicode that look just like, say Latin alphabet characters. So there's a lowercase 'a' for example, in cyrillic, it's not a lowercase 'a' in the Latin alphabet, it's a cyrillic 'a', but it looks just like an 'a'. So it's possible for people to register names, domain names, that in there Unicode representation, look like for example, PayPal, which of course has two a's in it, and those two a's could be cyrillic a's. >> Not truly the ASCII representation of PayPal which we resolve through the DNS. >> Exactly, so imagine how subtle an attack that would be if you were able to send out a bunch of email, including the links that said www.-- >> Someone's hacked your PayPal account, click here. >> Yeah, exactly. And if you eyeballed it you'd think Well, sure that's www.PayPal.com, but little do you know it's actually not the -- >> So Jim Ruth talked about applying some unconventional methods, because the bad guys don't subscribe to the conventional methods . They don't buy into it. He said that they change up their standards, is what I wrote down, but that was maybe their sort of security footprint. 1.5 times a day, how does that apply to your DNS world, how do you even do that? >> Well, we're beginning to do more and more with analytics DNS. The passive DNS database that I talked about. More and more big security players, including Infoblox are collecting passive DNS data. And you can run interesting analytics on that passive DNS data. And you can, in some cases, automatically detect suspicious or malicious behavior. For example you can say "Hey, look this named IP address mapping is changing really, really rapidly" and that might be an indication of let's say, fast flux. Or you can say "These domain names have really high entropy. We did an engram analysis of the labels of these". The consequence of that we believe that this resolution of these domain names, is actually being used to tunnel data out of an organization or into an organization. So there's some things you can do with these analytical algorithms in order to suss out suspicious and malicious. >> And you're doing that in as close to real time as possible, presumably right? >> Cricket: That's right. >> And so, now everybody's talking about Edge, Edge computing, Edge analytics. How will the Edge effect your ability to keep up? >> Well, the challenge I think with doing analytics on passive DNS is that you have to be able to collect that data from a lot of places. The more places that you have, the more sensors that you have collecting passive DNS data the better. You need to be able to get it out from the Edge. From those local recursive DNS servers that are actually responding to the query's that come from say your smart phone or your laptop or what have you. If you don't have that kind of data, you've only got, say, big ISPs, then you may not detect the compromise of somebody's corporate network, for example. >> I was looking at some stats when I asked the IOT questions, 'cause you're kind of teasing out kind of the edge of the network and with mobile and wearables as the general was pointing out, is that it's going to create more service area, but I just also saw a story, I don't know if it's from Google or wherever, but 80% plus roughly, websites are going to have SSL HTBS that they're resolving through. And there's reports out here that a lot of the anti virus provisions have been failing because of compromised certificates. And to quote someone from Research Park, and we want to get your reaction to this "Our results show", this is from University of Maryland College Park. "Our results show that compromised certificates pose a bigger threat than we previously believed, and is not restricted to advanced threats and digitally signed malware was common in the wild." Well before Stuxnet. >> Yeah, yeah. >> And so breaches have been caused by compromising certificates of actual authority. So this brings up the whole SSL was supposed to be solving this, that's just one problem. Now you've got the certificates, well before Stuxnet. So Stuxnet really was kind of going on before Stuxnet. Now you've got the edge of the network. Who has the DNS control for these devices? Is it kind of like failing? Is it crumbling? How do we get that trust back? >> That's a good question. One of the issues that we've had is that at various points, CAs, Certificate Authorities, have been conned into issuing certificates for websites that they shouldn't have. For example, "Hey, generate a cert for me". >> John: The Chinese do it all the time. >> Exactly. I run www. Bank of America .com. They give it to the wrong guy. He installs it. We have I think, something like 1,500 top level certification authorities. Something crazy like that. Dan Komenski had a number in one of his blog posts and it was absolutely ridiculous. The number of different CA's that we trust that are built into the most common browsers, like Chrome and Firefox and things like that. We're actually trying to address some of those issues with DNS, so there are two new resource records being introduced to DNS. One is TLSA. >> John: TLSA? >> Yeah, TLSA. And the other one is called CAA I think, which always makes me think of a California Automotive Association. (laughter) But TLSA is basically a way of publishing data in your own zone that says My cert looks like this. You can say "This is my cert." You can just completely go around the CA. And you can say "This is my cert" and then your DNS sec sign your zone and you're done. Or you can do something short of that and you can say "My cert should look like this "and it should have this CA. "This is my CA. "Don't trust any other one" >> So it's metadata about the cert or the cert itself. >> Exactly, so that way if somebody manages to go get a cert for your website, but they get that cert from some untrustworthy CA. I don't know who that would be. >> John: Or a comprimised-- >> Right, or a compromised CA. No body would trust it. No body who actually looks up the TSLA record because they'll go "Oh, Okay. I can see that Infoblox's cert that their CA is Symantech. And this is not a Symantech signed cert. So I'm not going to believe it". And at the same time this CAA record is designed to be consumed by the CA's themselves, and it's a way of saying, say Infoblox can say "We are a customer of Symantech or whoever" And when somebody goes to the cert and says "Hey, I want to generate a certificate for www.Infoblox.com, they'll look it up and say "Oh, they're a Symantech customer, I'm not going to do that for you". >> So it creates trust. So how does this impact the edge of the network, because the question really is, the question that's on everyone's mind is, does the internet of things create more trust or does it create more vulnerabilities? Everyone knows it's a surface area, but still there are technical solutions when you're talking about, how does this play out in your mind? How does Infoblox see it? How do you see it? What's Paul Vixie working on, does that tie into it? Because out in the hinterlands and the edge of the network and the wild, is it like a DNS server on the device. It could be a sensor? How are they resolving things? What is the protocol for these? >> At least this gives you a greater assurance if you're using TLS to encrypt communication between a client and a web server or some other resource out there on the internet. It at least gives you a better assurance that you really aren't being spoofed. That you're going to the right place. That your communications are secure. So that's all really good. IOT, I think of as slightly orthogonal to that. IOT is still a real challenge. I mean there is so many IOT devices out there. I look at IOT though, and I'll talk about this tomorrow, and actually I've got a live event on Thursday, where I'll talk about it some more with my friend Matt Larson. >> John: Is that going to be here in New York? >> Actually we're going to be broadcasting out of Washington, D.C. >> John: Were you streaming that? >> It is streamed. In fact it's only streamed. >> John: Put a plug in for the URL. >> If you go to www.Infoblox.com I think it's one of the first things that will slide into your view. >> So you're putting it onto your company site. Infoblox.com. You and Matt Larson. Okay, cool. Thursday event, check it out. >> It is somewhat embarrassingly called Cricket Liu Live. >> You're a celebrity. >> It's also Matt Larson Live. >> Both of you guys know what you're talking about. It's great. >> So there's a discussion among certain boards of directors that says, "Look, we're losing the battle, "we're losing the war. "We got to shift more on response "and at least cover our butts. "And get some of our response mechanisms in place." What do you advise those boards? What's the right balance between sort of defense perimeter, core infrastructure, and response. >> Well, I would certainly advocate as a DNS guy, that people instrument their DNS infrastructure to the extent that they can to be able to detect evidence of compromise. And that's a relatively straight forward thing to do. And most organizations haven't gone through the trouble to plumb their DNS infrastructure into their, for example, their sim infrastructure, so they can get query log information, they can use RPZs to flag when a client looks up the domain name of a known command and control server, which is a clear indication of compromise. Those sorts of things. I think that's really important. It's a pretty easy win. I do think at this point that we have to resign ourselves to the idea that we have devices on our network that are infected. That game is lost. There's no more crunchy outer shell security. It just doesn't really work. So you have to have defensive depth as they say. >> Now servs has been around for such a long time. It's been one of those threats that just keeps coming. It's like waves and waves. So it looks like there's some things happening, that's cool. So I got to ask you, CyberConnect is the first real inaugural event that brings industry and some obviously government and tech geeks together, but it's not black hat or ETF. It's not those geeky forums. It's really a business community coming together. What's your take of this event? What's your observations? What are you seeing here? >> Well, I'm really excited to actually get the opportunity to talk to people who are chiefly security people. I think that's kind of a novelty for me, because most of the time I think I speak to people who are chiefly networking people and in particular that little niche of networking people who are interested in DNS. Although truth be told, maybe they're not really interested in DNS, maybe they just put up with me. >> Well the community is really strong. The DNS community has always been organically grown and reliable. >> But I love the idea of talking about DNS security to a security audience. And hopefully some of the folks we get to talk to here, will come away from it thinking oh, wow, so I didn't even realize that my DNS infrastructure could actually be a security tool for me. Could actually be helpful in any way in detecting compromise. >> And what about this final question, 'cause I know we got a time check here. But, operational impact of some of these DNS changes that are coming down from Paul Vixie, you and Matt Larson doing some things together, What's the impact of the customer and they say "okay, DNS will play a role in how I role out my architecture. New solutions for cyber, IOT is right around the corner. What's the impact to them in your mind operationally. >> There certainly is some operational impact, for example if you want to subscribe to RPZ feeds, you've got to become a customer of somebody who provides a commercial RPZ feed or somebody who provides a free RPZ feed. You have to plumb that into your DNS infrastructure. You have to make sure that it continues transferring. You have to plumb that into your sim, so when you get a hit against an RPZ, you're notified about it, your security folks. All that stuff is routine day to day stuff. Nothing out of the ordinary. >> No radical plumbing changes. >> Right, but I think one of the big challenges in so many of the organizations that I go to visit, the security organization and the networking organization are in different silos and they don't necessarily communicate a lot. So maybe the more difficult operational challenge is just making sure that you have that communication. And that the security guys know the DNS guys, the networking guys, and vice versa. And they cooperate to work on problems. >> This seems to be the big collaboration thing that's happening here. That it's more of a community model coming together, rather than security. Cricket Liu here, DNS, Chief Architect of DNS and senior fellow of Infoblox. The legend in the DNS community. Paul Vixie amongst the peers. Really that community holding down the fort I'll see a lot of exploits that they have to watch out for. Thanks for your commentary here at the CyberConnect 2017 inaugural event. This is theCUBE. We'll be right back with more after this short break. (techno music)