>> Hello everyone. Welcome to theCUBE's coverage of International Women's Day. I'm John Furrier, host of theCUBE been profiling the leaders in the technology world, women in technology from developers to the boardroom, everything in between. We have two great guests promoting in from Malaysia. Nancy Wang is the general manager, also CUBE alumni from AWS Data Protection, and founder and board chair of Advancing Women in Tech, awit.org. And of course Kate Watts who's the executive director of Advancing Women in Tech.org. So it's awit.org. Nancy, Kate, thanks for coming all the way across remotely from Malaysia. >> Of course, we're coming to you as fast as our internet bandwidth will allow us. And you know, I'm just thrilled today that you get to see a whole nother aspect of my life, right? Because typically we talk about AWS, and here we're talking about a topic near and dear to my heart. >> Well, Nancy, I love the fact that you're spending a lot of time taking the empowerment to go out and help the industries and helping with the advancement of women in tech. Kate, the executive director it's a 501C3, it's nonprofit, dedicating to accelerating the careers of women in groups in tech. Can you talk about the organization? >> Yes, I can. So Advancing Women in Tech was founded in 2017 in order to fix some of the pathway problems that we're seeing on the rise to leadership in the industry. And so we specifically focus on supporting mid-level women in technical roles, get into higher positions. We do that in a few different ways through mentorship programs through building technical skills and by connecting people to a supportive community. So you have your peer network and then a vertical sort of relationships to help you navigate the next steps in your career. So to date we've served about 40,000 individuals globally and we're just looking to expand our reach and impact and be able to better support women in the industry. >> Nancy, talk about the creation, the origination story. How'd this all come together? Obviously the momentum, everyone in the industry's been focused on this for a long time. Where did AWIT come from? Advancing Women in Technology, that's the acronym. Advancing Women in Technology.org, where'd it come from? What's the origination story? >> Yeah, so AWIT really originated from this desire that I had, to Kate's point around, well if you look around right and you know, don't take my word for it, right? Look at stats, look at news reports, or just frankly go on your LinkedIn and see how many women in underrepresented groups are in senior technical leadership roles right out in the companies whose names we all know. And so that was my case back in 2016. And so when I first got the idea and back then I was actually at Google, just another large tech company in the valley, right? It was about how do we get more role models, how we get more, for example, women into leadership roles so they can bring up the next generation, right? And so this is actually part of a longer speech that I'm about to give on Wednesday and part of the US State Department speaker program. In fact, that's why Kate and I are here in Malaysia right now is working with over 200 women entrepreneurs from all over in Southeast Asia, including Malaysia Philippines, Vietnam, Borneo, you know, so many countries where having more women entrepreneurs can help raise the GDP right, and that fits within our overall mission of getting more women into top leadership roles in tech. >> You know, I was talking about Teresa Carlson she came on the program as well for this year this next season we're going to do. And she mentioned the decision between the US progress and international. And she's saying as much as it's still bad numbers, it's worse than outside the United States and needs to get better. Can you comment on the global aspect? You brought that up. I think it's super important to highlight that it's just not one area, it's a global evolution. >> Absolutely, so let me start, and I'd love to actually have Kate talk about our current programs and all of the international groups that we're working with. So as Teresa aptly mentioned there is so much work to be done not just outside the US and North Americas where typically tech nonprofits will focus, but rather if you think about the one to end model, right? For example when I was doing the product market fit workshop for the US State Department I had women dialing in from rice fields, right? So let me just pause there for a moment. They were holding their cell phones up near towers near trees just so that they can get a few minutes of time with me to do a workshop and how to accelerate their business. So if you don't call that the desire to propel oneself or accelerate oneself, not sure what is, right. And so it's really that passion that drove me to spend the next week and a half here working with local entrepreneurs working with policy makers so we can take advantage and really leverage that passion that people have, right? To accelerate more business globally. And so that's why, you know Kate will be leading our contingent with the United Nations Women Group, right? That is focused on women's economic empowerment because that's super important, right? One aspect can be sure, getting more directors, you know vice presidents into companies like Google and Amazon. But another is also how do you encourage more women around the world to start businesses, right? To reach economic and freedom independence, right? To overcome some of the maybe social barriers to becoming a leader in their own country. >> Yes, and if I think about our own programs and our model of being very intentional about supporting the learning development and skills of women and members of underrepresented groups we focused very much on providing global access to a number of our programs. For instance, our product management certification on Coursera or engineering management our upcoming women founders accelerator. We provide both access that you can get from anywhere. And then also very intentional programming that connects people into the networks to be able to further their networks and what they've learned through the skills online, so. >> Yeah, and something Kate just told me recently is these courses that Kate's mentioning, right? She was instrumental in working with the American Council on Education and so that our learners can actually get up to six college credits for taking these courses on product management engineering management, on cloud product management. And most recently we had our first organic one of our very first organic testimonials was from a woman's tech bootcamp in Nigeria, right? So if you think about the worldwide impact of these upskilling courses where frankly in the US we might take for granted right around the world as I mentioned, there are women dialing in from rice patties from other, you know, for example, outside the, you know corporate buildings in order to access this content. >> Can you think about the idea of, oh sorry, go ahead. >> Go ahead, no, go ahead Kate. >> I was going to say, if you can't see it, you can't become it. And so we are very intentional about ensuring that we have we're spotlighting the expertise of women and we are broadcasting that everywhere so that anybody coming up can gain the skills and the networks to be able to succeed in this industry. >> We'll make sure we get those links so we can promote them. Obviously we feel the same way getting the word out. I think a couple things I'd like to ask you guys cause I think you hit a great point. One is the economic advantage the numbers prove that diverse teams perform better number one, that's clear. So good point there. But I want to get your thoughts on the entrepreneurial equation. You mentioned founders and startups and there's also different makeups in different countries. It's not like the big corporations sometimes it's smaller business in certain areas the different cultures have different business sizes and business types. How do you guys see that factoring in outside the United States, say the big tech companies? Okay, yeah. The easy lower the access to get in education than stay with them, in other countries is it the same or is it more diverse in terms of business? >> So what really actually got us started with the US State Department was around our work with women founders. And I love for Kate to actually share her experience working with AWS startups in that capacity. But frankly, you know, we looked at the content and the mentor programs that were providing women who wanted to be executives, you know, quickly realize a lot of those same skills such as finding customers, right? Scaling your product and building channels can also apply to women founders, not just executives. And so early supporters of our efforts from firms such as Moderna up in Seattle, Emergence Ventures, Decibel Ventures in, you know, the Bay Area and a few others that we're working with right now. Right, they believed in the mission and really helped us scale out what is now our existing platform and offerings for women founders. >> Those are great firms by the way. And they also are very founder friendly and also understand the global workforce. I mean, that's a whole nother dimension. Okay, what's your reaction to all that? >> Yes, we have been very intentional about taking the product expertise and the learnings of women and in our network, we first worked with AWS startups to support the development of the curriculum for the recent accelerator for women founders that was held last spring. And so we're able to support 25 founders and also brought in the expertise of about 20 or 30 women from Advancing Women in Tech to be able to be the lead instructors and mentors for that. And so we have really realized that with this network and this individual sort of focus on product expertise building strong teams, we can take that information and bring it to folks everywhere. And so there is very much the intentionality of allowing founders allowing individuals to take the lessons and bring it to their individual circumstances and the cultures in which they are operating. But the product sense is a skill that we can support the development of and we're proud to do so. >> That's awesome. Nancy, I want to ask you some never really talk about data storage and AWS cloud greatness and goodness, here's different and you also work full-time at AWS and you're the founder or the chairman of this great organization. How do you balance both and do you get, they're getting behind you on this, Amazon is getting behind you on this. >> Well, as I say it's always easier to negotiate on the way in. But jokes aside, I have to say the leadership has been tremendously supportive. If you think about, for example, my leaders Wayne Duso who's also been on the show multiple times, Bill Vaas who's also been on the show multiple times, you know they're both founders and also operators entrepreneurs at heart. So they understand that it is important, right? For all of us, it's really incumbent on all of us who are in positions to do so, to create a pathway for more people to be in leadership roles for more people to be successful entrepreneurs. So, no, I mean if you just looked at LinkedIn they're always uploading my vote so they reach to more audiences. And frankly they're rooting for us back home in the US while we're in Malaysia this week. >> That's awesome. And I think that's a good culture to have that empowerment and I think that's very healthy. What's next for you guys? What's on the agenda? Take us through the activities. I know that you got a ton of things happening. You got your event out there, which is why you're out there. There's a bunch of other activities. I think you guys call it the Advancing Women in Tech week. >> Yes, this week we are having a week of programming that you can check out at Advancing Women in Tech.org. That is spotlighting the expertise of a number of women in our space. So it is three days of programming Tuesday, Wednesday and Thursday if you are in the US so the seventh through the ninth, but available globally. We are also going to be in New York next week for the event at the UN and are looking to continue to support our mentorship programs and also our work supporting women founders throughout the year. >> All right. I have to ask you guys if you don't mind get a little market data so you can share with us here at theCUBE. What are you hearing this year that's different in the conversation space around the topics, the interests? Obviously I've seen massive amounts of global acceleration around conversations, more video, things like this more stories are scaling, a lot more LinkedIn activity. It just seems like it's a lot different this year. Can you guys share any kind of current trends you're seeing relative to the conversations and topics being discussed across the the community? >> Well, I think from a needle moving perspective, right? I think due to the efforts of wonderful organizations including the Q for spotlighting all of these awesome women, right? Trailblazing women and the nonprofits the government entities that we work with there's definitely more emphasis on creating access and creating pathways. So that's probably one thing that you're seeing is more women, more investors posting about their activities. Number two, from a global trend perspective, right? The rise of women in security. I noticed that on your agenda today, you had Lena Smart who's a good friend of mine chief information security officer at MongoDB, right? She and I are actually quite involved in helping founders especially early stage founders in the security space. And so globally from a pure technical perspective, right? There's right more increasing regulations around data privacy, data sovereignty, right? For example, India's in a few weeks about to get their first data protection regulation there locally. So all of that is giving rise to yet another wave of opportunity and we want women founders uniquely positioned to take advantage of that opportunity. >> I love it. Kate, reaction to that? I mean founders, more pathways it sounds like a neural network, it sounds like AI enabled. >> Yes, and speaking of AI, with the rise of that we are also hearing from many community members the importance of continuing to build their skills upskill learn to be able to keep up with the latest trends. There's a lot of people wondering what does this mean for my own career? And so they're turning to organizations like Advancing Women in Tech to find communities to both learn the latest information, but also build their networks so that they are able to move forward regardless of what the industry does. >> I love the work you guys are doing. It's so impressive. I think the economic angle is new it's more amplified this year. It's always kind of been there and continues to be. What do you guys hope for by next year this time what do you hope to see different from a needle moving perspective, to use your word Nancy, for next year? What's the visual output in your mind? >> I want to see real effort made towards 50-50 representation in all tech leadership roles. And I'd like to see that happen by 2050. >> Kate, anything on your end? >> I love that. I'm going to go a little bit more touchy-feely. I want everybody in our space to understand that the skills that they build and that the networks they have carry with them regardless of wherever they go. And so to be able to really lean in and learn and continue to develop the career that you want to have. So whether that be at a large organization or within your own business, that you've got the potential to move forward on that within you. >> Nancy, Kate, thank you so much for your contribution. I'll give you the final word. Put a plug in for the organization. What are you guys looking for? Any kind of PSA you want to share with the folks watching? >> Absolutely, so if you're in a position to be a mentor, join as a mentor, right? Help elevate and accelerate the next generation of women leaders. If you're an investor help us invest in more women started companies, right? Women founded startups and lastly, if you are women looking to accelerate your career, come join our community. We have resources, we have mentors and who we have investors who are willing to come in on the ground floor and help you accelerate your business. >> Great work. Thank you so much for participating in our International Women's Day 23 program and we'd look to keep this going quarterly. We'll see you next year, next time. Thanks for coming on. Appreciate it. >> Thanks so much John. >> Thank you. >> Okay, women leaders here. >> Nancy: Thanks for having us >> All over the world, coming together for a great celebration but really highlighting the accomplishments, the pathways the investment, the mentoring, everything in between. It's theCUBE. Bring as much as we can. I'm John Furrier, your host. Thanks for watching.

(upbeat music) >> Welcome back to Supercloud 2, which is an open industry collaboration between technologists, consultants, analysts, and of course, practitioners, to help shape the future of cloud. And at this event, one of the key areas we're exploring is the intersection of cloud and data, and how building value on top of hyperscale clouds and across clouds is evolving, a concept we call supercloud. And we're pleased to welcome Harvir Singh, who's the chief data architect and global head of data at Western Union. Harvir, it's good to see you again. Thanks for coming on the program. >> Thanks, David, it's always a pleasure to talk to you. >> So many things stand out from when we first met, and one of the most gripping for me was when you said to me, "When data moves, money moves." And that's the world we live in today, and really have for a long time. Money has moved as bits, and when it has to move, we want it to move quickly, securely, and in a governed manner. And the pressure to do so is only growing. So tell us how that trend is evolved over the past decade in the context of your industry generally, and Western Union, specifically. Look, I always say to people that we are probably the first ones to introduce digital currency around the world because, hey, somebody around the world needs money, we move data to make that happen. That trend has actually accelerated quite a bit. If you look at the last 10 years, and you look at all these payment companies, digital companies, credit card companies that have evolved, majority of them are working on the same principle. When data moves, money moves. When data is stale, the money goes away, right? I think that trend is continuing, and it's not just the trend is in this space, it's also continuing in other spaces, specifically around, you know, acquisition of customers, communication with customers. It's all becoming digital, and it's, at the end of the day, it's all data being moved from one place or another. At the end of the day, you're not seeing the customer, but you're looking at, you know, the data that he's consuming, and you're making actionable items on it, and be able to respond to what they need. So I think 10 years, it's really, really evolved. >> Hmm, you operate, Western Union operates in more than 200 countries, and you you have what I would call a pseudo federated organization. You're trying to standardize wherever possible on the infrastructure, and you're curating the tooling and doing the heavy lifting in the data stack, which of course lessens the burden on the developers and the line of business consumers, so my question is, in operating in 200 countries, how do you deal with all the diversity of laws and regulations across those regions? I know you're heavily involved in AWS, but AWS isn't everywhere, you still have some on-prem infrastructure. Can you paint a picture of, you know, what that looks like? >> Yeah, a few years ago , we were primarily mostly on-prem, and one of the biggest pain points has been managing that infrastructure around the world in those countries. Yes, we operate in 200 countries, but we don't have infrastructure in 200 countries, but we do have agent locations in 200 countries. United Nations says we only have like 183 are countries, but there are countries which, you know, declare themselves countries, and we are there as well because somebody wants to send money there, right? Somebody has an agent location down there as well. So that infrastructure is obviously very hard to manage and maintain. We have to comply by numerous laws, you know. And the last few years, specifically with GDPR, CCPA, data localization laws in different countries, it's been a challenge, right? And one of the things that we did a few years ago, we decided that we want to be in the business of helping our customers move money faster, security, and with complete trust in us. We don't want to be able to, we don't want to be in the business of managing infrastructure. And that's one of the reasons we started to, you know, migrate and move our journey to the cloud. AWS, obviously chosen first because of its, you know, first in the game, has more locations, and more data centers around the world where we operate. But we still have, you know, existing infrastructure, which is in some countries, which is still localized because AWS hasn't reached there, or we don't have a comparable provider there. We still manage those. And we have to comply by those laws. Our data privacy and our data localization tech stack is pretty good, I would say. We manage our data very well, we manage our customer data very well, but it comes with a lot of complexity. You know, we get a lot of requests from European Union, we get a lot of requests from Asia Pacific every pretty much on a weekly basis to explain, you know, how we are taking controls and putting measures in place to make sure that the data is secured and is in the right place. So it's a complex environment. We do have exposure to other clouds as well, like Google and Azure. And as much as we would love to be completely, you know, very, very hybrid kind of an organization, it's still at a stage where we are still very heavily focused on AWS yet, but at some point, you know, we would love to see a world which is not reliant on a single provider, but it's more a little bit more democratized, you know, as and when what I want to use, I should be able to use, and pay-per-use. And the concept started like that, but it's obviously it's now, again, there are like three big players in the market, and, you know, they're doing their own thing. Would love to see them come collaborate at some point. >> Yeah, wouldn't we all. I want to double-click on the whole multi-cloud strategy, but if I understand it correctly, and in a perfect world, everything on-premises would be in the cloud is, first of all, is that a correct statement? Is that nirvana for you or not necessarily? >> I would say it is nirvana for us, but I would also put a caveat, is it's very tricky because from a regulatory perspective, we are a regulated entity in many countries. The regulators would want to see some control if something happens with a relationship with AWS in one country, or with Google in another country, and it keeps happening, right? For example, Russia was a good example where we had to switch things off. We should be able to do that. But if let's say somewhere in Asia, this country decides that they don't want to partner with AWS, and majority of our stuff is on AWS, where do I go from there? So we have to have some level of confidence in our own infrastructure, so we do maintain some to be able to fail back into and move things it needs to be. So it's a tricky question. Yes, it's nirvana state that I don't have to manage infrastructure, but I think it's far less practical than it said. We will still own something that we call it our own where we have complete control, being a financial entity. >> And so do you try to, I'm sure you do, standardize between all the different on-premise, and in this case, the AWS cloud or maybe even other clouds. How do you do that? Do you work with, you know, different vendors at the various places of the stack to try to do that? Some of the vendors, you know, like a Snowflake is only in the cloud. You know, others, you know, whether it's whatever, analytics, or storage, or database, might be hybrid. What's your strategy with regard to creating as common an experience as possible between your on-prem and your clouds? >> You asked a question which I asked when I joined as well, right? Which question, this is one of the most important questions is how soon when I fail back, if I need to fail back? And how quickly can I, because not everything that is sitting on the cloud is comparable to on-prem or is backward compatible. And the reason I say backward compatible is, you know, there are, our on-prem cloud is obviously behind. We haven't taken enough time to kind of put it to a state where, because we started to migrate and now we have access to infrastructure on the cloud, most of the new things are being built there. But for critical application, I would say we have chronology that could be used to move back if need to be. So, you know, technologies like Couchbase, technologies like PostgreSQL, technologies like Db2, et cetera. We still have and maintain a fairly large portion of it on-prem where critical applications could potentially be serviced. We'll give you one example. We use Neo4j very heavily for our AML use cases. And that's an important one because if Neo4j on the cloud goes down, and it's happened in the past, again, even with three clusters, having all three clusters going down with a DR, we still need some accessibility of that because that's one of the biggest, you know, fraud and risk application it supports. So we do still maintain some comparable technology. Snowflake is an odd one. It's obviously there is none on-prem. But then, you know, Snowflake, I also feel it's more analytical based technology, not a transactional-based technology, at least in our ecosystem. So for me to replicate that, yes, it'll probably take time, but I can live with that. But my business will not stop because our transactional applications can potentially move over if need to. >> Yeah, and of course, you know, all these big market cap companies, so the Snowflake or Databricks, which is not public yet, but they've got big aspirations. And so, you know, we've seen things like Snowflake do a deal with Dell for on-prem object store. I think they do the same thing with Pure. And so over time, you see, Mongo, you know, extending its estate. And so over time all these things are coming together. I want to step out of this conversation for a second. I just ask you, given the current macroeconomic climate, what are the priorities? You know, obviously, people are, CIOs are tapping the breaks on spending, we've reported on that, but what is it? Is it security? Is it analytics? Is it modernization of the on-prem stack, which you were saying a little bit behind. Where are the priorities today given the economic headwinds? >> So the most important priority right now is growing the business, I would say. It's a different, I know this is more, this is not a very techy or a tech answer that, you know, you would expect, but it's growing the business. We want to acquire more customers and be able to service them as best needed. So the majority of our investment is going in the space where tech can support that initiative. During our earnings call, we released the new pillars of our organization where we will focus on, you know, omnichannel digital experience, and then one experience for customer, whether it's retail, whether it's digital. We want to open up our own experience stores, et cetera. So we are investing in technology where it's going to support those pillars. But the spend is in a way that we are obviously taking away from the things that do not support those. So it's, I would say it's flat for us. We are not like in heavily investing or aggressively increasing our tech budget, but it's more like, hey, switch this off because it doesn't make us money, but now switch this on because this is going to support what we can do with money, right? So that's kind of where we are heading towards. So it's not not driven by technology, but it's driven by business and how it supports our customers and our ability to compete in the market. >> You know, I think Harvir, that's consistent with what we heard in some other work that we've done, our ETR partner who does these types of surveys. We're hearing the same thing, is that, you know, we might not be spending on modernizing our on-prem stack. Yeah, we want to get to the cloud at some point and modernize that. But if it supports revenue, you know, we'll invest in that, and get the, you know, instant ROI. I want to ask you about, you know, this concept of supercloud, this abstracted layer of value on top of hyperscale infrastructure, and maybe on-prem. But we were talking about the integration, for instance, between Snowflake and Salesforce, where you got different data sources and you were explaining that you had great interest in being able to, you know, have a kind of, I'll say seamless, sorry, I know it's an overused word, but integration between the data sources and those two different platforms. Can you explain that and why that's attractive to you? >> Yeah, I'm a big supporter of action where the data is, right? Because the minute you start to move, things are already lost in translation. The time is lost, you can't get to it fast enough. So if, for example, for us, Snowflake, Salesforce, is our actionable platform where we action, we send marketing campaigns, we send customer communication via SMS, in app, as well as via email. Now, we would like to be able to interact with our customers pretty much on a, I would say near real time, but the concept of real time doesn't work well with me because I always feel that if you're observing something, it's not real time, it's already happened. But how soon can I react? That's the question. And given that I have to move that data all the way from our, let's say, engagement platforms like Adobe, and particles of the world into Snowflake first, and then do my modeling in some way, and be able to then put it back into Salesforce, it takes time. Yes, you know, I can do it in a few hours, but that few hours makes a lot of difference. Somebody sitting on my website, you know, couldn't find something, walked away, how soon do you think he will lose interest? Three hours, four hours, he'll probably gone, he will never come back. I think if I can react to that as fast as possible without too much data movement, I think that's a lot of good benefit that this kind of integration will bring. Yes, I can potentially take data directly into Salesforce, but I then now have two copies of data, which is, again, something that I'm not a big (indistinct) of. Let's keep the source of the data simple, clean, and a single source. I think this kind of integration will help a lot if the actions can be brought very close to where the data resides. >> Thank you for that. And so, you know, it's funny, we sometimes try to define real time as before you lose the customer, so that's kind of real time. But I want to come back to this idea of governed data sharing. You mentioned some other clouds, a little bit of Azure, a little bit of Google. In a world where, let's say you go more aggressively, and we know that for instance, if you want to use Google's AI tools, you got to use BigQuery. You know, today, anyway, they're not sort of so friendly with Snowflake, maybe different for the AWS, maybe Microsoft's going to be different as well. But in an ideal world, what I'm hearing is you want to keep the data in place. You don't want to move the data. Moving data is expensive, making copies is badness. It's expensive, and it's also, you know, changes the state, right? So you got governance issues. So this idea of supercloud is that you can leave the data in place and actually have a common experience across clouds. Let's just say, let's assume for a minute Google kind of wakes up, my words, not yours, and says, "Hey, maybe, you know what, partnering with a Snowflake or a Databricks is better for our business. It's better for the customers," how would that affect your business and the value that you can bring to your customers? >> Again, I would say that would be the nirvana state that, you know, we want to get to. Because I would say not everyone's perfect. They have great engineers and great products that they're developing, but that's where they compete as well, right? I would like to use the best of breed as much as possible. And I've been a person who has done this in the past as well. I've used, you know, tools to integrate. And the reason why this integration has worked is primarily because sometimes you do pick the best thing for that job. And Google's AI products are definitely doing really well, but, you know, that accessibility, if it's a problem, then I really can't depend on them, right? I would love to move some of that down there, but they have to make it possible for us. Azure is doing really, really good at investing, so I think they're a little bit more and more closer to getting to that state, and I know seeking our attention than Google at this point of time. But I think there will be a revelation moment because more and more people that I talk to like myself, they're also talking about the same thing. I'd like to be able to use Google's AdSense, I would like to be able to use Google's advertising platform, but you know what? I already have all this data, why do I need to move it? Can't they just go and access it? That question will keep haunting them (indistinct). >> You know, I think, obviously, Microsoft has always known, you know, understood ecosystems. I mean, AWS is nailing it, when you go to re:Invent, it's all about the ecosystem. And they think they realized they can make a lot more money, you know, together, than trying to have, and Google's got to figure that out. I think Google thinks, "All right, hey, we got to have the best tech." And that tech, they do have the great tech, and that's our competitive advantage. They got to wake up to the ecosystem and what's happening in the field and the go-to-market. I want to ask you about how you see data and cloud evolving in the future. You mentioned that things that are driving revenue are the priorities, and maybe you're already doing this today, but my question is, do you see a day when companies like yours are increasingly offering data and software services? You've been around for a long time as a company, you've got, you know, first party data, you've got proprietary knowledge, and maybe tooling that you've developed, and you're becoming more, you're already a technology company. Do you see someday pointing that at customers, or again, maybe you're doing it already, or is that not practical in your view? >> So data monetization has always been on the charts. The reason why it hasn't seen the light is regulatory pressure at this point of time. We are partnering up with certain agencies, again, you know, some pilots are happening to see the value of that and be able to offer that. But I think, you know, eventually, we'll get to a state where our, because we are trying to build accessible financial services, we will be in a state that we will be offering those to partners, which could then extended to their customers as well. So we are definitely exploring that. We are definitely exploring how to enrich our data with other data, and be able to complete a super set of data that can be used. Because frankly speaking, the data that we have is very interesting. We have trends of people migrating, we have trends of people migrating within the US, right? So if a new, let's say there's a new, like, I'll give you an example. Let's say New York City, I can tell you, at any given point of time, with my data, what is, you know, a dominant population in that area from migrant perspective. And if I see a change in that data, I can tell you where that is moving towards. I think it's going to be very interesting. We're a little bit, obviously, sometimes, you know, you're scared of sharing too much detail because there's too much data. So, but at the end of the day, I think at some point, we'll get to a state where we are confident that the data can be used for good. One simple example is, you know, pharmacies. They would love to get, you know, we've been talking to CVS and we are talking to Walgreens, and trying to figure out, if they would get access to this kind of data demographic information, what could they do be better? Because, you know, from a gene pool perspective, there are diseases and stuff that are very prevalent in one community versus the other. We could probably equip them with this information to be able to better, you know, let's say, staff their pharmacies or keep better inventory of products that could be used for the population in that area. Similarly, the likes of Walmarts and Krogers, they would like to have more, let's say, ethnic products in their aisles, right? How do you enable that? That data is primarily, I think we are the biggest source of that data. So we do take pride in it, but you know, with caution, we are obviously exploring that as well. >> My last question for you, Harvir, is I'm going to ask you to do a thought exercise. So in that vein, that whole monetization piece, imagine that now, Harvir, you are running a P&L that is going to monetize that data. And my question to you is a there's a business vector and a technology vector. So from a business standpoint, the more distribution channels you have, the better. So running on AWS cloud, partnering with Microsoft, partnering with Google, going to market with them, going to give you more revenue. Okay, so there's a motivation for multi-cloud or supercloud. That's indisputable. But from a technical standpoint, is there an advantage to running on multiple clouds or is that a disadvantage for you? >> It's, I would say it's a disadvantage because if my data is distributed, I have to combine it at some place. So the very first step that we had taken was obviously we brought in Snowflake. The reason, we wanted our analytical data and we want our historical data in the same place. So we are already there and ready to share. And we are actually participating in the data share, but in a private setting at the moment. So we are technically enabled to share, unless there is a significant, I would say, upside to moving that data to another cloud. I don't see any reason because I can enable anyone to come and get it from Snowflake. It's already enabled for us. >> Yeah, or if somehow, magically, several years down the road, some standard developed so you don't have to move the data. Maybe there's a new, Mogli is talking about a new data architecture, and, you know, that's probably years away, but, Harvir, you're an awesome guest. I love having you on, and really appreciate you participating in the program. >> I appreciate it. Thank you, and good luck (indistinct) >> Ah, thank you very much. This is Dave Vellante for John Furrier and the entire Cube community. Keep it right there for more great coverage from Supercloud 2. (uplifting music)

>> From theCUBE studios in Palo Alto in Boston, bringing you data-driven insights from theCUBE in ETR. This is Breaking Analysis with Dave Vellante. >> Despite the more than $100 billion spent each year fighting Cyber-crime. When we do an end-of-the year look back and ask "How did we do?" The answer is invariably the same, "Worse than last year." Pre pandemic, the picture was disheartening, but since March of 2020 the situation has only worsened as cyber-criminals have become increasingly sophisticated, better funded and more brazen. SecOps pros continue to fight, but unlike conventional wars, this one has no end. Now the flip side of course, is that markets continue to value cybersecurity firms at significant premiums. Because this huge market will continue to grow by double digits for the foreseeable future. Hello and welcome to this week's Wikibon theCUBE Insights powered by ETR. In this Breaking Analysis, we look at the state of cybersecurity in 2021 and beyond. We'll update you with the latest survey data from enterprise technology research and share the fundamentals that have investors piling into the security space like never before. Let's start with the customer view. Cybersecurity remains the number one priority for CIOs and CSOs. This latest ETR survey, once again asked IT buyers to rank their top priorities for the next 12 months. Now the last three polling period dating back to last March. Cybersecurity has outranked every top spending category, including cloud, data analytics, productivity software, networking, AI, and automation or RPA. Now this shouldn't surprise anybody, but it underscores the challenges that organizations face. Not only are they in the midst of a non-optional digital transformation, but they have to also fund a cyber war that has no ceasefires, no truces, and no exit path. Now there's much more going on in cybersecurity than ransomware, but certainly that has the attention of executives. And it's becoming more and more lucrative for attackers. Here's a snapshot of some of the more well-documented attacks this decade many which have occurred in very recent months. CNA Financial, they got hit earlier this year and paid a $40 million ransom. The Ireland Health Service also got hit this year and refused to pay the ransom, but it's estimated that the cost to recover and the damage to the organization exceeded half a billion dollars. The request was for a $20 million ransom. The JBS meat company hack, they paid $11 million. CWT travel paid $5 million. The disruption from the Colonial Pipeline company, was widely reported they paid more than $4 million, as the Brenntag, the chemical company. The NBA got hit. Computer makers, Quanta and Acer also. More than 2,000 random attacks were reported to the FBI in the first seven months of 2021. Up more than 60% from 2020. Now, as I've said many times, you don't have to be a genius to be a ransomware as today. Anyone can go on the dark web, tap into ransomware as a service. Attackers, they have insidious names like darkside, evil, the cobalt, crime gang, wizard spider, the Lazarus gang, and numerous others. Criminals they have negotiation services is most typically the attackers, they'll demand a specific amount of money but they're willing to compromise in an exchange of cryptocurrency for decryption keys. And as mentioned, it's not just ransomware supply chain attacks like the solar winds hack hit organizations within the U.S government and companies like Mimecast this year. Now, while these attacks often do end up in a ransom situation. The attackers sometimes find it more lucrative to live off the land and stealth fashion and ex filtrates sensitive data that can be sold or in the case of many financial institution attacks they'll steal information from say a chief investment officer that signals an upcoming trading strategy and then the attackers will front run that trade in the stock market. Now, of course phishing, remains one of the most prominent threats. Only escalated by the work from home trend as users bring their own devices and of course home networks are less secure. So it's bad, worse than ever before. But you know, if there's a problem, entrepreneurs and investors, they're going to be there to solve it. So here's a LinkedIn post from one of the top investors in the business, Mike Speiser. He was a founding investor in Snowflake. He helped get pure storage to escape velocity and many, many other successes. This hit my LinkedIn feed the other day, his company Sutter Hill Ventures is co-leading a 1.3 Series D on an $8.3 billion valuation. They're putting in over $200 million. Now Lacework is a threat detection software company that looks at security as a data problem and they monitor exposures across clouds. So very timely. So watch that company. They're going to soar. Now the right hand chart shows venture investments in cybersecurity over the past several years. You can see it exploded in 2019 to $7.6 billion. And people thought the market was peaking at that time, if you recall. But then investments rose a little bit to $7.8 billion in 2020 right in the middle of lockdown. And then the hybrid work, the cloud, the new normal thesis kicked in big time. It's in full gear this year. You can see nearly $12 billion invested in cybersecurity in the first half of 2021 alone. So the money keeps coming in as the problem gets worse and the market gets more crowded. Now we'd like to show this slide from Optiv, it's their security taxonomy. It'll make your eyes cross. It's so packed with companies in different sectors. We'll put a link in our posts, so you can stare at this. We've used this truck before. It's pretty good. It's comprehensive and it's worth spending some time to see what that landscape looks like. But now let's reduce this down a bit and bring in some of the ETR data. This is survey data from October that shows net score or spending momentum on the vertical axis and market share or pervasiveness in the dataset on the horizontal axis. That's a measure of mentioned share if you will. Now this is just isolated on the information security sector within the ETR taxonomies. No filters in terms of the number of responses. So it's every company that ETR picks up in cybersecurity from its buyer surveys. Now companies above that red line, we consider them to have a highly elevated spending momentum for their products and services. And you can see, there are a lot of companies that are in this map first of all, and several above that magic mark. So you can see the momentum of Microsoft and Palo Alto. That's most impressive because of their size, their pervasiveness in the study, Cisco and Splunk are also quite prominent. They don't have as much spending momentum, but they're pretty respectable. And you can see the companies that have been real movers in this market that we've been reporting on for a while. Okta, CrowdStrike, Zscaler, CyberArk, SailPoint, Authzero, all companies that we've extensively covered in previous breaking analysis episodes as the up and comers. And isn't it interesting that Datadog is now showing up in the vertical axis. You see that in the left-hand side up high, they're becoming more and more competitive to Splunk in this space as an alternative and lines are blurring between observability, log analytics, security, and as we previously reported even backup and recovery. But now let's simplify this picture a bit more and filter down a little bit further. This chart shows the same X, Y view. Same data construct and framework, but we required more than a hundred responses to hit the chart. So the companies, they have to have a notable market presence in the ETR survey. It's perhaps a bit less crowded, but still very packed. Isn't it? You can see firms that are less prominent in the space like Datadog fell off. The big companies we mentioned, obviously still prominent Microsoft, Palo Alto, Cisco and Splunk and then those with real momentum, they stand out a little bit. There's somewhat smaller, but they're gaining traction in the market. As we felt they would Okta and Auth zero, which Okta acquired as we reported on earlier this year, both showing strength as our CrowdStrike, Zscaler, CyberArk, which does identity and competition with Okta and SentinelOne, which went public mid this year. The company SentinelOne uses AI to do threat detection and has been doing quite well. SalePoint and Proofpoint are right on that red elevated line and then there's a big pack in the middle. Look, this is not an easy market to track. It's virtually every company plays in security. Look, AWS says some of the most advanced security in the business but they're not in the chart specifically, but you see Microsoft is. Because much of AWS security is built into services. Amazon customers heavily rely on the Amazon ecosystem which is in the Amazon marketplace for security products. And often they associate their security spend with those partners and not necessarily Amazon. And you'll see networking companies you see right there, like Juniper and the bottom there and in the ETR data set and the players like VMware in the middle of the pack. They've been really acquisitive for example, with carbon black. And the, of course, you've got a lot of legacy players like McAfee and RSA and IBM. Look, virtually every company has a security story and that will only become more common in the coming years. Now here's another look at the ETR data it's in the raw form, but it'll give you a sense of two things; One is how the data from the previous chart is plotted. And two, it gives you a time series of the data. So the data lists the top companies in the ETR data sets sorted by the October net score in the right most column. Again, that measures spending momentum. So to make the cut here, you had to have more than a hundred mentions which is shown on the left-hand side of the chart that shared N, IE that's shared accounts in the dataset. And you can track the data from last October, July of this year and the most recent October, 2021 survey. So we, drew that red line just about at the 40% net score market coincidentally, there are 10 companies that are over that figure over that bar. We sometimes call out the four star companies. We give four stars to those companies that both are in the top 10 and spending momentum and the top in prominence are shared N in the dataset. So some of these 10 would fit into that profile by that methodology, specifically, Microsoft, Okta, CrowdStrike, and Palo Alto networks. They would be the four star companies. Now a couple of other things to point out here, DDoS attacks, they're still relevant, and they're real threat. So a company like CloudFlare which is just above that red line they play in that space. Now we've also shaded the companies in the fat middle. A lot of these companies like Cisco and Splunk for example, they're major players in the security space with very strong offerings and customer affinity. We sometimes give them two stars. So this is what makes this market so interesting. It's not like the high end discourage market where literally every vendor in the Gartner magic quadrant is up in the right, okay. And there's only five or four or five, six vendors there. This market is diverse with many, many segments and sub segments, and it's such a vital space. And there's so many holes to fill with an ever changing threat landscape as we've seen in the last two years. So this is in part which makes it such a good market for investors. There's a lot of room for growth and not just from stealing market share. That's certainly an opportunity there, but things like cloud, multi-cloud, shifting end points, the edge ,and so forth make this space really ripe for investments. And to underscore this, we put together this little chart of some of the pure play security firms to see how their stock performance has done recently. So you can see that here, you know, it's a little hard to read, but it's not hard to see that Okta, CrowdStrike, Zscaler on the left have been big movers. These charts where possible all show a cross here, starting at the lockdown last year. The only exception is SentinelOne which IPO mid this year. So that's the point March, 2020 when the whole world changed and security priorities really started to shift to accommodate the work from home. But it's quite obvious that since the pandemic, these six companies have been on a tear for the fundamental reason that hybrid work has created a shift in spending priorities for CSOs. No longer are organizations just spending on hardening a perimeter, that perimeter has been blown away. The network is flattening. Work is what you do, it's no longer a place. As such threats are on the rise and cloud, endpoint security, identity access tools there become increasingly vital and the vendors who provide them are on the rise. So it's no surprise that the players that we've listed here which play quite prominently in those markets are all on fire. So now in summary, I want to stress that while the picture is sometimes discouraging. The entire world is becoming more and more tuned in to the cyber threat. And that's a good thing. Money is pouring in. Look, technology got us into this problem and technology is a defensive weapon that will help us continue this fight. But it's going to take more than technology. And I want to share something. We get dozens and dozens of in bounds this time of the year because we do an annual predictions posts. So folks and they want to help us out. So now most of the in bounds and the predictions that we get, they're just kind of observations or frankly, non predictions that can't really be measured as like where you right, or where you're wrong. So for the most part I like predictions that are binary. For example, last December we predicted their IT spending in 2021 would rebound and grow at 4% relative to 2020. Well, it did rebound but that prediction really wasn't as accurate as I'd like. It was frankly wrong. We think it's actually the market's going to actually grow. Spending's going to grow more like 7% this year. Not to worry plenty of our predictions came true, but we'll leave that for another day. Anyway, I got an email from Dean Fisk of Fisk partners. It's a PR firm representing an individual named Lyndon Brown chief of strategy officer of Pondurance. Pondurance is a security consultancy. And the email had the standard, Hey, in case you're working on a predictions post this year end, blah, blah, blah. But instead of sharing with me, a bunch of non predictions, the notes said here's some trends in cybersecurity that might be worth thinking about. And there were a few predictions sprinkled in there, but I wanted to call it a couple of the comments from Linden Brown, whom I don't know, I never met the guy, but I really thought his trends were spot on. The first was a stat I'll share that the United Nations report cyber crime is up 600% due to the pandemic. If as if I couldn't feel worse already. His first point though was that the hybrid workplace will be the new frontier for cyber. Yes, we totally agree. There are permanent shifts taking place. And we actually predicted that last year, but he further cited that many companies went from zero to full digital transformation overnight and many are still on that journey. And his point is that hybrid work is going to require a complete overhaul of how we think about security. We think this is very true. Now the other point that stood out is that governments are going to crack down on this behavior. And we've seen this where criminals have had their critical infrastructure dismantled by governments. No doubt the U.S government has the capabilities to do so. And it is very much focused on this issue. But it's tricky as Robert Gates, who was the former defense secretary, told me a few years back in theCUBE. He said, well, we have the best offense. We also have the most to lose. So we have to be very careful, but Linden's key point was you are going to see a much more forward and aggressive public policy and new laws that give crime fighters more latitude . Again, it's tricky kind of like the Patriot act was tricky but it's coming. Now, another call-out from Linden shares his assertion that natural disasters will bring increased cyber risk. And I thought this was a really astute point because natural disasters they're on the rise. And when there's chaos, there's cash opportunities for criminals. And I'll add to this that the supply chain risk is far from over. This is going to be continuing theme this coming year and beyond. And one of the things that Linden Brown said in his note to me is essentially you can't take humans out of the equation. Automation alone can't solve the problem, but some companies operate as though they can. Just as bad human behavior, can tramp good security, Good human education and behavior is going to be a key weapon in this endless war. Now the last point is we're going to see continued escalation government crackdowns are going to bring retaliation and to Gates' point. The U.S has a lot at stake. So expect insurance premiums are going to go through the roof. That's assuming you can even get cyber insurance. And so we got to hope for the best, but for sure, we have to plan for the worst because it's coming. Deploy technology aggressively but people in process will ultimately be the other ingredients that allow us to live to battle for another day. Okay. That's a wrap for today. Remember these episodes they're all available as podcasts, wherever you listen just search "breaking analysis" podcast. Check out ETR his website at ETR.plus. We also publish a full report every week on Wikibond.com and siliconangle.com. You can get in touch. Email me @david.volante@tsiliconangle.com or you can DM me @dvellante. Comment on our LinkedIn posts. This is Dave Vellante for theCUBE insights powered by ETR. Have a great week. everybody stay safe, be well. And we'll see you next time. (techno music)

(up-tempo music) >> Welcome to today's session of the cube's presentation of the AWS startup showcase. The next big thing in AI security and life sciences. Today, we'll be speaking with Aizon, as part of our life sciences track and I'm pleased to welcome the co-founder as well as the chief science officer of Aizon: Toni Monzano, will be discussing how artificial intelligence is driving key processes in pharma manufacturing. Welcome to the show. Thanks so much for being with us today. >> Thank you Natalie to you and to your introduction. >> Yeah. Well, as you know industry 4.0 is revolutionizing manufacturing across many industries. Let's talk about how it's impacting biotech and pharma and as well as Aizon's contributions to this revolution. >> Well, actually pharmacogenetics is totally introducing a new concept of how to manage processes. So, nowadays the industry is considering that everything is particularly static, nothing changes and this is because they don't have the ability to manage the complexity and the variability around the biotech and the driving factor in processes. Nowadays, with pharma - technologies cloud, our computing, IOT, AI, we can get all those data. We can understand the data and we can interact in real time, with processes. This is how things are going on nowadays. >> Fascinating. Well, as you know COVID-19 really threw a wrench in a lot of activity in the world, our economies, and also people's way of life. How did it impact manufacturing in terms of scale up and scale out? And what are your observations from this year? >> You know, the main problem when you want to do a scale-up process is not only the equipment, it is also the knowledge that you have around your process. When you're doing a vaccine on a smaller scale in your lab, the only parameters you're controlling in your lab, they have to be escalated when you work from five liters to 2,500 liters. How to manage this different of a scale? Well, AI is helping nowadays in order to detect and to identify the most relevant factors involved in the process. The critical relationship between the variables and the final control of all the full process following a continued process verification. This is how we can help nowadays in using AI and cloud technologies in order to accelerate and to scale up vaccines like the COVID-19. >> And how do you anticipate pharma manufacturing to change in a post COVID world? >> This is a very good question. Nowadays, we have some assumptions that we are trying to overpass yet with human efforts. Nowadays, with the new situation, with the pandemic that we are living in, the next evolution that we are doing humans will take care about the good practices of the new knowledge that we have to generate. So AI will manage the repetitive tasks, all the human condition activity that we are doing, So that will be done by AI, and humans will never again do repetitive tasks in this way. They will manage complex problems and supervise AI output. >> So you're driving more efficiencies in the manufacturing process with AI. You recently presented at the United nations industrial development organization about the challenges brought by COVID-19 and how AI is helping with the equitable distribution of vaccines and therapies. What are some of the ways that companies like Aizon can now help with that kind of response? >> Very good point. Could you imagine you're a big company, a top pharma company, that you have an intellectual property of COVID-19 vaccine based on emergency and principle, and you are going to, or you would like to, expand this vaccination in order not to get vaccination, also to manufacture the vaccine. What if you try to manufacture these vaccines in South Africa or in Asia in India? So the secret is to transport, not only the raw material not only the equipment, also the knowledge. How to appreciate how to control the full process from the initial phase 'till their packaging and the vials filling. So, this is how we are contributing. AI is packaging all this knowledge in just AI models. This is the secret. >> Interesting. Well, what are the benefits for pharma manufacturers when considering the implementation of AI and cloud technologies. And how can they progress in their digital transformation by utilizing them? >> One of the benefits is that you are able to manage the variability the real complexity in the world. So, you can not create processes, in order to manufacture drugs, just considering that the raw material that you're using is never changing. You cannot consider that all the equipment works in the same way. You cannot consider that your recipe will work in the same way in Brazil than in Singapore. So the complexity and the variability is must be understood as part of the process. This is one of the benefits. The second benefit is that when you use cloud technologies, you have not a big care about computing's licenses, software updates, antivirals, scale up of cloud ware computing. Everything is done in the cloud. So well, this is two main benefits. There are more, but this is maybe the two main ones. >> Yeah. Well, that's really interesting how you highlight how this is really. There's a big shift how you handle this in different parts of the world. So, what role does compliance and regulation play here? And of course we see differences the way that's handled around the world as well. >> Well, I think that is the first time the human race in the pharma - let me say experience - that we have a very strong commitment from the 30 bodies, you know, to push forward using this kind of technologies actually, for example, the FDA, they are using cloud, to manage their own system. So why not use them in pharma? >> Yeah. Well, how does AWS and Aizon help manufacturers address these kinds of considerations? >> Well, we have a very great partner. AWS, for us, is simplifying a lot our life. So, we are a very, let me say different startup company, Aizon, because we have a lot of PhDs in the company. So we are not in the classical geeky company with guys all day parameter developing. So we have a lot of science inside the company. So this is our value. So everything that is provided by Amazon, why we have to aim to recreate again so we can rely on Sage Maker. we can rely on Cogito, we can rely on Landon we can rely on Esri to have encryption data with automatic backup. So, AWS is simplifying a lot of our life. And we can dedicate all our knowledge and all our efforts to the things that we know: pharma compliance. >> And how do you anticipate that pharma manufacturing will change further in the 2021 year? Well, we are participating not only with business cases. We also participate with the community because we are leading an international project in order to anticipate this kind of new breakthroughs. So, we are working with, let me say, initiatives in the - association we are collaborating in two different projects in order to apply AI in computer certification in order to create more robust process for the MRA vaccine. We are collaborating with the - university creating the standards for AI application in GXP. We collaborating with different initiatives with the pharma community in order to create the foundation to move forward during this year. >> And how do you see the competitive landscape? What do you think Aizon provides compared to its competitors? >> Well, good question. Probably, you can find a lot of AI services, platforms, programs softwares that can run in the industrial environment. But I think that it will be very difficult to find a GXP - a full GXP-compliant platform working on cloud with AI when AI is already qualified. I think that no one is doing that nowadays. And one of the demonstration for that is that we are also writing some scientific papers describing how to do that. So you will see that Aizon is the only company that is doing that nowadays. >> Yeah. And how do you anticipate that pharma manufacturing will change or excuse me how do you see that it is providing a defining contribution to the future of cloud-scale? >> Well, there is no limits in cloud. So as far as you accept that everything is varied and complex, you will need power computing. So the only way to manage this complexity is running a lot of power computation. So cloud is the only system, let me say, that allows that. Well, the thing is that, you know pharma will also have to be compliant with the cloud providers. And for that, we created a new layer around the platform that we say qualification as a service. We are creating this layer in order to qualify continuously any kind of cloud platform that wants to work on environment. This is how we are doing that. >> And in what areas are you looking to improve? How are you constantly trying to develop the product and bring it to the next level? >> Always we have, you know, in mind the patient. So Aizon is a patient-centric company. Everything that we do is to improve processes in order to improve at the end, to deliver the right medicine at the right time to the right patient. So this is how we are focusing all our efforts in order to bring this opportunity to everyone around the world. For this reason, for example, we want to work with this project where we are delivering value to create vaccines for COVID-19, for example, everywhere. Just packaging the knowledge using AI. This is how we envision and how we are acting. >> Yeah. Well, you mentioned the importance of science and compliance. What do you think are the key themes that are the foundation of your company? >> The first thing is that we enjoy the task that we are doing. This is the first thing. The other thing is that we are learning every day with our customers and for real topics. So we are serving to the patients. And everything that we do is enjoying science enjoying how to achieve new breakthroughs in order to improve life in the factory. We know that at the end will be delivered to the final patient. So enjoying making science and creating breakthroughs; being innovative. >> Right, and do you think that in the sense that we were lucky, in light of COVID, that we've already had these kinds of technologies moving in this direction for some time that we were somehow able to mitigate the tragedy and the disaster of this situation because of these technologies? >> Sure. So we are lucky because of this technology because we are breaking the distance, the physical distance, and we are putting together people that was so difficult to do that in all the different aspects. So, nowadays we are able to be closer to the patients to the people, to the customer, thanks to these technologies. Yes. >> So now that also we're moving out of, I mean, hopefully out of this kind of COVID reality, what's next for Aizon? Do you see more collaboration? You know, what's next for the company? >> The next for the company is to deliver AI models that are able to be encapsulated in the drug manufacturing for vaccines, for example. And that will be delivered with the full process not only materials, equipment, personnel, recipes also the AI models will go together as part of the recipe. >> Right, well, we'd love to hear more about your partnership with AWS. How did you get involved with them? And why them, and not another partner? >> Well, let me explain to you a secret. Seven years ago, we started with another top cloud provider, but we saw very soon, that this other cloud provider were not well aligned with the GXP requirements. For this reason, we met with AWS. We went together to some seminars, conferences with top pharma communities and pharma organizations. We went there to make speeches and talks. We felt that we fit very well together because AWS has a GXP white paper describing very well how to rely on AWS components. One by one. So this is for us, this is a very good credential, when we go to our customers. Do you know that when customers are acquiring and are establishing the Aizon platform in their systems, they are outbidding us. They are outbidding Aizon. Well we have to also outbid AWS because this is the normal chain in pharma supplier. Well, that means that we need this documentation. We need all this transparency between AWS and our partners. This is the main reason. >> Well, this has been a really fascinating conversation to hear how AI and cloud are revolutionizing pharma manufacturing at such a critical time for society all over the world. Really appreciate your insights, Toni Monzano: the chief science officer and co-founder of Aizon. I'm your host, Natalie Erlich, for the Cube's presentation of the AWS startup showcase. Thanks very much for watching. (soft upbeat music)

>>Please >>welcome back to HPD discovered 2021. The cubes virtual coverage, continuous coverage of H P. S H. P. S. Annual customer event. My name is Dave Volonte and we're going to dive into the intersection of high performance computing data and AI with DR Eng limb go who is the senior vice president and CTO for AI Hewlett Packard enterprise Doctor go great to see you again. Welcome back to the cube. >>Hello Dave, Great to talk to you again. >>You might remember last year we talked a lot about swarm intelligence and how AI is evolving. Of course you hosted the day two keynotes here at discover and you talked about thriving in the age of insights and how to craft a data centric strategy. And you addressed you know some of the biggest problems I think organizations face with data that's You got a data is plentiful but insights they're harder to come by. And you really dug into some great examples in retail banking and medicine and health care and media. But stepping back a little bit with zoom out on discovered 21, what do you make of the events so far? And some of your big takeaways? >>Mm Well you started with the insightful question, Right? Yeah, data is everywhere then. But we like the insight. Right? That's also part of the reason why that's the main reason why you know Antonio on day one focused and talked about that. The fact that we are now in the age of insight, right? Uh and uh and and how to thrive thrive in that in this new age. What I then did on the day to kino following Antonio is to talk about the challenges that we need to overcome in order in order to thrive in this new asia. >>So maybe we could talk a little bit about some of the things that you took away in terms I'm specifically interested in some of the barriers to achieving insights when customers are drowning in data. What do you hear from customers? What we take away from some of the ones you talked about today? >>Oh, very pertinent question. Dave You know the two challenges I spoke about right now that we need to overcome in order to thrive in this new age. The first one is is the current challenge and that current challenge is uh you know stated is no barriers to insight. You know when we are awash with data. So that's a statement. Right? How to overcome those barriers. What are the barriers of these two insight when we are awash in data? Um I in the data keynote I spoke about three main things. Three main areas that received from customers. The first one, the first barrier is in many with many of our customers. A data is siloed. All right. You know, like in a big corporation you've got data siloed by sales, finance, engineering, manufacturing, and so on, uh supply chain and so on. And uh there's a major effort ongoing in many corporations to build a federation layer above all those silos so that when you build applications above they can be more intelligent. They can have access to all the different silos of data to get better intelligence and more intelligent applications built. So that was the that was the first barrier. We spoke about barriers to incite when we are washed with data. The second barrier is uh that we see amongst our customers is that uh data is raw and dispersed when they are stored and and uh and you know, it's tough to get tough to to get value out of them. Right? And I in that case I I used the example of uh you know the May 6 2010 event where the stock market dropped a trillion dollars in in tens of minutes. You know, we we all know those who are financially attuned with know about this uh incident, But this is not the only incident. There are many of them out there and for for that particular May six event, uh you know, it took a long time to get insight months. Yeah, before we for months we had no insight as to what happened, why it happened, right. Um, and and there were many other incidences like this and the regulators were looking for that one rule that could, that could mitigate many of these incidences. Um, one of our customers decided to take the hard road to go with the tough data right? Because data is rolling dispersed. So they went into all the different feeds of financial transaction information, took the took the tough took the tough road and analyze that data took a long time to assemble. And they discovered that there was quote stuffing right? That uh people were sending a lot of traits in and then cancelling them almost immediately. You have to manipulate the market. Um And why why why didn't we see it immediately? Well, the reason is the process reports that everybody sees the rule in there that says all trades, less than 100 shares don't need to report in there. And so what people did was sending a lot of less than 103 100 100 shares trades uh to fly under the radar to do this manipulation. So here is here the second barrier right? Data could be raw and dispersed. Um Sometimes you just have to take the hard road and um and to get insight And this is 1 1 great example. And then the last barrier is uh is has to do with sometimes when you start a project to to get insight to get uh to get answers and insight. You you realize that all the datas around you but you don't you don't seem to find the right ones to get what you need. You don't you don't seem to get the right ones. Yeah. Um here we have three quick examples of customers. 111 was it was a great example right? Where uh they were trying to build a language translator, a machine language translator between two languages. Right? By not do that. They need to get hundreds of millions of word pairs, you know, of one language compared uh with a corresponding other hundreds of millions of them. They say, well I'm going to get all these word pairs. Someone creative thought of a willing source. And you thought it was the United Nations, you see. So sometimes you think you don't have the right data with you, but there might be another source. And the willing one that could give you that data Right? The 2nd 1 has to do with uh there was uh the uh sometimes you you may just have to generate that data, interesting one. We had an autonomous car customer that collects all these data from their cars, right? Massive amounts of data, loss of sensors, collect loss of data. And uh, you know, but sometimes they don't have the data they need even after collection. For example, they may have collected the data with a car uh in in um in fine weather and collected the car driving on this highway in rain and also in stone, but never had the opportunity to collect the car in hill because that's a rare occurrence. So instead of waiting for a time where the car can dr inhale, they build a simulation you by having the car collector in snow and simulated him. So, these are some of the examples where we have customers working to overcome barriers, right? You have barriers that is associated the fact that data silo the Federated it various associated with data. That's tough to get that. They just took the hard road, right? And, and sometimes, thirdly, you just have to be creative to get the right data. You need, >>wow, I I'll tell you, I have about 100 questions based on what you just said. Uh, there's a great example, the flash crash. In fact, Michael Lewis wrote about this in his book The Flash Boys and essentially right. It was high frequency traders trying to front run the market and sending in small block trades trying to get on the front end it. So that's and they, and they chalked it up to a glitch like you said, for months. Nobody really knew what it was. So technology got us into this problem. I guess my question is, can technology help us get out of the problem? And that maybe is where AI fits in. >>Yes, yes. Uh, in fact, a lot of analytics, we went in to go back to the raw data that is highly dispersed from different sources, right, assemble them to see if you can find a material trend, right? You can see lots of trends, right? Like, uh, you know, we if if humans look at things right, we tend to see patterns in clouds, right? So sometimes you need to apply statistical analysis, um math to to be sure that what the model is seeing is is real. Right? And and that required work. That's one area. The second area is uh you know, when um uh there are times when you you just need to to go through that uh that tough approach to to find the answer. Now, the issue comes to mind now is is that humans put in the rules to decide what goes into a report that everybody sees. And in this case uh before the change in the rules. Right? But by the way, after the discovery, uh authorities change the rules and all all shares, all traits of different any sizes. It has to be reported. No. Yeah. Right. But the rule was applied uh you know, to say earlier that shares under 100 trades under 100 shares need not be reported. So sometimes you just have to understand that reports were decided by humans and and under for understandable reasons. I mean they probably didn't want that for various reasons not to put everything in there so that people could still read it uh in a reasonable amount of time. But uh we need to understand that rules were being put in by humans for the reports we read. And as such there are times you just need to go back to the raw data. >>I want to ask, >>it's gonna be tough. >>Yeah. So I want to ask a question about AI is obviously it's in your title and it's something you know a lot about but and I want to make a statement, you tell me if it's on point or off point. So it seems that most of the Ai going on in the enterprise is modeling data science applied to troves of data but but there's also a lot of ai going on in consumer whether it's you know, fingerprint technology or facial recognition or natural language processing will a two part question will the consumer market as has so often in the enterprise sort of inform us uh the first part and then will there be a shift from sort of modeling if you will to more you mentioned autonomous vehicles more ai influencing in real time. Especially with the edge you can help us understand that better. >>Yeah, it's a great question. Right. Uh there are three stages to just simplify, I mean, you know, it's probably more sophisticated than that but let's simplify three stages. All right. To to building an Ai system that ultimately can predict, make a prediction right or to to assist you in decision making, have an outcome. So you start with the data massive amounts of data that you have to decide what to feed the machine with. So you feed the machine with this massive chunk of data and the machine uh starts to evolve a model based on all the data is seeing. It starts to evolve right to the point that using a test set of data that you have separately kept a site that you know the answer for. Then you test the model uh you know after you trained it with all that data to see whether it's prediction accuracy is high enough and once you are satisfied with it, you you then deploy the model to make the decision and that's the influence. Right? So a lot of times depend on what what we are focusing on. We we um in data science are we working hard on assembling the right data to feed the machine with, That's the data preparation organization work. And then after which you build your models, you have to pick the right models for the decisions and prediction you wanted to make. You pick the right models and then you start feeding the data with it. Sometimes you you pick one model and the prediction isn't that robust, it is good but then it is not consistent right now. What you do is uh you try another model so sometimes it's just keep trying different models until you get the right kind. Yeah, that gives you a good robust decision making and prediction after which It is tested well Q eight. You would then take that model and deploy it at the edge. Yeah. And then at the edges is essentially just looking at new data, applying it to the model that you have trained and then that model will give you a prediction decision. Right? So uh it is these three stages. Yeah, but more and more uh your question reminds me that more and more people are thinking as the edge become more and more powerful. Can you also do learning at the edge? Right. That's the reason why we spoke about swarm learning the last time, learning at the edge as a swamp, right? Because maybe individually they may not have enough power to do so. But as a swamp they made >>is that learning from the edge? You're learning at the edge? In other words? >>Yes. >>Yeah, I understand the question. Yeah. >>That's a great question. That's a great question. Right? So uh the quick answer is learning at the edge, right? Uh and and also from the edge, but the main goal, right? The goal is to learn at the edge so that you don't have to move the data that the edge sees first back to the cloud or the core to do the learning because that would be the reason. One of the main reasons why you want to learn at the edge, right? Uh So so that you don't need to have to send all that data back and assemble it back from all the different Edge devices, assemble it back to the cloud side to to do the learning right. With someone you can learn it and keep the data at the edge and learn at that point. >>And then maybe only selectively send the autonomous vehicle example you gave us great because maybe there, you know, there may be only persisting, they're not persisting data that is inclement weather or when a deer runs across the front. And then maybe they they do that and then they send that smaller data set back and maybe that's where it's modelling done. But the rest can be done at the edges. It's a new world that's coming down. Let me ask you a question, is there a limit to what data should be collected and how it should be collected? >>That's a great question again, you know uh wow today, full of these uh insightful questions that actually touches on the second challenge. Right? How do we uh in order to thrive in this new age of insight? The second challenge is are you know the is our future challenge, right? What do we do for our future? And and in there is uh the statement we make is we have to focus on collecting data strategically for the future of our enterprise. And within that I talk about what to collect right? When to organize it when you collect and where will your data be, you know, going forward that you are collecting from? So what, when and where for the what data for the what data to collect? That? That was the question you ask. Um it's it's a question that different industries have to ask themselves because it will vary, right? Um Let me give you the, you use the autonomous car example, let me use that. And We have this customer collecting massive amounts of data. You know, we're talking about 10 petabytes a day from the fleet of their cars. And these are not production autonomous cars, right? These are training autonomous cars, collecting data so they can train and eventually deploy commercial cars. Right? Um, so this data collection cars they collect as a fleet of them collect 10 petabytes a day and when it came to us uh building a storage system yeah, to store all of that data, they realized they don't want to afford to store all of it. Now here comes the dilemma, right? Should what should I after I spent so much effort building all these cars and sensors and collecting data, I've now decide what to delete. That's a dilemma right now in working with them on this process of trimming down what they collected. You know, I'm constantly reminded of the sixties and seventies, right? To remind myself 16 seventies we call a large part of our D. N. A junk DNA. Today we realize that a large part of that what we call john has function as valuable function. They are not jeans, but they regulate the function of jeans, you know? So, so what's jumped in the yesterday could be valuable today or what's junk today could be valuable tomorrow. Right? So, so there's this tension going on right between you decided not wanting to afford to store everything that you can get your hands on. But on the other hand, you you know, you worry you you you ignore the wrong ones, right? You can see this tension in our customers, right? And it depends on industry here. Right? In health care, they say I have no choice. I I want it. All right. One very insightful point brought up by one health care provider that really touched me was, you know, we are not we don't only care. Of course we care a lot. We care a lot about the people we are caring for, right? But you also care for the people were not caring for. How do we find them? Mhm. Right. And that therefore they did not just need to collect data that is uh that they have with from their patients. They also need to reach out right to outside data so that they can figure out who they are not caring for. Right? So they want it all. So I tell us them. So what do you do with funding if you want it all? They say they have no choice but to figure out a way to fund it and perhaps monetization of what they have now is the way to come around and find out. Of course they also come back to us rightfully that, you know, we have to then work out a way to help them build that system, you know, so that health care, right? And and if you go to other industries like banking, they say they can't afford to keep them on, but they are regulated. Seems like healthcare, they are regulated as to uh privacy and such. Like so many examples different industries having different needs but different approaches to how what they collect. But there is this constant tension between um you perhaps deciding not wanting to fund all of that uh all that you can stall right on the other hand, you know, if you if you kind of don't want to afford it and decide not to store some uh if he does some become highly valuable in the future right? Don't worry. >>We can make some assumptions about the future, can't we? I mean, we know there's gonna be a lot more data than than we've ever seen before. We know that we know. Well notwithstanding supply constraints on things like nand, we know the prices of storage is gonna continue to decline. We also know and not a lot of people are really talking about this but the processing power but he says moore's law is dead. Okay, it's waning. But the processing power when you combine the Cpus and N. P. U. S. And Gpus and accelerators and and so forth actually is is increasing. And so when you think about these use cases at the edge, you're going to have much more processing power, you're going to have cheaper storage and it's going to be less expensive processing. And so as an ai practitioner, what can you do with that? >>So the amount of data that's gonna come in, it's gonna we exceed right? Our drop in storage costs are increasing computer power. Right? So what's the answer? Right? So so the the answer must be knowing that we don't and and even the drop in price and increase in bandwidth, it will overwhelm the increased five G will overwhelm five G. Right? Given amount 55 billion of them collecting. Right? So the answer must be that there might need to be a balance between you needing to bring all that data from the 55 billion devices data back to a central as a bunch of central. Cause because you may not be able to afford to do that firstly band with even with five G. M and and SD when you'll still be too expensive given the number of devices out there, Were you given storage costs dropping? You'll still be too expensive to try and store them all. So the answer must be to start at least to mitigate the problem to some leave both a lot of the data out there. Right? And only send back the pertinent ones as you said before. But then if you did that, then how are we gonna do machine learning at the core and the cloud side? If you don't have all the data, you want rich data to train with. Right? Some sometimes you wanna mix of the uh positive type data and the negative type data so you can train the machine in a more balanced way. So the answer must be eventually right. As we move forward with these huge number of devices out of the edge to do machine learning at the edge today, we don't have enough power. Right? The edge typically is characterized by a lower uh energy capability and therefore lower compute power. But soon, you know, even with lower energy they can do more with compute power, improving in energy efficiency, Right? Uh So learning at the edge today we do influence at the edge. So we data model deploy and you do in France at the age, that's what we do today. But more and more I believe given a massive amount of data at the edge, you, you have to have to start doing machine learning at the edge and, and if when you don't have enough power then you aggregate multiple devices, compute power into a swamp and learn as a swan. >>Oh, interesting. So now of course, if, if I were sitting and fly, fly on the wall in hp board meeting, I said okay. HB is as a leading provider of compute how do you take advantage of that? I mean we're going, we're, I know its future, but you must be thinking about that and participating in those markets. I know today you are, you have, you know, edge line and other products. But there's, it seems to me that it's, it's not the general purpose that we've known in the past. It's a new type of specialized computing. How are you thinking about participating in that >>opportunity for the customers? The world will have to have a balance right? Where today the default? Well, the more common mode is to collect the data from the edge and train at uh at some centralized location or a number of centralized location um going forward. Given the proliferation of the edge devices, we'll need a balance. We need both. We need capability at the cloud side. Right? And it has to be hybrid and then we need capability on the edge side. Yeah. That they want to build systems that that on one hand, uh is uh edge adapted, right? Meaning the environmentally adapted because the edge different. They are on a lot of times. On the outside. Uh They need to be packaging adapted and also power adapted, right? Because typically many of these devices are battery power. Right? Um, so you have to build systems that adapt to it. But at the same time they must not be custom. That's my belief. They must be using standard processes and standard operating system so that they can run a rich set of applications. So yes. Um that's that's also the insightful for that Antonio announced in 2018 Uh the next four years from 2018, right $4 billion dollars invested to strengthen our edge portfolio. Edge product lines, Right. Edge solutions. >>I can doctor go, I could go on for hours with you. You're you're just such a great guest. Let's close. What are you most excited about in the future? Of of of it. Certainly H. P. E. But the industry in general. >>Yeah. I think the excitement is uh the customers, right? The diversity of customers and and the diversity in a way they have approached their different problems with data strategy. So the excitement is around data strategy, right? Just like you know uh you know, the the statement made was was so was profound, right? Um And Antonio said we are in the age of insight powered by data. That's the first line, right. Uh The line that comes after that is as such were becoming more and more data centric with data, the currency. Now the next step is even more profound. That is um You know, we are going as far as saying that you know um data should not be treated as cost anymore. No. Right. But instead as an investment in a new asset class called data with value on our balance sheet, this is a this is a step change right? In thinking that is going to change the way we look at data, the way we value it. So that's a statement that this is the exciting thing because because for for me, a city of Ai right uh machine is only as intelligent as the data you feed it with data is a source of the machine learning to be intelligent. So, so that's that's why when when people start to value data, right? And and and say that it is an investment when we collect it, it is very positive for AI because an AI system gets intelligent, get more intelligence because it has a huge amounts of data and the diversity of data. So it would be great if the community values values data. Well, >>you certainly see it in the valuations of many companies these days. Um and I think increasingly you see it on the income statement, you know, data products and people monetizing data services and maybe eventually you'll see it in the in the balance. You know, Doug Laney, when he was a gardener group wrote a book about this and a lot of people are thinking about it. That's a big change, isn't it? Dr >>yeah. Question is is the process and methods evaluation right. But I believe we'll get there, we need to get started and then we'll get there. Believe >>doctor goes on >>pleasure. And yeah. And then the Yeah, I will well benefit greatly from it. >>Oh yeah, no doubt people will better understand how to align you know, some of these technology investments, Doctor goes great to see you again. Thanks so much for coming back in the cube. It's been a real pleasure. >>Yes. A system. It's only as smart as the data you feed it with. >>Excellent. We'll leave it there, thank you for spending some time with us and keep it right there for more great interviews from HP discover 21 this is Dave Volonte for the cube. The leader in enterprise tech coverage right back

>>Welcome back to HPD discovered 2021 the cubes virtual coverage, continuous coverage of H P. S H. P. S. Annual customer event. My name is Dave Volonte and we're going to dive into the intersection of high performance computing data and AI with DR Eng limb go who is the senior vice president and CTO for AI at Hewlett Packard enterprise Doctor go great to see you again. Welcome back to the cube. >>Hello Dave, Great to talk to you again. >>You might remember last year we talked a lot about swarm intelligence and how AI is evolving. Of course you hosted the day two keynotes here at discover you talked about thriving in the age of insights and how to craft a data centric strategy and you addressed you know some of the biggest problems I think organizations face with data that's You got a data is plentiful but insights they're harder to come by. And you really dug into some great examples in retail banking and medicine and health care and media. But stepping back a little bit with zoom out on discovered 21, what do you make of the events so far? And some of your big takeaways? >>Mm Well you started with the insightful question, right? Yeah. Data is everywhere then. But we like the insight. Right? That's also part of the reason why that's the main reason why you know Antonio on day one focused and talked about that. The fact that we are now in the age of insight. Right? Uh and and uh and and how to thrive thrive in that in this new age. What I then did on the day to kino following Antonio is to talk about the challenges that we need to overcome in order in order to thrive in this new age. >>So maybe we could talk a little bit about some of the things that you took away in terms I'm specifically interested in some of the barriers to achieving insights when you know customers are drowning in data. What do you hear from customers? What we take away from some of the ones you talked about today? >>Oh, very pertinent question. Dave you know the two challenges I spoke about right now that we need to overcome in order to thrive in this new age. The first one is is the current challenge and that current challenge is uh you know stated is you know, barriers to insight, you know when we are awash with data. So that's a statement right? How to overcome those barriers. What are the barriers of these two insight when we are awash in data? Um I in the data keynote I spoke about three main things. Three main areas that received from customers. The first one, the first barrier is in many with many of our customers. A data is siloed. All right. You know, like in a big corporation you've got data siloed by sales, finance, engineering, manufacturing, and so on, uh supply chain and so on. And uh, there's a major effort ongoing in many corporations to build a federation layer above all those silos so that when you build applications above they can be more intelligent. They can have access to all the different silos of data to get better intelligence and more intelligent applications built. So that was the that was the first barrier we spoke about barriers to incite when we are washed with data. The second barrier is uh, that we see amongst our customers is that uh data is raw and dispersed when they are stored and and uh and you know, it's tough to get tough to to get value out of them. Right? And I in that case I I used the example of uh you know the May 6 2010 event where the stock market dropped a trillion dollars in in tens of ministerial. We we all know those who are financially attuned with know about this uh incident But this is not the only incident. There are many of them out there and for for that particular May six event uh you know, it took a long time to get insight months. Yeah before we for months we had no insight as to what happened, why it happened, right. Um and and there were many other incidences like this. And the regulators were looking for that one rule that could, that could mitigate many of these incidences. Um one of our customers decided to take the hard road go with the tough data right? Because data is rolling dispersed. So they went into all the different feeds of financial transaction information. Uh took the took the tough uh took the tough road and analyze that data took a long time to assemble and they discovered that there was court stuffing right? That uh people were sending a lot of traits in and then cancelling them almost immediately. You have to manipulate the market. Um And why why why didn't we see it immediately? Well the reason is the process reports that everybody sees uh rule in there that says all trades. Less than 100 shares don't need to report in there. And so what people did was sending a lot of less than 103 100 100 shares trades uh to fly under the radar to do this manipulation. So here is here the second barrier right? Data could be raw and dispersed. Um Sometimes you just have to take the hard road and um and to get insight And this is 1 1 great example. And then the last barrier is uh is has to do with sometimes when you start a project to to get insight to get uh to get answers and insight. You you realize that all the datas around you but you don't you don't seem to find the right ones To get what you need. You don't you don't seem to get the right ones. Yeah. Um here we have three quick examples of customers. 111 was it was a great example right? Where uh they were trying to build a language translator, a machine language translator between two languages. Right? But not do that. They need to get hundreds of millions of word pairs, you know, of one language compared uh with the corresponding other hundreds of millions of them. They say we are going to get all these word pairs. Someone creative thought of a willing source and a huge, so it was a United Nations you see. So sometimes you think you don't have the right data with you, but there might be another source and a willing one that could give you that data right. The second one has to do with uh there was uh the uh sometimes you you may just have to generate that data, interesting one. We had an autonomous car customer that collects all these data from their cars, right, massive amounts of data, loss of senses, collect loss of data. And uh you know, but sometimes they don't have the data they need even after collection. For example, they may have collected the data with a car uh in in um in fine weather and collected the car driving on this highway in rain and also in stone, but never had the opportunity to collect the car in hale because that's a rare occurrence. So instead of waiting for a time where the car can dr inhale, they build a simulation you by having the car collector in snow and simulated him. So these are some of the examples where we have customers working to overcome barriers, right? You have barriers that is associated the fact that data is silo Federated, it various associated with data. That's tough to get that. They just took the hard road, right? And sometimes, thirdly, you just have to be creative to get the right data you need, >>wow, I tell you, I have about 100 questions based on what you just said. Uh, there's a great example, the flash crash. In fact, Michael Lewis wrote about this in his book, The Flash Boys and essentially right. It was high frequency traders trying to front run the market and sending in small block trades trying to get on the front end it. So that's and they, and they chalked it up to a glitch like you said, for months, nobody really knew what it was. So technology got us into this problem. I guess my question is, can technology help us get out of the problem? And that maybe is where AI fits in. >>Yes, yes. Uh, in fact, a lot of analytics, we went in, uh, to go back to the raw data that is highly dispersed from different sources, right, assemble them to see if you can find a material trend, right? You can see lots of trends right? Like, uh, you know, we, if if humans look at things right, we tend to see patterns in clouds, right? So sometimes you need to apply statistical analysis, um math to be sure that what the model is seeing is is real. Right? And and that required work. That's one area. The second area is uh you know, when um uh there are times when you you just need to to go through that uh that tough approach to to find the answer. Now, the issue comes to mind now is is that humans put in the rules to decide what goes into a report that everybody sees in this case uh before the change in the rules. Right? But by the way, after the discovery, the authorities change the rules and all all shares, all traits of different any sizes. It has to be reported. No. Yeah. Right. But the rule was applied uh you know, to say earlier that shares under 100 trades under 100 shares need not be reported. So sometimes you just have to understand that reports were decided by humans and and under for understandable reasons. I mean they probably didn't want that for various reasons not to put everything in there so that people could still read it uh in a reasonable amount of time. But uh we need to understand that rules were being put in by humans for the reports we read. And as such, there are times you just need to go back to the raw data. >>I want to ask, >>albeit that it's gonna be tough. >>Yeah. So I want to ask a question about AI is obviously it's in your title and it's something you know a lot about but and I want to make a statement, you tell me if it's on point or off point. So it seems that most of the Ai going on in the enterprise is modeling data science applied to troves of data >>but >>but there's also a lot of ai going on in consumer whether it's you know, fingerprint technology or facial recognition or natural language processing. Will a two part question will the consumer market has so often in the enterprise sort of inform us uh the first part and then will there be a shift from sort of modeling if you will to more you mentioned autonomous vehicles more ai influencing in real time. Especially with the edge. She can help us understand that better. >>Yeah, it's a great question. Right. Uh there are three stages to just simplify, I mean, you know, it's probably more sophisticated than that but let's simplify three stages. All right. To to building an Ai system that ultimately can predict, make a prediction right or to to assist you in decision making, have an outcome. So you start with the data massive amounts data that you have to decide what to feed the machine with. So you feed the machine with this massive chunk of data and the machine uh starts to evolve a model based on all the data is seeing. It starts to evolve right to the point that using a test set of data that you have separately campus site that you know the answer for. Then you test the model uh you know after you trained it with all that data to see whether it's prediction accuracy is high enough and once you are satisfied with it, you you then deploy the model to make the decision and that's the influence. Right? So a lot of times depend on what what we are focusing on. We we um in data science are we working hard on assembling the right data to feed the machine with, That's the data preparation organization work. And then after which you build your models, you have to pick the right models for the decisions and prediction you wanted to make. You pick the right models and then you start feeding the data with it. Sometimes you you pick one model and the prediction isn't that robust, it is good but then it is not consistent right now what you do is uh you try another model so sometimes it's just keep trying different models until you get the right kind. Yeah, that gives you a good robust decision making and prediction after which It is tested well Q eight. You would then take that model and deploy it at the edge. Yeah. And then at the edges is essentially just looking at new data, applying it to the model, you're you're trained and then that model will give you a prediction decision. Right? So uh it is these three stages. Yeah, but more and more uh you know, your question reminds me that more and more people are thinking as the edge become more and more powerful. Can you also do learning at the edge? Right. That's the reason why we spoke about swarm learning the last time, learning at the edge as a swamp, right? Because maybe individually they may not have enough power to do so. But as a swampy me, >>is that learning from the edge or learning at the edge? In other words? Yes. Yeah. Question Yeah. >>That's a great question. That's a great question. Right? So uh the quick answer is learning at the edge, right? Uh and also from the edge, but the main goal, right? The goal is to learn at the edge so that you don't have to move the data that the Edge sees first back to the cloud or the core to do the learning because that would be the reason. One of the main reasons why you want to learn at the edge, right? Uh So so that you don't need to have to send all that data back and assemble it back from all the different edge devices, assemble it back to the cloud side to to do the learning right? With swampland. You can learn it and keep the data at the edge and learn at that point. >>And then maybe only selectively send the autonomous vehicle example you gave us. Great because maybe there, you know, there may be only persisting, they're not persisting data that is inclement weather or when a deer runs across the front and then maybe they they do that and then they send that smaller data set back and maybe that's where it's modelling done. But the rest can be done at the edges. It's a new world that's coming down. Let me ask you a question, is there a limit to what data should be collected and how it should be collected? >>That's a great question again. You know uh wow today, full of these uh insightful questions that actually touches on the second challenge. Right? How do we uh in order to thrive in this new age of inside? The second challenge is are you know the is our future challenge, right? What do we do for our future? And and in there is uh the statement we make is we have to focus on collecting data strategically for the future of our enterprise. And within that I talk about what to collect right? When to organize it when you collect and then where will your data be, you know going forward that you are collecting from? So what, when and where for the what data for the what data to collect? That? That was the question you ask. Um it's it's a question that different industries have to ask themselves because it will vary, right? Um let me give you the you use the autonomous car example, let me use that. And you have this customer collecting massive amounts of data. You know, we're talking about 10 petabytes a day from the fleet of their cars. And these are not production autonomous cars, right? These are training autonomous cars collecting data so they can train and eventually deploy commercial cars, right? Um so this data collection cars they collect as a fleet of them collect temporal bikes a day. And when it came to us building a storage system to store all of that data, they realized they don't want to afford to store all of it. Now, here comes the dilemma, right? What should I after I spent so much effort building all these cars and sensors and collecting data, I've now decide what to delete. That's a dilemma right now in working with them on this process of trimming down what they collected. You know, I'm constantly reminded of the sixties and seventies, right? To remind myself 60 and seventies, we call a large part of our D. N. A junk DNA. Today. We realize that a large part of that what we call john has function as valuable function. They are not jeans, but they regulate the function of jeans, you know, So, so what's jump in the yesterday could be valuable today or what's junk today could be valuable tomorrow, Right? So, so there's this tension going on right between you decided not wanting to afford to store everything that you can get your hands on. But on the other hand, you you know, you worry you you you ignore the wrong ones, right? You can see this tension in our customers, right? And it depends on industry here, right? In health care, they say I have no choice. I I want it. All right. One very insightful point brought up by one health care provider that really touched me was, you know, we are not we don't only care. Of course we care a lot. We care a lot about the people we are caring for, right? But you also care for the people were not caring for. How do we find them? Mhm. Right. And that therefore, they did not just need to collect data. That is that they have with from their patients. They also need to reach out right to outside data so that they can figure out who they are not caring for, right? So they want it all. So I tell us them, so what do you do with funding if you want it all? They say they have no choice but to figure out a way to fund it and perhaps monetization of what they have now is the way to come around and find that. Of course they also come back to us rightfully that you know, we have to then work out a way to help them build that system, you know? So that's health care, right? And and if you go to other industries like banking, they say they can't afford to keep them off, but they are regulated, seems like healthcare, they are regulated as to uh privacy and such. Like so many examples different industries having different needs, but different approaches to how what they collect. But there is this constant tension between um you perhaps deciding not wanting to fund all of that uh all that you can store, right? But on the other hand, you know, if you if you kind of don't want to afford it and decide not to store some uh if he does some become highly valuable in the future, right? Yeah. >>We can make some assumptions about the future, can't we? I mean, we know there's gonna be a lot more data than than we've ever seen before. We know that we know well notwithstanding supply constraints on things like nand. We know the prices of storage is going to continue to decline. We also know, and not a lot of people are really talking about this but the processing power but he says moore's law is dead okay. It's waning. But the processing power when you combine the Cpus and NP US and GPUS and accelerators and and so forth actually is is increasing. And so when you think about these use cases at the edge, you're going to have much more processing power, you're gonna have cheaper storage and it's going to be less expensive processing And so as an ai practitioner, what can you do with that? >>Yeah, it's highly again, another insightful questions that we touched on our keynote and that that goes up to the why I do the where? Right, When will your data be? Right. We have one estimate that says that by next year there will be 55 billion connected devices out there. Right. 55 billion. Right. What's the population of the world? Of the other? Of 10 billion? But this thing is 55 billion. Right? Uh and many of them, most of them can collect data. So what do you what do you do? Right. Um So the amount of data that's gonna come in, it's gonna weigh exceed right? Our drop in storage costs are increasing computer power. Right? So what's the answer? Right. So, so the the answer must be knowing that we don't and and even the drop in price and increase in bandwidth, it will overwhelm the increased five G will overwhelm five G. Right? Given amount 55 billion of them collecting. Right? So, the answer must be that there might need to be a balance between you needing to bring all that data from the 55 billion devices of data back to a central as a bunch of central Cause because you may not be able to afford to do that firstly band with even with five G. M and and SD when you'll still be too expensive given the number of devices out there. Were you given storage cause dropping will still be too expensive to try and store them all. So the answer must be to start at least to mitigate the problem to some leave both a lot of the data out there. Right? And only send back the pertinent ones as you said before. But then if you did that, then how are we gonna do machine learning at the core and the cloud side? If you don't have all the data you want rich data to train with. Right? Some sometimes you want a mix of the uh positive type data and the negative type data so you can train the machine in a more balanced way. So the answer must be eventually right. As we move forward with these huge number of devices out of the edge to do machine learning at the edge. Today, we don't have enough power. Right? The edge typically is characterized by a lower uh, energy capability and therefore lower compute power. But soon, you know, even with lower energy, they can do more with compute power improving in energy efficiency, Right? Uh, so learning at the edge today, we do influence at the edge. So we data model deploy and you do influence at the age, that's what we do today. But more and more, I believe, given a massive amount of data at the edge, you you have to have to start doing machine learning at the edge. And and if when you don't have enough power, then you aggregate multiple devices, compute power into a swamp and learn as a swan, >>interesting. So now, of course, if I were sitting and fly on the wall in HP board meeting, I said, okay, HP is as a leading provider of compute, how do you take advantage of that? I mean, we're going, I know it's future, but you must be thinking about that and participating in those markets. I know today you are you have, you know, edge line and other products. But there's it seems to me that it's it's not the general purpose that we've known in the past. It's a new type of specialized computing. How are you thinking about participating in that >>opportunity for your customers? Uh the world will have to have a balance right? Where today the default, Well, the more common mode is to collect the data from the edge and train at uh at some centralized location or a number of centralized location um going forward. Given the proliferation of the edge devices, we'll need a balance. We need both. We need capability at the cloud side. Right. And it has to be hybrid. And then we need capability on the edge side. Yeah. That they want to build systems that that on one hand, uh is uh edge adapted, right? Meaning the environmentally adapted because the edge different they are on a lot of times on the outside. Uh They need to be packaging adapted and also power adapted, right? Because typically many of these devices are battery powered. Right? Um so you have to build systems that adapt to it, but at the same time they must not be custom. That's my belief. They must be using standard processes and standard operating system so that they can run rich a set of applications. So yes. Um that's that's also the insightful for that Antonio announced in 2018, Uh the next four years from 2018, right, $4 billion dollars invested to strengthen our edge portfolio, edge product lines, right Edge solutions. >>I get a doctor go. I could go on for hours with you. You're you're just such a great guest. Let's close what are you most excited about in the future of of of it? Certainly H. P. E. But the industry in general. >>Yeah I think the excitement is uh the customers right? The diversity of customers and and the diversity in a way they have approached their different problems with data strategy. So the excitement is around data strategy right? Just like you know uh you know the the statement made was was so was profound. Right? Um And Antonio said we are in the age of insight powered by data. That's the first line right? The line that comes after that is as such were becoming more and more data centric with data the currency. Now the next step is even more profound. That is um you know we are going as far as saying that you know um data should not be treated as cost anymore. No right. But instead as an investment in a new asset class called data with value on our balance sheet, this is a this is a step change right in thinking that is going to change the way we look at data the way we value it. So that's a statement that this is the exciting thing because because for for me a city of AI right uh machine is only as intelligent as the data you feed it with. Data is a source of the machine learning to be intelligent. So so that's that's why when when people start to value data right? And and and say that it is an investment when we collect it. It is very positive for ai because an Ai system gets intelligent, more intelligence because it has a huge amounts of data and the diversity of data. So it'd be great if the community values values data. Well >>you certainly see it in the valuations of many companies these days. Um and I think increasingly you see it on the income statement, you know data products and people monetizing data services and maybe eventually you'll see it in the in the balance. You know Doug Laney when he was a gardener group wrote a book about this and a lot of people are thinking about it. That's a big change isn't it? Dr >>yeah. Question is is the process and methods evaluation. Right. But uh I believe we'll get there, we need to get started then we'll get their belief >>doctor goes on and >>pleasure. And yeah and then the yeah I will will will will benefit greatly from it. >>Oh yeah, no doubt people will better understand how to align you know, some of these technology investments, Doctor goes great to see you again. Thanks so much for coming back in the cube. It's been a real pleasure. >>Yes. A system. It's only as smart as the data you feed it with. >>Excellent. We'll leave it there. Thank you for spending some time with us and keep it right there for more great interviews from HP discover 21. This is dave a lot for the cube. The leader in enterprise tech coverage right back.

>>from >>around the >>globe, it's the >>cube with digital >>coverage of IBM, >>Think 2021 >>brought to you by IBM. Welcome back to the cubes coverage of IBM Think 2021 virtual, I'm john for your host of the cube, had a great line up here talking sustainability. Kary musa ph d general manager of AI applications and block chains, career great to see you and wayne both the vice president of corporate environmental affairs and chief sustainability officer, among other things involved in the products around that. Wait and korean, great to see you. Thanks for coming on. >>Thank you for having us. >>Well, I'll start with you. What's driving? IBMS investment sustainability as a corporate initiative. We know IBM has been active, we've covered this many times, but there's more drivers now as IBM has more of a larger global scope and continues to do that with hybrid cloud, it's much more of a global landscape. What's driving today's investments in sustainability, >>you know, johN what drives IBM in this area has always been a longstanding, mature and deep seated belief in corporate responsibility. That's the bedrock foundation. So, you know, IBM is 100 10 year old company. We've always strived to be socially responsible, But what's not as well known is that for the last 50 years, IBM has truly regarded environmental sustainability is a strategic imperative. Okay, It's strategic because hey, environmental problems require a strategic fix. It's long term imperative because you have to be persistent with environmental problems, you don't necessarily solve them overnight. And it's imperative because business cannot succeed in a world of environmental degradation, that really is the main tenant of sustainable development. You can't have successful economies with environmental degradation, you can't solving environmental problems without successful economies. So, and IBM's case as a long standing company, We were advantaged because 50 years ago our ceo at the time, Tom Watson put in place the company's first policy for environmental, our stewardship and we've been at it ever since. And he did that in 1971 and that was just six months after the U. S. C. P. A. Was created. It was a year before the Stockholm Conference on the Environment. So we've been added for that long. Um in essence really it's about recognizing that good environmental management makes good business sense. It's about corporate responsibility and today it's the E of E. S. G. >>You know, wayne. That's a great call out, by the way, referencing thomas Watson that IBM legend. Um people who don't may not know the history, he was really ahead of its time and that was a lot of the culture they still see around today. So great to see that focus and great, great call out there. But I will ask though, as you guys evolved in today's modern error. How is that evolved in today's focus? Because you know, we see data centers, carbon footprint, global warming, you now have uh A I and analytics can measure everything. So I mean you can you can measure everything now. So as the world gets larger in the surface area of what is contributing to the sustainable equation is larger, what's the current IBM focus? >>So, you know, these days we continually look at all of the ways in which IBM s day to day business practices intersect with any matter of the environment, whether it's materials waste water or energy and climate. And IBM actually has 21 voluntary goals that drive us towards leadership. But today john as you know, uh the headline is really climate change and so we're squarely focused like many others on that. And that's an imperative. But let me say before I just before I briefly tell you our current goals, it's also important to have context as to where we have been because that helps people understand what we're doing today. And so again, climate change is a topic that the men and women of IBM have paid attention to for a long time. Yeah, I was think about it. It was back in 1992 that the U. S. C. P. A. Created something called Energy Star. People look at that and they say, well, what's that all about? Okay, that's all about climate change. Because the most environmentally friendly energy you can get is the energy that you don't really need to consume. IBM was one of eight companies that helped the U. S. C. P. A. Launched that program 1992. Today we're all disclosing C. 02 emissions. IBM began doing that in 1994. Okay. In 2007, 13 years ago, I'd be unpublished. Its position on climate change, calling for urgent action around the world. We supported the Paris agreement 2015. We reiterated that support in 2017 for the us to remain a partner. 2019, we became a founding member of Climate Leadership Council, which calls for a carbon tax and a carbon dividend. So that's all background context. Today, we're working on our third renewable electricity goal, our fifth greenhouse gas emissions reduction goal and we set a new goal to achieve net zero greenhouse gas emissions. Each of those three compels IBM to near term >>action. That's awesome wayne as corporate environmental affairs and chief sustainable, great vision and awesome work. Karim dr Karim use if I wanna. We leave you in here, you're the general manager. You you've got to make this work because of the corporate citizenship that IBM is displaying. Obviously world world class, we know that's been been well reported and known, but now it's a business model. People realize that it's good business to have sustainability, whether it's carbon neutral footprints and or intersecting and contributing for the world and their employees who want mission driven companies ai and Blockchain, that's your wheelhouse. This is like you're in the big wave, wow, this is happening, give us your view because you're commercializing this in real time. >>Yeah, look as you've already said and it's the way well articulated, this is a business imperative, right? Is key to all companies corporate strategies. So the first step when you think about operationalized in this is what we've been doing, is to really step back and kind of break this down into what we call five key needs or focus areas that we've understood that we work with our clients. Remember in this context, Wayne is indeed my clients as well. Right. And so when you think about it, the five needs, as we like to lay them out, we talk about the sustainability strategy first of all, how are you approaching it as you saw from Wayne, identifying your key goals and approaches right against that, you begin to get into various areas and dimensions. Climate risk management is becoming increasingly important, especially in asset heavy industries electrification, energy and emissions management, another key focus area where we can bring technology to bear resilient infrastructure and operations, sustainable supply chain, all of these kind of come together to really connect with our clients business operations and allows us to bring together the technologies and the context of ai Blockchain and the key business operations. We can support to kind of begin to address specific news cases in the context of those needs. >>You know, I've covered it in the past and written about and also talked about the cube about sustainability on the supply chain side with Blockchain, whether it's your tracking, you know, um you know, transport of goods with with Blockchain and making sure that that kind of leads your kind of philosophy works because this waste involved is also disruption to business a security issues. But when you really move into the Ai side, how does a company scale that Corinne? Because now, you know, I have to one operationalize it and then scale it. Okay, so that's transformed, innovate and scale. How do I take take me through the examples of how that works >>well, I think really key to that, and this is really key to our ethos, it's enabling ai for business by integrating ai directly into business operations and decision making. So it's not really how can I put this? We try to make it so that the client isn't fixating on trying to deploy ai, they're just leveraging Ai. So as you say, let's take some practical examples. You talked about sustainable supply chains and you know, the key needs around transparency and provenance. Right? So we have helped clients like a tear with their seafood network or the shrimp sustainability network, where there's a big focus on understanding where are things being sourced and how they're moving through the supply chain. We also have a responsible sourcing business network that's being used for cobalt in batteries as an example from mine to manufacturing and here our technologies are allowing us to essentially track, trace and prove the provenance Blockchain serves as kind of that key shared ledger to pull all this information together. But we're leveraging AI to begin to quickly assess based upon the data inputs, the actual state of inventory, how to connect dots across multiple suppliers and as you onboard them and off board them off the network. So that's how we begin to put A. I in action so that the client begins to fixate on the work and the decisions they need to make. Not the AI itself. Another quick example would be in the context of civil infrastructure. One of our clients son and Belt large, maximum client of ours, he uses maximum to really focus on the maintenance and sustainable maintenance of their bridges. Think about how much money is spent setting up to do bridge inspections right. When you think about how much they have to invest the stopping of the traffic that scaffolding. We have been leveraging AI to do things like visual inspection, actually fly drones, take pictures, assess those images to identify cracks and use that to route and prioritized work. Similar examples are occurring in energy and utilities focused on vegetation management where we're leveraging ai to analyse satellite imagery, weather data and bringing it together so that work can be optimally prior authorized and deployed um for our clients. >>It's interesting. One of the themes coming out of think that I'm observing is this notion of transformation is innovation and innovation is about scale. Right? So it's not just innovation for innovating sake. You can transform from whether it's bridge inspections to managing any other previous pre existing kind of legacy condition and bring that into a modern error and then scale it with data. This is a common theme. It applies to to your examples. Kareem, that's super valuable. Um how do you how do you tie that together with partnering? Because wayne you were talking about the corporate initiative, that's just IBM we learned certainly in cybersecurity and now these other areas like sustainability, it's a team sport, you have to work on a global footprint with other industries and other leaders. How was I being working across the industry to connect and work with other, either initiatives or companies or governments. >>Sure. And there have been john over the years and at present a number of diverse collaborations that we seek out and we participate in. But before I address that, I just want to amplify something Kareem said, because it's so important, as I look back at the environmental movement over the last 50 years, frankly, since the first earth day in 1970, I, you know, with the benefit of hindsight, I observed there have really been three different hair, It's in the very beginning, global societies had to enact laws to control pollution that was occurring. That was the late 60s 1970s, into the early 1980s and around the early 1980s through to the first part of this century, that era of let's get control of this sort of transformed, oh, how can we prevent stuff from happening given the way we've always done business and that area ran for a while. But now, thanks to technology and data and things like Blockchain and ai we all have the opportunity to move into this era of innovation, which differs from control in which differs from traditional prevention. Innovation is about changing the way you get the same thing done. And the reason that's enabled is because of the tools that you just spoke about with korean. So how do we socialize these opportunities? Well to your question, we interact with a variety of diverse teams, government, different business associations, NGos and Academia. Some examples. There's an organization named the Center for Climate and Energy Solutions, which IBM is a founding member of its Business Leadership Council. Its predecessor was the Q Centre on global climate change. We've been involved with that since 1998. That is a cross section of people from all these different constituencies who are looking for solutions to climate. Many Fortune 102000s in there were part of the green grid. The green grid is an organization of companies involved with data centers and it's constantly looking at how do you measure energy efficiency and data centers and what are best practices to reduce consumption of energy at data centers where a member of the renewable energy buyers alliance? Many Fortune 100 200 Zar in that trying to apply scale to procure more renewable electricity to actually come to our facilities I mentioned earlier were part of the Climate Leadership Council calling for a carbon tax were part of the United Nations Environment programs science policy business form that gets us involved with many ministers of environment from countries around the world. We recently joined the new MITt Climate and sustainability consortium. Mitt Premier Research University. Many key leaders are part of that. Looking at how academic research can supercharge this opportunity for innovation and then the last one, I'm just wrap up call for code. You may be familiar with IBM s involvement in call for code. Okay. The current challenge under Call for Code in 2021 calls for solutions targeted the climate change. So that's that's a diverse set of different constituents, different types of people. But we try to get involved with all of them because we learn and hopefully we contribute something along the way as well. >>Awesome Wayne. Thank you very much, Karim, the last 30 seconds we got here. How do companies partner with IBM if they want to connect in with the mission and the citizenship that you guys are doing? How do they bring that to their company real quick. Give us a quick overview. >>Well, you know, it's really quite simple. Many of these clients are already clients of ours were engaging with them in the marketplace today, right, trying to make sure we understand their needs, trying to ensure that we tune what we've got to offer both in terms of product and consulting services with our GPS brethren, you know, to meet their needs, linking that in as well to IBM being in what we like to turn clients zero. We're also applying these same technologies and capabilities to support IBM efforts. And so as they engage in all these associations, what IBM is doing, that also provides a way to really get started. It's really fixate on those five imperatives or needs are laid out, picked kind of a starting point and tie it to something that matters. That changes how you're doing something today. That's really the key. As far as uh we're concerned, >>Karim, we thank you for your time on sustainability. Great initiative. Congratulations on the continued mission. Going back to the early days of IBM and the Watson generation continuing out in the modern era. Congratulations and thanks for sharing. >>Thank you john. >>Okay. It's the cubes coverage. I'm sean for your host. Thanks for watching. Mhm. Mhm. Mhm.

>>From around the globe, it's the Cube with digital coverage of IBM think 2021 brought to you by IBM. Welcome back to the cubes coverage of IBM Think 2021 virtual, I'm john for your host of the cube. We had a great line up here talking sustainability, kary musa ph d general manager of AI applications and block chains going great to see you and wayne, both the vice president of corporate environmental affairs and chief sustainability officer, among other things involved in the products around that. Wait and korean, great to see you. Thanks for coming on. >>Thank you for having us. >>Well, I'll start with you what's driving? IBMS investment in sustainability as a corporate initiative. We know IBM has been active, we've covered this many times, but there's more drivers now as IBM has more of a larger global scope and continues to do that with hybrid cloud, it's much more of a global landscape. What's driving today's investments in sustainability, >>You know, jOHn what drives IBM in this area has always been a longstanding, mature and deep seated belief in corporate responsibility. That's the bedrock foundation. So, you know, IBM 110 year old company, we've always strived to be socially responsible, But what's not as well known is that for the last 50 years, IBM has truly regarded environmental sustainability is a strategic imperative. Okay, It's strategic because hey, environmental problems require a strategic fix. It's a long term imperative because you have to be persistent with environmental problems, you don't necessarily solve them overnight. And it's imperative because business cannot succeed in a world of environmental degradation that really is the main tenant of sustainable development. You can't have successful economies with environmental degradation, you can't solving environmental problems without successful economies. So, and IBM's case as a long standing company, We were advantaged because 50 years ago our ceo at the time, Tom Watson put in place the company's first policy for environmental a stewardship and we've been at it ever since. And he did that in 1971 and that was just six months after the U. S. E. P. A. Was created. It was a year before the Stockholm Conference on the Environment. So we've been added for that long. Um in essence, really it's about recognizing that good environmental management makes good business sense, It's about corporate responsibility and today it's the E of E. S. G. >>You know, wayne. That's a great call out, by the way, referencing thomas Watson, the IBM legend. Um people who don't may not know the history, he was really ahead of its time and that was a lot of the culture they still see around today. So great to see that focus and great, great call out there. But I will ask though, as you guys evolved in today's modern error, how has that evolved in today's focus? Because, you know, we see data centers, carbon footprint, global warming, you now have a I and analytics can measure everything. So I mean you can you can measure everything now. So as the world gets larger in the surface area of what is contributing to the sustainable equation is larger, what's the current IBM focus? >>So these days we continually look at all of the ways in which IBM s day to day business practices intersect with any matter of the environment, whether it's materials, waste water or energy and climate. And IBM actually has 21 voluntary goals that drive us towards leadership. But today john as you know, uh the headline is really climate change and so we're squarely focused like many others on that and that's an imperative. But let me say before I just before I briefly tell you our current goals, it's also important to have context as to where we have been because that helps people understand what we're doing today. And so again, climate change is a topic that the men and women of IBM have paid attention to for a long time. Yeah, I was think about it. It was back in 1992 that the U. S. C. P. A. Created something called Energy Star. People look at that and they said, well, what's that all about? Okay, that's all about climate change. Because the most environmentally friendly energy you can get is the energy that you don't really need to consume. IBM was one of eight companies that helped the U. S. C. P. A. Launched that program 1992. Today we're all disclosing C. 02 emissions. IBM began doing that in 1994. Okay. In 2007, 13 years ago, I'd be unpublished. Its position on climate change, calling for urgent action around the world. He supported the Paris Agreement 2015. We reiterated that support in 2017 for the us to remain a partner. 2019, we became a founding member of Climate Leadership Council which calls for a carbon tax and a carbon dividend. So that's all background context. Today, we're working on our third renewable electricity goal, our fifth greenhouse gas emissions reduction goal and we set a new goal to achieve net zero greenhouse gas emissions. Each of those three compels IBM to near term action. >>That's awesome wayne as corporate environmental affairs and chief sustainable, great vision and awesome work. Karim dr Karim use if I wanna we leave you in here, you're the general manager. You you got to make this work because of the corporate citizenship that IBM is displaying. Obviously world world class, we know that's been been well reported and known, but now it's a business model. People realize that it's good business to have sustainability, whether it's carbon neutral footprints and or intersecting and contributing for the world and their employees who want mission driven companies ai and Blockchain, that's your wheelhouse. This is like you're on the big wave, wow, this is happening, give us your view because you're commercializing this in real time. >>Yeah, look as you've already said and it's the way well articulated, this is a business imperative, right is key to all companies corporate strategies. So the first step when you think about operationalized in this is what we've been doing, is to really step back and kind of break this down into what we call five key needs or focus areas that we've understood that we work with our clients. Remember in this context, Wayne is indeed my clients as well. Right. And so when you think about it, the five needs, as we like to lay them out, we talk about the sustainability strategy first of all, how are you approaching it as you saw from Wayne, identifying your key goals and approaches right against that, you begin to get into various areas and dimensions. Climate risk management is becoming increasingly important, especially in asset heavy industries electrification, energy and emissions management, another key focus area where we can bring technology to bear resilient infrastructure and operations, sustainable supply chain, All of these kind of come together to really connect with our clients business operations and allows us to bring together the technologies and context of ai Blockchain and the key business operations. We can support to kind of begin to address specific news cases in the context of those >>needs. You know, I've covered it in the past and written about and also talked about on the cube about sustainability on the supply chain side with Blockchain, whether it's your tracking, you know, um you know, transport of goods with with Blockchain and making sure that that kind of leads your kind of philosophy works because there's waste involved is also disruption to business, a security issues, but when you really move into the Ai side, how does a company scale that Corinne, because now, you know, I have to one operationalize it and then scale it. Okay, so that's transformed, innovate and scale. How do I take take me through the examples of how that works >>well, I think really key to that, and this is really key to our ethos, it's enabling ai for business by integrating ai directly into business operations and decision making. So it's not really how can I put this? We try to make it so that the client isn't fixating on trying to deploy ai, they're just leveraging Ai. So as you say, let's take some practical examples. You talked about sustainable supply chains and you know, the key needs around transparency and provenance. Right. So we have helped clients like a tear with their seafood network or the shrimp sustainability network where there's a big focus on understanding where are things being sourced and how they're moving through the supply chain. We also have a responsible sourcing business network that's being used for cobalt in batteries as an example from mine to manufacturing and here our technologies are allowing us to essentially track, trace and prove the provenance Blockchain serves as kind of that key shared ledger to pull all this information together. But we're leveraging AI to begin to quickly assess based upon the data inputs, the actual state of inventory, how to connect dots across multiple suppliers and as you on board in an off board them off the network. So that's how we begin to put A I in action so that the client begins to fixate on the work and the decisions they need to make. Not the AI itself. Another quick example would be in the context of civil infrastructure. One of our clients son and Belt large, maximum client of ours he uses maximum too rarely focus on the maintaining sustainable maintenance of their bridges. Think about how much money is spent setting up to do bridge inspections right. When you think about how much they have to invest the stopping of the traffic that scaffolding. We have been leveraging AI to do things like visual inspection. Actually fly drones, take pictures, assess those images to identify cracks and use that to route and prioritized work. Similar examples are occurring in energy and utilities focused on vegetation management where we're leveraging AI to analyse satellite imagery, weather data and bringing it together so that work can be optimally prior authorized and deployed for our >>clients. It's interesting. One of the themes coming out of think that I'm observing is this notion of transformation is innovation and innovation is about scale. Right? So it's not just innovation for innovating sake. You can transform from whether it's bridge inspections to managing any other previous pre existing kind of legacy condition and bring that into a modern error and then scale it with data. This is a common theme. It applies to to your examples. Kareem, that's super valuable. Um how do you how do you tie that together with partnering? Because wayne you were talking about the corporate initiative, that's just IBM we learned certainly in cybersecurity and now these other areas like sustainability, it's a team sport, you have to work on a global footprint with other industries and other leaders. How was I being working across the industry to connect and work with other, either initiatives or companies or governments. >>Sure. And there have been john over the years and at present a number of diverse collaborations that we seek out and we participate in. But before I address that, I just want to amplify something Kareem said, because it's so important, as I look back at the environmental movement over the last 50 years, frankly, since the first earth day in 1970, I, you know, with the benefit of hindsight, I observed there have really been three different hair, it's in the very beginning, global societies had to enact laws to control pollution that was occurring. That was the late 60s 1970s, into the early 1980s and around the early 1980s through to the first part of this century, that era of let's get control of this sort of transformed, oh how can we prevent stuff from happening given the way we've always done business and that area ran for a while. But now thanks to technology and data and things like Blockchain and ai we all have the opportunity to move into this era of innovation which differs from control in which differs from traditional prevention. Innovation is about changing the way you get the same thing done. And the reason that's enabled is because of the tools that you just spoke about with Korean. So how do we socialize these opportunities? Well to your question, we interact with a variety of diverse teams, government, different business associations, Ngos and Academia. Some examples, there's an organization named the Center for Climate and Energy Solutions, which IBM is a founding member of its Business Leadership Council. Its predecessor was the Q Centre on global climate change. We've been involved with that since 1998. That is a cross section of people from all these different constituencies who are looking for solutions to climate. Many Fortune 102000s in there were part of the green grid. The green grid is an organization of companies involved with data centers and it's constantly looking at how do you measure energy efficiency and data centers and what are best practices to reduce consumption of energy at data centers where a member of the renewable energy buyers alliance? Many Fortune 100 200 Zarin that trying to apply scale to procure more renewable electricity to actually come to our facilities I mentioned earlier were part of the Climate Leadership Council calling for a carbon tax were part of the United Nations Environment Programs science Policy business form that gets us involved with many ministers of Environment from countries around the world. We recently joined the new MITt Climate and sustainability consortium. Mitt Premier Research University. Many key leaders are part of that. Looking at how academic research can supercharge this opportunity for innovation and then the last one, I'll just wrap up call for code. You may be familiar with IBM s involvement in call for code. Okay. The current challenge under call for code in 2021 calls for solutions targeted the climate change. So that's, that's a diverse set of different constituents, different types of people. But we try to get involved with all of them because we learn and hopefully we contribute something along the way as well. >>Awesome Wayne. Thank you very much Karim, the last 30 seconds we got here. How do companies partner with IBM if they want to connect in with the mission and the citizenship that you guys are doing? How do they bring that to their company real quick. Give us a quick overview. >>Well, you know, it's really quite simple. Many of these clients are already clients of ours were engaging with them in the marketplace today, right, trying to make sure we understand their needs, trying to ensure that we tune what we've got to offer, both in terms of product and consulting services with our GPS brethren, you know, to meet their needs, linking that in as well to IBM being and what we like to turn client zero. We're also applying these same technologies and capabilities to support IBM efforts. And so as they engage in all these associations, what IBM is doing that also provides a way to really get started. It's really fixate on those five imperatives or needs are laid out, picked kind of a starting point and tie it to something that matters. That changes how you're doing something today. That's really the key. As far as uh we're concerned, >>Karim, we thank you for your time on sustainability. Great initiative, Congratulations on the continued mission. Going back to the early days of IBM and the Watson generation continuing out in the modern era. Congratulations and thanks for sharing. >>Thank you john. >>Okay. It's the cubes coverage. I'm sean for your host. Thanks for watching. >>Mm. Mhm.

>>From around the globe, it's the cube with digital coverage of AWS reinvent 2020 sponsored by Intel and AWS. >>Oh, welcome back to the cube. As we continue our coverage of AWS reinvent 2020, you know, I know you're familiar with Moneyball, the movie, Brad Pitt, starting as Billy Bean, the Oakland A's general manager, where the A's were all over data, right. With the Billy Bean approach, it was a very, uh, data driven approach to building his team and a very successful team. Well, AWS is taking that to an extraordinary level and with us to talk about that as Matt Hearst, who was the head of global sports marketing and communications at AWS and Matt, thanks for joining us here on the queue. >>John is my pleasure. Thanks so much for having me. You >>Bet. Um, now we've already heard from a couple of folks, NFL folks, uh, at re-invent, uh, about the virtual draft. Um, but for those of our viewers who maybe aren't up to speed on that, or having a chance to see, uh, what those folks had to say, uh, let's just talk about that as an opener, um, about your involvement with the NFL and particularly with, with the draft and, and what that announcement was all about. >>Sure. We, we saw, we've seen a great evolution with our work with the NFL over the past few years. And you mentioned during the infrastructure keynote where Michelle McKenna who's, the CIO for the NFL talks about how they were able to stage the 2020 virtual draft, which was the NFL is much most watched ever, uh, you know, over 55 million viewers over three days and how they were unable to do it without the help and the power of AWS, you know, utilizing AWS is reliability, scalability, security, and network connectivity, where they were able to manage thousands of live feeds to flow to the internet and go to ESPN, to airline. Um, but additionally, Jennifer LinkedIn, who's the SVP of player health and innovation at the NFL spoke during the machine learning keynote during reinvent. And she talked about how we're working with the NFL, uh, to co-develop the digital athlete, which is a computer simulation model of a football player that can replicate infinite scenarios in a game environment to help better foster and understanding of how to treat and rehabilitate injuries in the short term and in the long-term in the future, ultimately prevent, prevent and predict injuries. >>And they're using machine learning to be able to do that. So there's, those are just a couple of examples of, uh, what the NFL talked about during re-invent at a couple of keynotes, but we've seen this work with the NFL really evolve over the past few years, you know, starting with next gen stats. Those are the advanced statistics that, uh, brings a new level of entertainment to football fans. And what we really like to do, uh, with the NFL is to excite, educate, and innovate. And those stats really bring fans closer to the game to allow the broadcasters to go a little bit deeper, to educate the fans better. And we've seen some of those come to life through some of our ads, uh, featuring Deshaun Watson, Christian McCaffrey, um, these visually compelling statistics that, that come to life on screen. Um, and it's not just the NFL. AWS is doing this with some of the top sports leagues around the world, you know, powering F1 insights, Buddhist league, and match facts, six nations, rugby match stats, all of which utilize AWS technology to uncover advanced stats and really help educate and engage fans around the world in the sports that they love. >>Let's talk about that engagement with your different partners then, because you just touched on it. This is a wide array of avenues that you're exploring. You're in football, you're in soccer, you're in sailing, uh, you're uh, racing formula one and NASCAR, for example, all very different animals, right? In terms of their statistics and their data and of their fan interest, what fans ultimately want. So, um, maybe on a holistic basis first, how are you, uh, kind of filtering through your partner's needs and their fans needs and your capabilities and providing that kind of merger of capabilities with desires >>Sports, uh, for AWS and for Amazon are no different than any other industry. And we work backwards from the customer and what their needs are. You know, when we look at the sports partners and customers that we work with and why they're looking to AWS to help innovate and transform their sports, it's really the innovative technologies like machine learning, artificial intelligence, high performance computing, internet of things, for example, that are really transforming the sports world and some of the best teams and leagues that we've talked about, that you touched on, you know, formula one, NASCAR, NFL, Buena, Sligo, six nations, rugby, and so on and so forth are using AWS to really improve the athlete and the team performance transform how fans view and engage with sports and deliver these real-time advanced statistics to give fans, uh, more of that excitement that we're talking about. >>Let me give you a couple of examples on some of these innovative technologies that our customers are using. So the Seattle Seahawks, I built a data Lake on AWS to use it for talent, evaluation and acquisition to improve player health and recovery times, and also for their game planning. And another example is, you know, formula and we talk about the F1 insights, those advanced statistics, but they're also using AWS high-performance computing that helped develop the next generation race car, which will be introduced in the 2022 season. And by using AWS F1 was able to reduce the average time to run simulations by 70% to improve the car's aerodynamics, reducing the downforce loss and create more wheel to wheel racing, to bring about more excitement on the track. And a third example, similar to, uh, F1 using HPC is any of those team UK. So they compete in the America's cup, which is the oldest trophy in international sports. And endosteum UK is using an HPC environment running on Amazon, easy to spot instances to design its boat for the upcoming competition. And they're depending on this computational power on AWS needing 2000 to 3000 simulations to design the dimension of just a single boat. Um, and so the power of the cloud and the power of the AWS innovative technologies are really helping, uh, these teams and leagues and sports organizations around the world transform their sport. >>Well, let's go back. Uh, you mentioned the Seahawks, um, just as, uh, an example of maybe, uh, the kind of insights that that you're providing. Uh, let's pretend I'm there, there's an outstanding running back and his name's Matt Hearst and, uh, and he's at a, you know, a college let's just pretend in California someplace. Um, what kind of inputs, uh, are you now helping them? Uh, and what kind of insights are you trying to, are you helping them glean from those inputs that maybe they didn't have before? And how are they actually applying that then in terms of their player acquisition and thinking about draft, right player development, deciding whether Matt Hertz is a good fit for them, maybe John Wallace is a good fit for them. Um, but what are the kinds of, of, uh, what's that process look like? >>So the way that the Seahawks have built the data Lake, they built it on AWFs to really, as you talk about this talent, evaluation and acquisition, to understand how a player, you know, for example, a John Walls could fit into their scheme, you know, that, that taking this data and putting it in the data Lake and figuring out how it fits into their schemes is really important because you could find out that maybe you played, uh, two different positions in high school or college, and then that could transform into, into the schematics that they're running. Um, and try to find, I don't want to say a diamond in the rough, but maybe somebody that could fit better into their scheme than, uh, maybe the analysts or others could figure out. And that's all based on the power of data that they're using, not only for the talent evaluation and acquisition, but for game planning as well. >>And so the Seahawks building that data Lake is just one of those examples. Um, you know, when, when you talk about a player, health and safety, as well, just using the NFL as the example, too, with that digital athlete, working with them to co-develop that for that composite NFL player, um, where they're able to run those infinite scenarios to ultimately predict and prevent injury and using Amazon SageMaker and AWS machine learning to do so, it's super important, obviously with the Seahawks, for the future of that organization and the success that they, that they see and continue to see, and also for the future of football with the NFL, >>You know, um, Roger Goodell talks about innovation in the national football league. We hear other commissioners talking about the same thing. It's kind of a very popular buzz word right now is, is leagues look to, uh, ways to broaden their, their technological footprint in innovative ways. Again, popular to say, how exactly though, do you see AWS role in that with the national football league, for example, again, or maybe any other league in terms of inspiring innovation and getting them to perhaps look at things differently through different prisms than they might have before? >>I think, again, it's, it's working backwards from the customer and understanding their needs, right? We couldn't have predicted at the beginning of 2020, uh, that, you know, the NFL draft will be virtual. And so working closely with the NFL, how do we bring that to life? How do we make that successful, um, you know, working backwards from the NFL saying, Hey, we'd love to utilize your technology to improve Clare health and safety. How are we able to do that? Right. And using machine learning to do so. So the pace of innovation, these innovative technologies are very important, not only for us, but also for these, uh, leagues and teams that we work with, you know, using F1 is another example. Um, we talked about HPC and how they were able to, uh, run these simulations in the cloud to improve, uh, the race car and redesign the race car for the upcoming seasons. >>But, uh, F1 is also using Amazon SageMaker, um, to develop new F1 insights, to bring fans closer to the action on the track, and really understand through technology, these split-second decisions that these drivers are taking in every lap, every turn, when to pit, when not to pit things of that nature and using the power of the cloud and machine learning to really bring that to life. And one example of that, that we introduced this year with, with F1 was, um, the fastest driver insight and working F1, worked with the Amazon machine learning solutions lab to bring that to life and use a data-driven approach to determine the fastest driver, uh, over the last 40 years, relying on the years of historical data that they store in S3 and the ML algorithms that, that built between AWS and F1 data scientists to produce this result. So John, you and I could sit here and argue, you know, like, like two guys that really love F1 and say, I think Michael Schumacher is the fastest drivers. It's Lewis, Hamilton. Who's great. Well, it turned out it was a arts incentive, you know, and Schumacher was second. And, um, Hamilton's third and it's the power of this data and the technology that brings this to life. So we could still have a fun argument as fans around this, but we actually have a data-driven results through that to say, Hey, this is actually how it, how it ranked based on how everything works. >>You know, this being such a strange year, right? With COVID, uh, being rampant and, and the major influence that it has been in every walk of global life, but certainly in the American sports. Um, how has that factored into, in terms of the kinds of services that you're looking to provide or to help your partners provide in order to increase that fan engagement? Because as you've pointed out, ultimately at the end of the day, it's, it's about the consumer, right? The fan, and giving them info, they need at the time they want it, that they find useful. Um, but has this year been, um, put a different point on that for you? Just because so many eyeballs have been on the screen and not necessarily in person >>Yeah. T 20, 20 as, you know, a year, unlike any other, um, you know, in our lifetimes and hopefully going forward, you know, it's, it's not like that. Um, but we're able to understand that we can still bring fans closer to the sports that they love and working with, uh, these leagues, you know, we talk about NFL draft, but with formula one, we, uh, in the month of may developed the F1 Pro-Am deep racer event that featured F1 driver, uh, Daniel Ricardo, and test driver TA Sianna Calderon in this deep racer league and deep racers, a one 18th scale, fully autonomous car, um, that uses reinforcement learning, learning a type of machine learning. And so we had actual F1 driver and test driver racing against developers from all over the world. And technology is really playing a role in that evolution of F1. Um, but also giving fans a chance to go head to head against the Daniel Ricardo, which I don't know that anyone else could ever say that. >>Yeah, I raced against an F1 driver for head to head, you know, and doing that in the month of may really brought forth, not only an appreciation, I think for the drivers that were involved on the machine learning and the technology involved, but also for the developers on these split second decisions, these drivers have to make through an event like that. You know, it was, it was great and well received. And the drivers had a lot of fun there. Um, you know, and that is the national basketball association. The NBA played in the bubble, uh, down in Orlando, Florida, and we work with second spectrum. They run on AWS. And second spectrum is the official optical provider of the NBA and they provide Clippers court vision. So, uh, it's a mobile live streaming experience for LA Clippers fans that uses artificial intelligence and machine learning to visualize data through on-screen graphic overlays. >>And second spectrum was able to rely on, uh, AWS is reliability, connectivity, scalability, and move all of their equipment to the bubble in Orlando and still produce a great experience for the fans, um, by reducing any latency tied to video and data processing, um, they needed that low latency to encode and compress the media to transfer an edit with the overlays in seconds without losing quality. And they were able to rely on AWS to do that. So a couple of examples that even though 2020 was, uh, was a little different than we all expected it to be, um, of how we worked closely with our sports partners to still deliver, uh, an exceptional fan experience. >>So, um, I mean, first off you have probably the coolest job at AWS. I think it's so, uh, congratulations. I mean, it's just, it's fascinating. What's on your want to do less than in terms of 20, 21 and beyond and about what you don't do now, or, or what you would like to do better down the road, any one area in particular that you're looking at, >>You know, our, our strategy in sports is no different than any other industry. We want to work backwards from our customers to help solve business problems through innovation. Um, and I know we've talked about the NFL a few times, but taking them for, for another example, with the NFL draft, improving player health and safety, working closely with them, we're able to help the NFL advance the game both on and off the field. And that's how we look at doing that with all of our sports partners and really helping them transform their sport, uh, through our innovative technologies. And we're doing this in a variety of ways, uh, with a bunch of engaging content that people can really enjoy with the sports that they love, whether it's, you know, quick explainer videos, um, that are short two minute or less videos explaining what these insights are, these advanced stats. >>So when you see them on the screening and say, Oh yeah, I understand what that is at a, at a conceptual level or having blog posts from a will, Carlin who, uh, has a long storied history in six nations and in rugby or Rob Smedley, along story history and F1 writing blog posts to give fans deeper perspective as subject matter experts, or even for those that want to go deeper under the hood. We've worked with our teams to take a deeper look@howsomeofthesecometolifedetailingthetechnologyjourneyoftheseadvancedstatsthroughsomedeepdiveblogsandallofthiscanbefoundataws.com slash sports. So a lot of great rich content for, uh, for people to dig into >>Great stuff, indeed. Um, congratulations to you and your team, because you really are enriching the fan experience, which I am. One of, you know, hundreds of millions are enjoying that. So thanks for that great work. And we wish you all the continued success down the road here in 2021 and beyond. Thanks, Matt. Thanks so much, Sean.

(upbeat music) >> Narrator: From around the globe. It's The CUBE, with digital coverage of AWS public sector online, (upbeat music) brought to you by, Amazon Web Services. >> Everyone welcome back to The CUBE virtual coverage, of AWS public sector summit online. I'm John Furrier, your host of The CUBE. Normally we're in person, out on Asia-Pacific, and all the different events related to public sector. But this year we have to do it remote, and we're going to do the remote virtual CUBE, with Data Virtual Public Sector Online Summit. And we have two great guests here, about Digital Earth Africa project, Clive Charlton. Head of Solutions Architecture, Sub-Saharan Africa with AWS, Clive thanks for coming on, and Aditya Agrawal founder of D4DInsights, and also the advisor for the Digital Earth Africa project with AWS. So gentlemen, thank you for coming on. Appreciate you coming on remotely. >> Thanks for having us. >> Thank you for having us, John. >> So Clive take us through real quickly. Just take a minute to describe what is the Digital Earth Africa Project. What are the problems, that you're aiming to solve? >> Well, we're really aiming to provide, actionable data to governments, and organization around Africa, by providing satellite imagery, in an easy to use format, and doing that on the cloud, that serves countries throughout Africa. >> And just from a cloud perspective, give us a quick taste of what's going on, just with the tech, it's on Amazon. You got a little satellite action. Is there ground station involved? Give us a little bit more color around, you know, what's the scope of the project. >> Yeah, so, historically speaking you'd have to process satellite imagery down link it, and then do some heavy heavy lifting, around the processing of the data. Digital Earth Africa was built, from the experiences from Digital Earth Australia, originally developed by a Geo-sciences Australia and they use container services for Kubernetes's called Elastic Kubernetes Service to spin up virtual machines, which we are required to process the raw satellite imagery, into a format called a Cloud Optimized GeoTIFF. This format is used to store very large volumes of data in a format that's really easy to query. So, organizations can just use NHTTP get range request. Just a query part of the file, that they're interested in, which means, the results are served much, much quicker, from much, much better overall experience, under the hood, the store where the data is stored in the Amazon Simple Storage Service, which is S3, and the Metadata Index in a Relational Database Service, that runs the Open Data CUBE Library, which is allows Digital Earth Africa, to store this data in both space and time. >> It's interesting. I just did a, some interviews last week, on a symposium on space and cybersecurity, and we were talking about , the impact of satellites and GPS and just the overall infrastructure shift. And it's just another part of the edge of the network. Aditya, I want to get your thoughts on this, and your reaction to the Digital Earth, cause you're an advisor. Let's zoom out. What's the impact of people's lives? Give us a quick overview, of how you see it playing out because, explaining to someone, who doesn't know anything about the project, like, okay what is it about, and how does it actually impact people? >> Sure. So, you know, as, as Clive mentioned, I mean there's, there's definitely a, a digital infrastructure behind Digital Earth Africa, in a way that it's going to be able to serve free and open satellite data. And often the, the issue around satellite data, especially within the context of Africa, and other parts of the world is that there's a level of capacity that's required, in order to be able to use that data. But there's also all kinds of access issues, because, traditionally satellite data is heavy. There's the old model of being able to download the data and then being able to do something with it. And then often about 80% of the time, that you spend on satellite data is spent, just pre processing the data, before you can actually, do any of the fun analysis around it, that really sort of impacts the kinds of decisions and actions that you're looking for. And so that's why Digital Earth Africa. And that's why this partnership, with Amazon is a fantastic partnership, because it really allows us, to be able, to scale the approach across the entire continent, make it easy for that data to be accessed and make it easier for people to be able to use that data. The way that Digital Earth Africa is being operationalized, is that we're not just looking at it, from the perspective of, let's put another infrastructure into Africa. We want this program, and it is a program, that we want institutionalized within Africa itself. One that leverages expertise across the continent, and one that brings in organizations across the continent to really sort of take the leadership and ownership of this program as it moves forward. The idea of it is that, once you're able to have this information, being able to address issues like food security, climate change, coastal resilience, land degradation where illegal mining is, where is the water? We want to be able to do that, in a way that it's really looking at what are the national development priorities within the countries themselves, and how does it also then support regional and global frameworks like Africa's Agenda 2063 and the sustainable development goals. >> No doubt in my mind, obviously, is that huge benefits to these kinds of technologies. I want to also just ask you, as a follow up is a huge space race going on, right now, explosion of availability of satellite data. And again, more satellites going up, There's more congestion, more contention. Again, we had a big event on that cybersecurity, and the congestion issue, but, you know, satellite data was power everyone here in the United States, you want an Uber, you want Google Maps you've got your everywhere with GPS, without it, we'd be kind of like (laughing), wondering what's going on. How do we even vote these days? So certainly an impact, but there's a huge surge of availability, of the use of satellite data. How do you explain this? And what are some of the challenges, from the data side that's coming, from the Digital Earth Africa project that you guys hope to resolve? >> Sure. I mean, that's a great question. I mean, I think at one level, when you're looking at the space race right now, satellites are becoming cheaper. They're becoming more efficient. There's increased technology now, on the types of sensors that you can deploy. There's companies like Planet, that are really revolutionizing how even small countries are able to deploy their own satellites, and the constellation that they're putting forward, in terms of the frequency by which, you're able to get data, for any given part of the earth on a daily basis, coupled with that. And you know, this is really sort of in climbs per view, but the cloud computing capabilities, and overall computing power that you have today, then what you had 10 years, 15 years ago is so vastly different. What used to take weeks to do before, for any kind of analysis on satellite data, which is heavy data now takes, you know, minutes or hours to do. So when you put all that together, again, you know, I think it really speaks, to the power of this partnership with Amazon and really, what that means, for how this data is going to be delivered to Africa, because it really allows for the scalability, for anything that happens through Digital Earth Africa. And so, for example, one of the approaches, that we're taking us, we identify what the priorities, and needs are at the country level. Let's say that it's a land degradation, there's often common issues across countries. And so when we can take one particular issue, tested with additional countries, and then we can scale it across the whole continent because the infrastructure is there for the whole continent. >> Yeah. That's a great point. So many storylines here. We'll get to climb in a second on sustainability. And I want to talk about the Open Data Platform. Obviously, open data, having data is one thing, but now train data, and having more trusted data becomes a huge issue. Again, I want to dig into that for a second, but, Clive, I want to ask you, first, what region are we in? I mean, is this, you guys actually have a great, first of all, we've been covering the region expansion from Bahrain all the way, as moves around the world, probably soon in space. There'll be a region Amazon space station region probably, someday in the future but, what region are you running the project out of? Can you, and why is it important? Can you share the update on the regional piece? >> Well, we're very pleased, that Digital Earth Africa, is using the new Africa region in Cape Town, in South Africa, which was launched in April of this year. It's one of 24 regions around the world and we have another three new regions announced, what this means for users of Digital Earth Africa is, they're able to use region closest to them, which gives them the best user experience. It's the, it's the quickest connection for them. But more importantly, we also wanted to use, an African solution, for African people and using the Africa region in Cape Town, really aligned with that thinking. >> So, localization on the data, latency, all that stuff is kind of within the region, within country here. Right? >> That's right, Yeah >> And why is that important? Is there any other benefits? Why should someone care? Obviously, this failover option, I mean, in any other countries to go to, but why is having something, in that region important for this project? >> Well, it comes down to latency for the, for the users. So, being as close to the data, as possible is, is really important, for the user experience. Especially when you're looking at large data sets, and big queries. You don't want to be, you don't want to be waiting a long lag time, for that query to go backwards and forwards, between the user and the region. So, having the data, in the Africa region in Cape Town is important. >> So it's about the region, I love when these new regions rollout from Amazon, Cause obviously it's this huge buildup CapEx, in this huge data center servers and everything. Sustainability is a huge part of the story. How does the sustainability piece fit into the, the data initiative supported in Africa? Can you share some updates on that? >> Well, this, this project is also closely aligned with the, Amazon Sustainability Data Initiative, which looks to accelerate sustainability research. and innovation, really by minimizing the cost, and the time required to acquire, and analyze large sustainability datasets. So the initiative supports innovators, and researchers with the data and tools, and, and technical experience, that they need to move sustainability, to the next level. These are public datasets and publicly available to anyone. In addition, to that, the initiative provides cloud grants to those who are interested in exploring, exploring the use of AWS technology and scalable infrastructure, to serve sustainability challenges, of this nature. >> Aditya, I want to hear your thoughts, on this comment that Clive made around latency, and certainly having a region there has great benefits. You don't need to hop on that. Everyone knows I'm a big fan of the regional model, but it brings up the issue, of what's going on in the country, from an infrastructure standpoint, a lot of mobility, a lot of edge computing. I can almost imagine that. So, so how do you see that evolving, from a business standpoint, from a project standpoint data standpoint, can you comment and react to that edge, edge angle? >> Yeah, I mean, I think, I think that, the value of an open data infrastructure, is that, you want to use that infrastructure, to create a whole data ecosystem type of an approach. And so, from the perspective of being able. to make this data readily accessible, making it efficiently accessible, and really being able to bring industry, into that ecosystem, because of what we really want as we, as the program matures, is for this program, to then also instigate the development of new businesses, entrepreneurship, really get the young people across Africa, which has the largest proportion of young people, anywhere in the world, to be engaged around what you can do, with satellite data, and the types of businesses that can be developed around it. And, so, by having all of our data reside in Cape Town on the continent there's obviously technical benefits, to that in terms of, being able to apply the data, and create new businesses. There's also a, a perception in the fact that, the data that Digital Earth Africa is serving, is in Africa and residing in Africa which does have, which does go a long way. >> Yeah. And that's a huge value. And I can just imagine the creativity cloud, if you can comment on this open data platform idea, because some of the commentary that we've been having on The CUBE here, and all around the world is data's great. We all know we're living with a lot of data, you starting to see that, the commoditization and horizontal scalability of data, is one thing, but to put it into software defined environments, whether, it's an entrepreneur coding up an app, or doing something to share some transparency, around some initiatives going on within the region or on the continent, it's about trusted data. It's about sharing algorithms. AI is also a consumer of data, machines consume data. So, it's not just the technology data, is part of this new normal. What's this Open Data Platform, And how does that translate into value in your opinion? >> I, yeah. And you know, when, when data is shared on, on AWS anyone can analyze it and build services on top of it, using a broad range of compute and data to data analytics products, you know, things like Amazon EC2, or Lambda, which is all serverless compute, to things like Amazon Elastic MapReduce, for complex extract and transformation processes, but sharing data in the cloud, lets users, spend more time on the data analysis, rather than, than the data acquisition. And researchers can analyze data shared on AWS, without needing to pay to store their own copy, which is what the Open Data Platform provides. You only have to pay for the compute that you use and you don't need to purchase storage, to start a new project. So the registry of the open data on AWS, makes it easy to find those datasets, but, by making them publicly available through AWS services. And when you share, share your data on AWS, you make it available, to a large and growing community of developers, and startups, and enterprises, all around the world. And you know, and we've been talking particularly around, around Africa. >> Yeah. So it's an open source model, basically, it's free. You don't, it doesn't cost you anything probably, just started maybe down the road, if it gets heavy, maybe to charging but the most part easy for scientists to use and then you're leveraging it into the open, contributing back. Is that right? >> Yep. That's right. To me getting, getting researchers, and startups, and organizations growing quickly, without having to worry about the data acquisition, they can just get going and start building. >> I want to get back to Aditya, on this skill gap issue, because you brought up something that, I thought was really cool. People are going to start building apps. I'm going to start to see more innovation. What are the needs out there? Because we're seeing a huge onboarding of new talent, young talent, people rescaling from existing jobs, certainly COVID accelerated, people looking for more different kinds of work. I'm sure there's a lot of (laughing) demand to, to do some innovative things. The question I always get, and want to get your reaction is, what are the skills needed to, to get involved, to one contribute, but also benefit from it, whether it's the data satellite, data or just how to get involved skill-wise >> Sure. >> Yes. >> Yeah. So most recently we've created a six week training course. That's really kind of taken users from understanding, the basics of Earth Observation Data, to how to work, with Python, to how to create their own Jupyter notebooks, and their own Use cases. And so there's a, there's a wide sort of range of skill sets, that are required depending on who you are because, effectively, what we want to be able to do is get everyone from, kind of the technical user, that might have some remote sensing background to the developer, to the policy maker, and decision maker, to understand the value of this infrastructure, whether you're the one who's actually analyzing the data. If you're the one who's developing new applications, or you're taking that information from a managerial or policy level discussion to actually deliver the action and sort of impact that you're looking for. And so, you know, in, in that regard, we're working with ITC in the Netherlands and again, with institutions across Africa, that already have a mandate, and expertise in this particular area, to create a holistic capacity development program, that will address all of those different factors. >> So I guess the follow up question I want to have is, how do you ensure the priorities of Africa are addressed, as part of this program? >> Yeah, so, we are, we've created a governance model, that really is both top down, and bottom up. At the bottom up level, We have a technical advisory committee, that has over 15 institutions, many of which are based across Africa, that really have a good understanding of the needs, the priorities, and the mandate for how to work with countries. And at the top down level, we're developing a governing board, that will be inclusive, of the key continental level institutions, that really provide the political buy-in, the sustainability of the program, and really provide overall guidance. And within that, we're also creating an operational models, such that these institutions, that do have the capacity to support the program, they're actually the ones, who are also going to be supporting, the implementation of the program itself. >> And there's been some United Nations, sustained development projects all kinds of government involvement, around making sure certain things would happen, within the country. Can you just share, some of the highlights, or some of the key initiatives, that are going on, that you're supporting, to make it a better, better world? >> Yeah. So this is, this program is very closely aligned to a sustainable development agenda. And so looking after, looking developing methods, that really address, the sustainable development goals as one facet, in Africa, there's another program looking overall, overall national development priorities and sustainability called the Agenda 2063. And really like, I think what it really comes down to this, this wouldn't be happening, without the country level involvement themselves. So, this started with five countries, originally, Senegal, Ghana, Kenya, Tanzania, and the government of Kenya itself, has really been, a kind of a founding partner for, how Digital Earth Africa and it's predecessor of Africa Regional Data Cube, came to be. And so without high level support, and political buying within those governments, I mean, it's really because of that. That's why we're, we're where we are. >> I need you to thank you for coming on and sharing that insight. Clive will give you the final word, for the folks watching Digital Earth Africa, processes, petabytes of data. I mean the satellite data as well, huge, you mentioned it's a new region. You're running Kubernetes, Elastic Kubernetes Service, making containers easy to use, pay as you go. So you get cutting edge, take the one minute to, to share why this region's cutting edge. Does it have the scale of other regions? What should they know about AWS, in Cape Town, for Africa's new region? Take a minute to, to put plugin. >> Yeah, thank you for that, John. So all regions are built in the, in the same way, all around the world. So they're built for redundancy and reliability. They typically have a minimum of three, what we call Availability Zones. And each one is a contains a, a cluster of, of data centers, and all interconnected with fast fiber. So, you know, you can survive, you know, a failure with with no impact to your services. And the Cape Town region is built in exactly the same the same way, we have most of the services available in the, in the Cape Town region, like most other regions. So, as a user of AWS, you, you can have the confidence that, You can deploy your services and workloads, into AWS and run it in the same in the same way, with the same kind of speed, and the same kind of support, and infrastructure that's backing any region, anywhere else in the world. >> Well great. Thanks for that plug, Aditya, thank you for your insight. And again, innovation follows cloud computing, whether you're building on top of it as a startup a government or enterprise, or the big society better, in this case, the Digital Earth Africa project. Great. A great story. Thank you for sharing. I appreciate it. >> Thank you for having us. >> Thank you for having us, John >> I'm John Furrier with, The CUBE, virtual remote, not in person this year. I hope to see you next time in person. Thanks for watching. (upbeat music) (upbeat music decreases)

from around the globe it's thecube covering space and cyber security symposium 2020 hosted by cal poly hello everyone welcome to the space and cyber security symposium 2020 hosted by cal poly where the intersection of space and security are coming together i'm john furrier your host with thecube here in california i want to welcome our featured guest lieutenant general john f thompson with the united states space force approach to cyber security that's the topic of this session and of course he's the commander of the space and missile system center in los angeles air force base also heading up space force general thank you for coming on really appreciate you kicking this off welcome to the symposium hey so uh thank you very much john for that very kind introduction also uh very much thank you to cal poly uh for this opportunity to speak to this audience today also a special shout out to one of the organizers uh dustin brun for all of his work uh helping uh get us uh to this point uh ladies and gentlemen as uh as uh john mentioned uh i'm jt thompson uh i lead the 6 000 men and women of the united states space forces space and missile system center which is headquartered here at los angeles air force base in el segundo if you're not quite sure where that's at it's about a mile and a half from lax this is our main operating location but we do have a number of other operating locations around the country with about 500 people at kirtland air force base in albuquerque new mexico uh and about another 500 people on the front range of the rockies uh between colorado springs and uh and denver plus a smattering of other much smaller operating locations nationwide uh we're responsible for uh acquiring developing and sustaining the united states space force's critical space assets that includes the satellites in the space layer and also on the ground layer our ground segments to operate those satellites and we also are in charge of procuring launch services for the u.s space force and a number of our critical mission partners across the uh department of defense and the intelligence community um just as a couple of examples of some of the things we do if you're unfamiliar with our work we developed and currently sustained the 31 satellite gps constellation that satellite constellation while originally intended to help with global navigation those gps signals have provided trillions of dollars in unanticipated value to the global economy uh over the past three decades i mean gps is everywhere i think everybody realizes that agriculture banking the stock market the airline industry uh separate and distinct navigation systems it's really pervasive across both the capabilities for our department of defense and capabilities for our economy and and individuals billions of individuals across our country and the planet some of the other work we do for instance in the communications sector uh secure communications satellites that we design and build that link america's sons and daughters serving in the military around the world and really enable real-time support and comms for our deployed forces and those of our allies we also acquire uh infrared missile warning satellites uh that monitor the planet for missile launches and provide advanced warning uh to the u.s homeland and to our allies uh in case some of those missile launches are uh nefarious um on a note that's probably a lot closer to home maybe a lot closer to home than many of us want to think about here in the state of california in 2018 smc jumped through a bunch of red tape and bureaucracy uh to partner with the u.s forest service during the two of the largest wildfires in the state's history the camp and woolsey fires in northern california as those fires spread out of control we created processes on the fly to share data from our missile warning satellites those are satellites that are systems that are purpose built to see heat sources from thousands of miles above the planet and we collaborated with the us forest service so that firefighters on the ground uh could track those fires more in real time and better forecast fires and where they were spreading thereby saving lives and and property by identifying hot spots and flare-ups for firefighters that data that we were able to working with our contractors pass to the u.s forest service and authorities here in california was passed in less than an hour as it was collected to get it into the hands of the emergency responders the first responders as quickly as possible and doing that in an hour greatly surpassed what was available from some of the other assets in the airborne and ground-based fire spotters it was really instrumental in fighting those fires and stopping their spread we've continued uh that involvement in recent years using multiple systems to support firefighters across the western u.s this fall as they battled numerous wildfires that unfortunately continue working together with the u.s forest service and with other partners uh we like to make uh we like to think that we made a difference here but there's still a lot more work to go and i think that we should always be asking ourselves uh what else can space data be used for and how can we more rapidly get that space data to uh stakeholders so that they can use it for for purposes of good if you will how else can we protect our nation how else can we protect our friends and allies um i think a major component of the of the discussion that we will have throughout this conference is that the space landscape has changed rapidly and continues to change rapidly um just over the past few years uh john and i were talking before we went live here and 80 nations now have uh space programs 80 nearly 80 space faring nations on the planet um if you just look at one mission area that uh the department of defense is interested in and that's small launch there are currently over a hundred different small launch companies uh within the u.s industrial base vying for commercial dod and civil uh payload capabilities uh mostly to low earth orbit it's it's just truly a remarkable time if you factor in those things like artificial intelligence and machine learning um where we're revolutionary revolutionizing really uh the ways that we generate process and use data i mean it's really remarkable in 2016 so if you think about this four years ago uh nasa estimated that there were 28 terabytes of information transiting their space network each day and that was four years ago um uh obviously we've got a lot of desire to work with a lot of the people in the audience of this congress or in this conference uh we need to work with big thinkers like many of you to answer questions on how best we apply data analytics to extract value and meaning from that data we need new generations of thinkers to help apply cutting edge edge theories of data mining cyber behaviorism and internet of things 2.0 it's just truly a remarkable time uh to be in the space business and the cyber aspects of the states of the space business are truly truly daunting and important to uh to all of us um integrating cyber security into our space systems both commercial and government is a mandate um it's no longer just a nice to have as the us space force and department of the air force leadership has said many times over the past couple of years space is becoming congested and contested and that contested aspect means that we've got to focus on cyber security uh in the same way that the banking industry and cyber commerce focus on uh cyber security day in and day out the value of the data and services provided is really directly tied to the integrity and availability of that data and services from the space layer from the ground control segments associated with it and this value is not just military it's also economic and it's not just american it's also a value for the entire world particularly particularly our allies as we all depend upon space and space systems your neighbors and friends here in california that are employed at the space and missile system center uh work with network defenders we work with our commercial contractors and our systems developers um our international allies and partners to try and build as secure and resilient systems as we can from the ground up that keep the global commons of space free and open for exploration and for commerce um as john and i were talking earlier before we came online there's an aspect of cyber security for space systems especially for some of our legacy systems that's more how do we bolt this on because we fielded those space systems a number of years ago and the the challenges of cyber security in the space domain have grown so we have a part that we have to worry about bolting it on but then we have to worry about building it in as we as we field new systems and build in a flexibility that that realizes that the cyber threat or the cyber security landscape will evolve over time it's not just going to be stagnant there will always be new vulnerabilities and new threat vectors that we always have to look at look uh as secretary barrett who is our secretary of the air force likes to say most americans use space before they have their first cup of coffee in the morning the american way of life really depends on space and as part of the united states space force we work with defense leaders our congress joint and international military teammates and industry to ensure american leadership in space i really thank you for this opportunity to address the audience today john and thanks so much to cal poly for letting me be one of the speakers at this event i really look forward to this for uh several months and so with that i look forward to your questions as we kind of move along here general thank you very much for the awesome uh introductory statement uh for the folks watching on the stream brigadier general carthan is going to be in the chat answering any questions feel free to chat away he's the vice commander of space and missile systems center he'll be available um a couple comments from your keynote before i get to my questions because it just jumped in my head you mentioned the benefits of say space but the fires in california we're living that here that's really real time that's a benefit you also mentioned the ability for more people launching payloads into space and i only imagine moore's law smaller faster cheaper applies to rockets too so i'm imagining you have the benefits of space and you have now more potential objects flying out sanctioned and maybe unsanctioned so you know is it going to be more rules around that i mean this is an interesting question because it's exciting space force but for all the good there is potentially bad out there yeah so i i john i think the uh i think the basics of your question is as space becomes more congested and contested is there a need for more international norms of how satellites fly in space what kind of basic features satellites have to perhaps deorbit themselves what kind of basic protections does do all satellites should all satellites be afforded as part of a peaceful global commons of space i think those are all fantastic questions and i know that u.s and many uh allied policy makers are looking very very hard at those kinds of questions in terms of what are the norms of behavior and how we uh you know how how we field and field is the military term but you know how we uh populate uh using civil or uh commercial terms uh that space layer at different altitudes uh low earth orbit mid mid-earth orbit geosynchronous earth orbit different kinds of orbits uh what the kind of mission areas we accomplish from space that's all things that need to be definitely taken into account as uh as the place gets a little bit not a little bit as the place gets increasingly more popular day in and day out well i'm super excited for space force i know that a new generation of young folks are really interested in it's an emerging changing great space the focus here at this conference is space and cyber security intersection i'd like to get your thoughts on the approach that space force is taking to cyber security and how it impacts our national goals here in the united states yeah yeah so that's a that's a great question john let me let me talk about in two uh two basic ways but number one is and and i know um some people in the audience this might make them a little bit uncomfortable but i have to talk about the threat right um and then relative to that threat i really have to talk about the importance of uh of cyber and specifically cyber security as it relates to that threat um the threats that we face um really represent a new era of warfare and that new era of warfare involves both space and cyber uh we've seen a lot of action in recent months uh from certain countries notably china and russia uh that have threatened what i referred to earlier as the peaceful global commons of space for example uh it through many unclassified sources and media sources everybody should understand that um uh the russians have been testing on orbit uh anti-satellite capabilities it's been very clear if you were following just the week before last the department of defense released its uh 2020 military and security developments involving the people's republic of china um uh and uh it was very clear that china is developing asats electronic jammers directed energy weapons and most relevant to today's discussion offensive cyber uh capabilities there are kinetic threats uh that are very very easy to see but a cyber attack against a critical uh command and control site or against a particular spacecraft could be just as devastating to the system and our war fighters in the case of gps and important to note that that gps system also impacts many civilians who are dependent upon those systems from a first response perspective and emergency services a cyber attack against a ground control site could cause operators to lose control of a spacecraft or an attacker could feed spoofed data to a system to mislead operators so that they send emergency services personnel to the to the wrong address right attacks on spacecraft on orbit whether directly via a network of intrusion or enabled through malware introduced during the systems production uh while we're building the satellite can [ __ ] or corrupt the data denial of service type attacks on our global networks obviously would disrupt our data flow and interfere with ongoing operations and satellite control i mean if gps went down i you know i hesitate to say it this way because we might elicit some screams from the audience but if gps went down a starbucks wouldn't be able to handle your mobile order uber drivers wouldn't be able to find you and domino's certainly certainly wouldn't be able to get there in 30 minutes or less right so with a little bit of tongue-in-cheek there from a military operations perspective it's dead serious um uh we have become accustomed in the commercial world to threats like lance ransomware and malware and those things have unfortunately become commonplace in commercial terrestrial networks and computer systems however what we're seeing is that our adversaries with the increased competition in space these same techniques are being retooled if you will to use against our national security space systems uh day in and day out um as i said during my opening remarks on the importance of cyber the value of these systems is directly tied to their integrity if commanders in the field uh firefighters in california or baristas in in starbucks can't trust the data they see they're receiving then that really harms their decision-making capabilities one of the big trends we've recently seen is the mood move towards proliferated leo uh uh constellations obviously uh spacex's uh starlink uh on the commercial side and on the military side the work that darpa and my organization smc are doing on blackjack and casino as well as some space transport layer constellation work that the space development agency is designing are all really really important types of mesh network systems that will revolutionize how we plan and field warfighting systems and commercial communications and internet providing systems but they're also heavily reliant on cyber security uh we've got to make sure that they are secured to avoid an accident or international damage uh loss of control of these constellations really could be catastrophic from both a mission perspective or from uh you know satellites tumbling out of low earth orbit perspective another trend is introductions in artificial intelligence and machine learning on board spacecraft or at the edge our satellites are really not so much hardware systems with a little software anymore in the commercial sector and in the defense sector they're basically flying boxes full of software right and we need to ensure the data that we're getting out of those flying boxes full of software are helping us base our decisions on accurate data and algorithms govern governing the right actions and that those uh that those systems are impervious to the extent possible uh to nefarious uh modifications so in summation a cyber security is vital element of everything in our national security space goals and i would argue for our national uh goals uh writ large including uh economic and information uh uh dimensions uh the space force leadership at all levels uh from uh some of the brand new second lieutenants that general raymond uh swore into the space force this morning uh ceremonially from the uh air force association's air space and cyberspace conference uh to the various highest levels general raymond uh general d t thompson myself and a number of other senior leaders in this enterprise we've got to make sure that we're all working together to keep cyber security at the forefront of our space systems because it they absolutely depend on it you know you mentioned uh hardware software threats opportunities challenges i want to ask you because you you got me thinking of the minute there around infrastructure i mean we've heard critical infrastructure you know grids here on on earth you're talking about critical infrastructure a redefinition of what critical infrastructure is an extension of what we have so i'd love to get your thoughts about space force's view of that critical infrastructure vis-a-vis the threat vectors because you know the term threat vectors has been kicked around in the cyber space oh yeah threat vectors they're always increasing the surface area well if the surface area is from space it's an unlimited surface area so you got different vectors so you got new critical infrastructure developing real time really fast and you got an expanded threat vector landscape putting that in perspective for the folks that aren't really inside the ropes on these critical issues how would you explain this and how would you talk about those two things well so i tell you um i just like um uh just like uh i'm sure people in the security side or the cyber security side of the business in the banking industry feel they feel like it's uh all possible threat vectors represent a dramatic and protect potentially existential threat to all of the dollars that they have in the banking system to the financial sector on the department of defense side we've got to have sort of the same mindset um that threat vector from to and through space against critical space systems ground segments the launch enterprise or transportation uh to orbit and the various different uh domains within uh within space itself like i mentioned before uh leo mio and geo-based satellites with different orbits all of the different mission areas that are accomplished from space that i mentioned earlier some that i didn't mention like weather tactical or wide band communications uh various new features of space control all of those are things that we have to worry about from a cyber security uh threat perspective and it's a it's a daunting challenge right now right yeah it's awesome and one of the things we've been following on the hardware side here in the on the ground is the supply chain we've seen you know malware being you know really put into really obscure hardware who manufactures it as being outsourced obviously government has restrictions but with the private sector uh you mentioned china and and the us kind of working together across these these peaceful areas but you got to look at the supply chain how does the supply chain the security aspect impact the mission of the u.s space force yeah yeah so so um how about another um just in terms of an example another kind of california-based historical example right um the very first u.s satellite uh explorer one was built by uh the jet propulsion uh laboratory folks uh not far from here in el segundo up in uh up in pasadena um that satellite when it was first built in the late 50s uh weighed a little bit over 30 pounds and i'm sure that each and every part was custom made and definitely made by u.s companies fast forward to today the global supply chain is so tightly coupled and frankly many industries are so specialized almost specialized regionally around the planet we focus every day to guarantee the integrity of every component that we put in our space systems is absolutely critical to the operations of those satellites and we're dependent upon them but it becomes more difficult and more difficult to understand the the heritage if you will of some of the parts that are used the thousands of parts that are used in some of our satellites that are literally school bus sized right the space industry especially uh national security space sector um uh is relatively small compared to other commercial industries and we're moving to towards using more and more parts uh from non-us companies uh cyber security and cyber awareness have to be baked in from the beginning if we're going to be using parts that maybe we don't necessarily um understand 100 percent like an explorer one uh the the lineage of that particular part the environmental difficulties in space are well known the radiation environment the temperature extremes the vacuum those require specialized component and the us military is not the only uh customer in that space in fact we're definitely not the dominant customer uh in space anymore all those factors require us along with our other government partners and many different commercial space organizations to keep a very close eye on our supply chains from a quality perspective a security perspective and availability um there's open source reporting on supply training intrusions from um many different breaches of commercial retailers to the infectious spread of uh you know compromised patches if you will and our adversaries are aware of these techniques as i mentioned earlier with other forms of attack considering our supply chains and development networks really becomes fair game for our adversaries so we have to uh take that threat seriously um between the government and industry sectors here in the u.s we're also working with our industry partners to enact stronger defenses and assess our own vulnerabilities last fall we completed an extensive review of all of our major contracts here at space and missile system center to determine the levels of cyber security requirements we've implemented across our portfolio and it sounds really kind of you know businessy geeky if you will you know hey we looked at our contracts to make sure that we had the right clauses in our contracts to address cyber security as dynamically as we possibly could and so we found ourselves having to add new language to our contracts to require system developers to implement some more advanced uh protective measures in this evolving cyber security environment so that data handling and supply chain perspective uh protections um from contract inception to launch and operations were taken into account uh cyber security really is a key performance parameter for us now it's as important as the the mission performance of the system it's as important as cost it's as important as schedule because if we deliver the perfect system on time and on cost uh it can perform that missile warning or that communications mis mission perfectly but it's not cyber secure if it doesn't have cyber protections built into it or the ability to implement mitigations against cyber uh threats then we've essentially fielded a shoe box in space that doesn't do the k the the war fighter or the nation uh any good um supply chain risk management is a is a major challenge for us uh we're doing a lot to coordinate with our industry partners uh we're all facing it head on uh to try and build secure and trusted components uh that keep our confidence as leaders firefighters and baristas uh as the case may be uh but it is a challenge and we're trying to rise to that challenge you know this so exciting this new area because it really touches everything you know talk about geeking out on on the tech the hardware the systems but also you put your kind of mba hat on you go what's the roi of the extra development and how you how things get built because the always the exciting thing for space geeks is like you're building cool stuff people love it's it's exciting but you still have to build and cyber security has proven that security has to be baked in from the beginning and be thought as a system architecture so you're still building things which means you've got to acquire things you got to acquire parts you got to acquire build software and and sustain it how is security impacting the acquisition and the sustainment of these systems for space yeah from initial development uh through planning for the acquisition design development fielding or production fielding and sustainment it impacts all aspects of of the life cycle john uh we simply especially from the concept of baking in cyber security uh we can't wait until something is built and then try and figure out how to make it cyber secure so we've moved way further uh towards working side by side with our system developers to strengthen cyber security from the very beginning of a system's development cyber security and the resilience associated with it really have to be treated as a key system attribute as i mentioned earlier equivalent with data rates or other metrics of performance we like to talk in uh in the space world about uh mission assurance and mission assurance has always you know sort of taken us as we as we technically geek out right mission assurance has always taken us to the will this system work in space right can it work in a vacuum can it work in you know as it as it uh you know transfers through uh the van allen radiation belt or through the the um the southern hemisphere's electromagnetic anomaly right will it work out in space and now from a resiliency perspective yeah it has to work in space it's got to be functional in space but it's also got to be resistant to these cyber security threats it's it's not just i think uh general dt thompson quoted this term it's not just widget assurance anymore it's mission assurance um uh how does that satellite uh operator that ground control segment operate while under attack so let me break your question a little bit uh just for purposes of discussion into into really two parts uh cyber uh for cyber security for systems that are new and cyber security uh for systems that are in sustainment or kind of old and legacy um obviously there's cyber vulnerabilities that threaten both and we really have to employ different strategies for for defense of of each one for new systems uh we're desperately trying to implement across the department of defense in particular in the space world a kind of a devsecops methodology and practice to delivering software faster and with greater security for our space systems here at smc we have a program called enterprise ground services which is a tool kit basically a collection of tools for common command and control of different satellite systems egs as we call it has an integrated suite for defensive cyber capabilities network operators can use these tools to gain unprecedented insight to data flows and to monitor space network traffic for anomalies or other potential indicators of of bad behavior malicious behavior if you will um uh it's rudimentary at this point but because we're using devsecops and that incremental development approach as we scale it it just becomes more and more capable you know every every product increment that we field here at uh at uh la air force base uh uh we have the united space space forces west coast software factory which we've dubbed kobayashi maru they're using those agile devops uh software development practices uh to deliver uh space awareness software uh to the combined space operations center uh affectionately called the csp that c-spock is just down the road uh from cal poly uh there in san luis obispo at vandenberg air force base they've securely linked the c-spock with other space operation centers around the planet our allies australia canada and the uk uh we're partnering with all of them to enable secure and enhanced combined space operations so lots of new stuff going on as we bake in new development uh capabilities for our our space systems but as i mentioned earlier we've got large constellations on satellite of satellites on orbit right now some of them are well in excess of a decade or more old on orbit and so the design aspects of those satellites are several decades old and so but we still have to worry about them because they're critical to our space capabilities um we've been working with an air force materiel command organization uh called crows which stands for the cyber resiliency office for uh weapon systems to assess all of those legacy platforms from a cyber security perspective and develop defensive strategies and potential hardware and software upgrades to those systems to better enable them to to live through this increasingly cyber security uh concerned era that we currently live in our industry partners have been critical to to both of those different avenues both new systems and legacy systems we're working closely with them to defend and upgrade uh national assets and develop the capabilities to do similar with uh with new national assets coming online the vulnerabilities of our space systems really kind of threaten the way we've done business in the past both militarily and in the case of gps economically the impacts of that cyber security risk are clear in our acquisition and sustainment processes but i've got to tell you it that as the threat vectors change as the vulnerabilities change we've got to be nimble enough agile enough to be able to bounce back and forth we can't just say uh many people in the audience are probably familiar with the rmf or the risk management framework approach to um to reviewing uh the cyber security of a system we can't have program managers and engineers just accomplish an rmf on a system and then hey high five we're all good uh it's a journey not a destination that's cyber security and it's a constant battle rhythm throughout a weapon systems life cycle not just a single event i want to get to this commercial business needs and your needs on the next question but before i go there you mentioned the agile and i see that clearly because when you have accelerated innovation cycles you've got to be faster and we saw this in the computer industry mainframes mini computers and then when you started getting beyond me when the internet hit and pcs came out you saw the big enterprises the banks and and government start to work with startups it used to be a joke in the entrepreneurial circles is that you know there's no way if you're a startup you're ever going to get a contract with a big business enterprise now that used to be for public sector and certainly uh for you guys so as you see startups out there and there's acquisition involved i'm sure would love to love to have a contract with space force there's an roi calculation where if it's in space and you have a sustainment view edit software you might have a new kind of business model that could be attractive to startups could you share your thoughts on the folks who want to be a supplier to you uh whether they're a startup or an existing business that wants to be agile but they might not be that big company we are john that's a fantastic question we are desperately trying to reach out to to those new space advocates to those startups to those um what we sometimes refer to within the department of defense those non-traditional uh defense contractors a couple of things just for uh thinking purposes on some of the things that we're trying to highlight um uh three years ago we created here at uh space and missile system center uh the space enterprise consortium uh to provide a platform uh a contractual vehicle really to enable us to rapidly prototype uh development of space systems and to collaborate uh between the u.s space force uh traditional defense contractors non-traditional vendors like startups and even some academic institutions uh spec as we call it space enterprise consortium uses a specialized contracting tool to get contracts uh awarded quickly many in the audience may be familiar with other transaction agreements and that's what spec is based on and so far in just three years spec has awarded 75 different uh prototyping contracts worth over 800 million dollars with a 36 reduction in time to award and because it's a consortium based competition for um for these kinds of prototyping efforts the barrier to entry for small and non-traditional for startups even for academic institutions to be able to compete for these kinds of prototypings is really lowered right um uh these types of partnerships uh that we've been working through on spec uh have really helped us work with smaller companies who might not have the background or expertise in dealing with the government or in working with cyber security uh for their systems both their developmental systems and the systems that they're designing and trying to build we want to provide ways for companies large and small to partner together and support um uh kind of mutually beneficial uh relationships between all um recently uh at the annual air force association uh conference that i mentioned earlier i moderated a panel with several space industry leaders uh all from big traditional defense contractors by the way and they all stressed the importance of building bridges and partnerships uh between major contractors in the defense industry and new entrants uh and that helps us capture the benefits of speed and agility that come with small companies and startups as well as the expertise and specialized skill sets of some of those uh larger contractors uh that we rely on day in and day out advanced cyber security protections and utilization of secure facilities are just a couple of things that i think we could be prioritizing more so in those collaborations as i mentioned earlier the spec has been very successful in awarding a number of different prototyping contracts and large dollar values and it's just going to get better right there's over 400 members of the space enterprise consortium 80 of them are non-traditional kinds of vendors and we just love working with them another thing that many people in the audience may be familiar with in terms of our outreach to innovators uh if you will and innovators that include uh cyber security experts is our space pitch day events right so we held our first event last november in san francisco uh where we awarded over a two-day period about 46 million dollars to 30 different companies um that had potentially game-changing ideas these were phase two small business innovative research efforts uh that we awarded with cash on the spot uh we're planning on holding our second space pitch day in the spring of 2021. uh we're planning on doing it right here in los angeles uh covent 19 environment permitting um and we think that these are you know fantastic uh uh venues for identifying and working with high-speed startups startups and small businesses who are interested in uh really truly partnering with the us air force it's a as i said before it's a really exciting time to be a part of this business uh and working with the innovation economy uh is something that the department of defense uh really needs to do in that um the innovation that we used to think was ours you know that 80 percent of the industrial-based innovation that came from the department of defense uh the the script has been flipped there and so now more than 70 percent uh particularly in space innovation uh comes from the commercial sector not from uh not from the defense business itself and so um that's a tsunami of uh investment and a tsunami of uh capability and i need to figure out how to get my surfboard out and ride it you know what i mean yeah i mean it's one of those things where the flip the script has been flipped but it's exciting because it's impacting everything are you talking about systems architecture you're talking about software you're talking about a business model you talk about devsecops from a technical perspective but now you have a business model innovation all the theaters of uh are exploding in innovation technical business personnel this brings up the workforce challenge you've got the cyber needs for the u.s space force there's probably a great roi model for new kinds of software development that could be priced into contracts that's a entrepreneurial innovation you got the the business model theater you've got the personnel how does the industry adopt and change you guys are clearly driving this how does the industry adjust to you yeah so um i think a great way to answer that question is to just talk about the kind of people that we're trying to prioritize in the u.s space force from a from an acquisition perspective and in this particular case from a from a cyber security perspective as i mentioned earlier it's the most exciting time to be in space programs uh really since the days of apollo um uh you know just to put it in terms that you know maybe have an impact with the audience uh from 1957 until today approximately 9 000 satellites uh have been launched from the various space faring countries around the planet uh less than two thousand of those nine thousand are still up on orbit and operational and yet in the new space regime um players like spacex have plans to launch you know 12 000 satellites for some of their constellations alone it really is a remarkable time in terms of innovation and fielding of space capabilities and all of those space capabilities whether they're commercial civil or defense are going to require appropriate cyber security uh protections it's just a really exciting time uh to be working in stuff like this and so uh folks like the folks in this audience who have a passion about space and a passion about cyber security are just the kind of people that we want to work with because we need to make sure our systems are are secure and resilient we need folks that have technical and computing expertise engineering skills to be able to design cybersecure systems that can detect and mitigate attacks uh but we also as you alluded to we need people that have that business and um you know business acumen human networking background so that we can launch the startups and work with the non-traditional businesses uh help to bring them on board help to secure both their data and our data and uh and and make sure our processes and systems are are free as much as possible from uh uh from attack um for preparation for for audience members who are young and maybe thinking about getting into this uh trade space um you gotta be smart on digital networking uh you gotta understand basic internet protocols concepts uh programming languages uh database design uh learn what you can from penetration or vulnerability testing and and uh risk assessment i will tell you this and i don't think he will i know he will not mind me telling you this but you've got to be a lifelong learner and so two years ago i'm at home one evening and i get a phone call on my cell phone and it's my boss the commander of air force space command uh general j raymond who is now currently the chief of space operations and he is on temporary duty flying overseas he lands where he's going and he first thing he does when he lands is he calls me and he goes jt um while i was traveling um i noticed that there were e-books available on the commercial airliner i was traveling on and there was an e-book on something called scrumming and agile devsecops and i read it have you read it um and i said no sir but if you tell me what the title of the book is i will read it and so i got to go to my staff meeting um you know the very next week the next time we had a staff meeting and tell everybody in the stab meeting hey if the four star and the three star can read the book about scrumming then i'm pretty sure all of you around this table and all our lieutenants and our captains our gs13s all of our government employees can get smart on uh the scrumming development process and interestingly as another side i had a telephone call with him last year during the holidays where he was trying to take some leave and i said sir what are you up to today are you are you you know making eggnog for the event tonight or whatever and the chief of space operations told me no i'm trying to teach myself python i'm at lesson two and it's not going so well but i'm i'm gonna figure this out and so that kind of thing if the chief of staff or the you know the the the chief of space operations can prioritize scrumming and python language and innovation in his daily schedule then we're definitely looking for other people who can do that and we'll just say lower levels of rank uh throughout our entire space force enterprise um look i i we don't need to need people that can code a satellite from scratch but we need to know we need to have people that have a basic grasp of the programming basics and cyber security requirements and that can turn those things into into meaningful actions obviously in the space domain things like basic physics and orbital mechanics are also important uh space is not an intuitive uh domain so under understanding how things survive uh on orbit is really critical to making the right design and operational decisions and you know i know there's probably a lot because of this conference i know there's a probably a whole lot of high-speed cyber security experts out in the audience and i need those people in the u.s space force the the country is counting on it but i wouldn't discount having people that are just cyber aware or cyber savvy right i have contracting officers and logisticians and program managers and they don't have to be high-end cyber security experts but they have to be aware enough about it to be able to implement cyber security protections um into our space system so the skill set is is really really broad um our adversaries are pouring billions of dollars into uh define designing uh and fielding offensive and destructive space cyber security weapons right they've repeatedly shown really a blatant disregard of safety and international norms for good behavior on orbit and the cyber security aspects of our space systems is really a key battleground going forward so that we can maintain that as i mentioned before peaceful uh global commons of space we really need all hands on deck if you're interested in helping in uniform if you're interested in helping uh not in uniform uh but as a government employee a commercial or civil employee to help us make cyber security more important uh or more cape more able to be developed for our space systems then we'd really love to uh to work with you or have you on the team to build that safe and secure future for our space systems lieutenant general john thompson great insight thank you for sharing all that awesome stories too and motivation for the young next generation the united states space force approach of cyber security really amazing talk thank you for your time final parting question is as you look out and you had your magic wand what's your view for the next few years in terms of things that we could accomplish it's a super exciting time what do you hope for so um um first of all john thanks to you and and thanks to cal poly uh for the invitation and and thanks to everybody for uh for their interest in cyber security especially as it relates to space systems that's here at the conference um uh there's a quote and i'll read it here uh from uh bernard schriever who was the uh the founder if you will uh a legend in uh dod space the founder of the western development division which was a predecessor organization to space and missile systems center general shrever i think captures the essence of what how we see the next couple of years the world has an ample supply of people who can always come up with a dozen good reasons why new ideas will not work and should not be tried but the people who produce progress are breed apart they have the imagination the courage and the persistence to find solutions and so i think if you're hoping that the next few years of space innovation and cyber security innovation are going to be a pony ride at the county fair then perhaps you should look for another line of work because i think the next few years in space and cyber security innovation are going to be more like a rodeo um and a very dynamic rodeo as it goes it is a an awesome privilege to be part of this ecosystem it's really an honor for me to um to be able to play some small role uh in the space ecosystem and trying to improve it uh while i'm trying to improve the chances of uh of the united states of america in a uh in a space war fighting uh uh environment um and so i thank all of you for uh participating today and for this little bit of time that you've allowed me to share with you thank you sir thank you for your leadership and thank you for the for the time for this awesome event space and cyber security symposium 2020 i'm john furrier on behalf of cal poly thanks for watching [Music]

>> Narrator: From around the globe. It's theCUBE covering space in cybersecurity symposium 2020 hosted by Cal Poly. >> Hello, everyone. Welcome to the space and cybersecurity symposium, 2020 hosted by Cal Poly where the intersection of space and security are coming together. I'm John Furrier, your host with theCUBE here in California. I want to welcome our featured guest, Lieutenant General, John F. Thompson with the United States Space Force approach to cybersecurity. That's the topic of this session. And of course he's the commander of the space and missile system center in Los Angeles Air Force Base. Also heading up Space Force. General, thank you for coming on. I really appreciate to you kicking this off. Welcome to the symposium. >> Hey, so thank you very much, John, for that very kind introduction. Also very much thank you to Cal Poly for this opportunity to speak to this audience today. Also a special shout out to one of the organizers, Dustin Debrun, for all of his work, helping get us to this point. Ladies and gentlemen as a John mentioned, I'm JT Thompson. I lead the 6,000 men and women of the United States Space Force's Space and Missile System Center, which is headquartered here at Los Angeles Air Force Base and El Segundo. If you're not quite sure where that's at, it's about a mile and a half from LAX. This is our main operating location, but we do have a number of other operating locations around the country. We're about 500 people at Kirtland Air Force Base in Albuquerque, New Mexico, and an about another 500 people on the front range of the Rockies between Colorado Springs and Denver plus a smattering of other much smaller operating locations nationwide. We're responsible for acquiring, developing and sustaining the United States Space Force's, critical space assets. That includes the satellites in the space layer and also on the ground layer our ground segments to operate those satellites. And we also are in charge of procuring launch services for the US Space Force and a number of our critical mission partners across the Department of Defense and the intelligence community. Just as a couple of examples of some of the things we do, if you're unfamiliar with our work we developed and currently sustain the 31 satellite GPS constellation that satellite constellation, while originally intended to help with global navigation, those GPS signals have provided trillions of dollars in unanticipated value to the global economy over the past three decades. GPS is everywhere. I think everybody realizes that. Agriculture, banking, the stock market, the airline industry, separate and distinct navigation systems. It's really pervasive across both capabilities for our Department of Defense and capabilities for our economy and individuals, billions of individuals across our country and the planet. Some of the other work we do for instance, in the communications sector, secure communications satellites that we designed and build that link America's sons and daughters serving in the military around the world and really enable real time support and comms for our deployed forces. And those of our allies. We also acquire infrared missile warning satellites that monitor the planet for missile launches that provide advanced warning to the US Homeland and to our allies in case some of those missile launches are nefarious. On a note, that's probably a lot closer to home, maybe a lot closer to home than many of us want to think about here in the state of California. In 2018, SMC jumped through a bunch of red tape and bureaucracy to partner with the US Forest Service during two of the largest wildfires in the state's history, the Camp and Woolsey fires in Northern California. As those fires spread out of control, we created processes on the fly to share data from our missile warning satellites. Those are satellites that are systems that are purpose built to see heat sources from thousands of miles above the planet. And we collaborated with the US Forest Service so that firefighters on the ground could track those fires more in real time and better forecast fires and where they were spreading, thereby saving lives and property by identifying hotspots and flareups for firefighters. That data that we were able to working with our contractors pass to the US Forest Service and authorities here in California, was passed in less than an hour as it was collected to get it into the hands of the emergency responders, the first responders as quickly as possible and doing that in an hour greatly surpassed what was available from some of the other assets in the airborne and ground-based fire spotters. It was really instrumental in fighting those fires and stopping their spread. We've continued that involvement in recent years, using multiple systems to support firefighters across the Western US this fall, as they battled numerous wildfires that unfortunately continue. Working together with the US Forest Service and with other partners we'd like to think that we've made a difference here, but there's still a lot more work to go. And I think that we should always be asking ourselves what else can space data be used for and how can we more rapidly get that space data to stakeholders so that they can use it for purposes of good, if you will. How else can we protect our nation? How else can we protect our friends and allies? I think a major component of the discussion that we will have throughout this conference is that the space landscape has changed rapidly and continues to change rapidly. Just over the past few years, John and I were talking before we went live here and 80 nations now have space programs. Nearly 80 space faring nations on the planet. If you just look at one mission area that the Department of Defense is interested in, and that's small launch, there are currently over 100 different small launch companies within the US industrial base vying for commercial DoD and civil payload capabilities, mostly to lower earth orbit. It's truly a remarkable time. If you factor in those things like artificial intelligence and machine learning, where we're revolutionizing really, the ways that we generate process and use data. It's really remarkable. In 2016, so if you think about this four years ago, NASA estimated that there were 28 terabytes of information transiting their space network each day. And that was four years ago. Obviously we've got a lot of desire to work with a lot of the people in the audience in this conference, we need to work with big thinkers, like many of you to answer questions on how best we apply data analytics to extract value and meaning from that data. We need new generations of thinkers to help apply cutting edge theories of data mining, cyber behaviorism, and Internet of Things 2.0, it's just truly a remarkable time to be in the space business and the cyber aspects of the space business are truly, truly daunting and important to all of us. Integrating cyber security into our space systems, both commercial and government is a mandate. it's no longer just a nice to have as the US Space Force and Department of the Air Force leadership has said many times over the past couple of years, space is becoming congested and contested. And that contested aspect means that we've got to focus on cyber security in the same way that the banking industry and cyber commerce focus on cybersecurity day in and day out. The value of the data and services provided is really directly tied to the integrity and availability of that data and services from the space layer, from the ground control segments associated with it. And this value is not just military, it's also economic and it's not just American, it's also a value for the entire world, particularly our allies, as we all depend upon space and space systems. Your neighbors and friends here in California that are employed at the space and missile system center work with network defenders. We work with our commercial contractors and our systems developers, our international allies and partners to try and build as secure and resilient systems as we can from the ground up that keep the global comments of space free and open for exploration and for commerce as John and I were talking earlier, before we came online, there's an aspect of cybersecurity for space systems, especially for some of our legacy systems, that's more, how do we bolt this on? Cause we fielded those space systems a number of years ago, and the challenges of cybersecurity in the space domain have grown. So we have a part that we have to worry about, bolting it on, but then we have to worry about building it in as we field new systems and build in a flexibility that realizes that the cyber threat or the cybersecurity landscape will evolve over time. It's not just going to be stagnant. There will always be new vulnerabilities and new threat vectors that we all have to look at. Look, as Secretary Barrett, who is our secretary of the air force likes to say most Americans use space before they have their first cup of coffee in the morning. The American way of life really depends on space. And as part of the United States Space Force, we work with defense leaders, our Congress joint, and international military teammates and industry to ensure American leadership in space. I really thank you for this opportunity to address the audience today, John, and thanks so much to Cal Poly for letting me be one of the speakers at this event. I've really looked forward to this for several months. And so with that, I look forward to your questions as we kind of move along here. >> General, thank you very much for those awesome introductory statement. For the folks watching on the stream, Brigadier General Carthan's going to be in the chat, answering any questions, feel free to chat away. He's the vice commander of Space and Missile System Center, he'll be available. A couple of comments from your keynote before I get to my questions. Cause it just jumped into my head. You mentioned the benefits of say space with the fires in California. We're living that here. That's really realtime. That's a benefit. You also mentioned the ability for more people launching payloads into space. I'm only imagined Moore's law smaller, faster, cheaper applies to rockets too. So I'm imagining you have the benefits of space and you have now more potential objects flying out sanctioned and maybe unsanctioned. So is it going to be more rules around that? This is an interesting question cause it's exciting Space Force, but for all the good there is potentially bad out there. >> Yeah. So John, I think the basics of your question is as space becomes more congested and contested, is there a need for more international norms of how satellites fly in space? What kind of basic features satellites have to perhaps de orbit themselves? What kind of basic protections should all satellites be afforded as part of a peaceful global commons of space? I think those are all fantastic questions. And I know that US and many allied policy makers are looking very, very hard at those kinds of questions in terms of what are the norms of behavior and how we field, and field as the military term. But how we populate using civil or commercial terms that space layer at different altitudes, lower earth orbit, mid earth orbit, geosynchronous earth orbit, different kinds of orbits, what the kind of mission areas we accomplished from space. That's all things that need to be definitely taken into account as the place gets a little bit, not a little bit as the place gets increasingly more popular day in and day out. >> I'm super excited for Space Force. I know that a new generation of young folks are really interested in it's an emerging, changing great space. The focus here at this conference is space and cybersecurity, the intersection. I'd like to get your thoughts on the approach that a space force is taking to cybersecurity and how it impacts our national goals here in the United States. >> Yeah. So that's a great question John, let me talk about it in two basic ways. At number one is an and I know some people in the audience, this might make them a little bit uncomfortable, but I have to talk about the threat. And then relative to that threat, I really have to talk about the importance of cyber and specifically cyber security, as it relates to that threat. The threats that we face really represented a new era of warfare and that new era of warfare involves both space and cyber. We've seen a lot of action in recent months from certain countries, notably China and Russia that have threatened what I referred to earlier as the peaceful global commons of space. For example, it threw many unclassified sources and media sources. Everybody should understand that the Russians have been testing on orbit anti-satellite capabilities. It's been very clear if you were following just the week before last, the Department of Defense released its 2020 military and security developments involving the People's Republic of China. And it was very clear that China is developing ASATs, electronic jammers, directed energy weapons, and most relevant to today's discussion, offensive cyber capabilities. There are kinetic threats that are very, very easy to see, but a cyber attack against a critical command and control site or against a particular spacecraft could be just as devastating to the system and our war fighters in the case of GPS and important to note that that GPS system also impacts many civilians who are dependent on those systems from a first response perspective and emergency services, a cyber attack against a ground control site could cause operators to lose control of a spacecraft or an attacker could feed spoofed data to assist them to mislead operators so that they sent emergency services personnel to the wrong address. Attacks on spacecraft on orbit, whether directly via a network intrusion or enabled through malware introduced during the system's production while we're building the satellite can cripple or corrupt the data. Denial-of-service type attacks on our global networks obviously would disrupt our data flow and interfere with ongoing operations and satellite control. If GPS went down, I hesitate to say it this way, cause we might elicit some screams from the audience. But if GPS went down a Starbucks, wouldn't be able to handle your mobile order, Uber drivers wouldn't be able to find you. And Domino's certainly wouldn't be able to get there in 30 minutes or less. So with a little bit of tongue in cheek there from a military operations perspective, it's dead serious. We have become accustomed in the commercial world to threats like ransomware and malware. And those things have unfortunately become commonplace in commercial terrestrial networks and computer systems. However, what we're seeing is that our adversaries with the increased competition in space these same techniques are being retooled, if you will, to use against our national security space systems day in and day out. As I said, during my opening remarks on the importance of cyber, the value of these systems is directly tied to their integrity. If commanders in the field, firefighters in California or baristas in Starbucks, can't trust the data they're receiving, then that really harms their decision making capabilities. One of the big trends we've recently seen is the move towards proliferated LEO constellations, obviously Space X's Starlink on the commercial side and on the military side, the work that DARPA and my organization SMC are doing on Blackjack and Casino, as well as some space transport layer constellation work that the space development agency is designing are all really, really important types of mesh network systems that will revolutionaries how we plan and field war fighting systems and commercial communications and internet providing systems. But they're also heavily reliant on cybersecurity. We've got to make sure that they are secured to avoid an accident or international damage. Loss of control of these constellations really could be catastrophic from both a mission perspective or from a satellites tumbling out of low earth orbit perspective. Another trend is introductions in artificial intelligence and machine learning, onboard spacecraft are at the edge. Our satellites are really not so much hardware systems with a little software anymore in the commercial sector and in the defense sector, they're basically flying boxes full of software. And we need to ensure that data that we're getting out of those flying boxes full of software are helping us base our decisions on accurate data and algorithms, governing the right actions and that those systems are impervious to the extent possible to nefarious modifications. So in summation, cybersecurity is a vital element of everything in our national security space goals. And I would argue for our national goals, writ large, including economic and information dimensions, the Space Force leadership at all levels from some of the brand new second lieutenants that general Raymond swore in to the space force this morning, ceremonially from the air force associations, airspace and cyberspace conference to the various highest levels, General Raymond, General DT Thompson, myself, and a number of other senior leaders in this enterprise. We've got to make sure that we're all working together to keep cyber security at the forefront of our space systems cause they absolutely depend on it. >> You mentioned hardware, software threats, opportunities, challenges. I want to ask you because you got me thinking of the minute they're around infrastructure. We've heard critical infrastructure, grids here on earth. You're talking about critical infrastructure, a redefinition of what critical infrastructure is, an extension of what we have. So I'd love to get your thoughts about Space Force's view of that critical infrastructure vis-a-vis the threat vectors, because the term threat vectors has been kicked around in the cyberspace. Oh you have threat vectors. They're always increasing the surface area. If the surface area is from space, it's an unlimited service area. So you got different vectors. So you've got new critical infrastructure developing real time, really fast. And you got an expanded threat vector landscape. Putting that in perspective for the folks that aren't really inside the ropes on these critical issues. How would you explain this and how would you talk about those two things? >> So I tell you, just like, I'm sure people in the security side or the cybersecurity side of the business in the banking industry feel, they feel like it's all possible threat vectors represent a dramatic and protect potentially existential threat to all of the dollars that they have in the banking system, to the financial sector. On the Department of Defense side, we've got to have sort of the same mindset. That threat vector from, to, and through space against critical space systems, ground segments, the launch enterprise, or transportation to orbit and the various different domains within space itself. Like I mentioned before, LEO, MEO and GEO based satellites with different orbits, all of the different mission areas that are accomplished from space that I mentioned earlier, some that I did mention like a weather tactical or wide band communications, various new features of space control. All of those are things that we have to worry about from a cyber security threat perspective. And it's a daunting challenge right now. >> Yeah, that's awesome. And one of the things we've been falling on the hardware side on the ground is the supply chain. We've seen, malware being, really put in a really obscure hardware. Who manufactures it? Is it being outsourced? Obviously government has restrictions, but with the private sector, you mentioned China and the US kind of working together across these peaceful areas. But you got to look at the supply chain. How does the supply chain in the security aspect impact the mission of the US space Force? >> Yeah. Yeah. So how about another, just in terms of an example, another kind of California based historical example. The very first US Satellite, Explorer 1, was built by the jet propulsion laboratory folks, not far from here in El Segundo, up in Pasadena, that satellite, when it was first built in the late 50s weighing a little bit, over 30 pounds. And I'm sure that each and every part was custom made and definitely made by US companies. Fast forward to today. The global supply chain is so tightly coupled, and frankly many industries are so specialized, almost specialized regionally around the planet. We focus every day to guarantee the integrity of every component that we put in our space systems is absolutely critical to the operations of those satellites and we're dependent upon them, but it becomes more difficult and more difficult to understand the heritage, if you will, of some of the parts that are used, the thousands of parts that are used in some of our satellites that are literally school bus sized. The space industry, especially national security space sector is relatively small compared to other commercial industries. And we're moving towards using more and more parts from non US companies. Cybersecurity and cyber awareness have to be baked in from the beginning if we're going to be using parts that maybe we don't necessarily understand 100% like an Explorer one, the lineage of that particular part. The environmental difficulties in space are well known. The radiation environment, the temperature extremes, the vacuum, those require specialized component. And the US military is not the only customer in that space. In fact, we're definitely not the dominant customer in space anymore. All those factors require us along with our other government partners and many different commercial space organizations to keep a very close eye on our supply chains, from a quality perspective, a security perspective and availability. There's open source reporting on supply training intrusions from many different breaches of commercial retailers to the infectious spread of compromised patches, if you will. And our adversaries are aware of these techniques. As I mentioned earlier, with other forms of attack, considering our supply chains and development networks really becomes fair game for our adversaries. So we have to take that threat seriously. Between the government and industry sectors here in the US. We're also working with our industry partners to enact stronger defenses and assess our own vulnerabilities. Last fall, we completed an extensive review of all of our major contracts here at Space and Missile System Center to determine the levels of cyber security requirements we've implemented across our portfolio. And it sounds really kind of businessy geeky, if you will. Hey, we looked at our contracts to make sure that we had the right clauses in our contracts to address cybersecurity as dynamically as we possibly could. And so we found ourselves having to add new language to our contracts, to require system developers, to implement some more advanced protective measures in this evolving cyber security environment. So that data handling and supply chain protections from contract inception to launch and operations were taken into account. Cyber security really is a key performance parameter for us now. Performance of the system, It's as important as cost, it's as important as schedule, because if we deliver the perfect system on time and on cost, it can perform that missile warning or that communications mission perfectly, but it's not cyber secure. If it's doesn't have cyber protections built into it, or the ability to implement mitigations against cyber threats, then we've essentially fielded a shoe box in space that doesn't do the CA the war fighter or the nation any good. Supply chain risk management is a major challenge for us. We're doing a lot to coordinate with our industry partners. We're all facing it head on to try and build secure and trusted components that keep our confidence as leaders, firefighters, and baristas as the case may be. But it is a challenge. And we're trying to rise to that challenge. >> This is so exciting this new area, because it really touches everything. Talk about geeking out on the tech, the hardware, the systems but also you put your kind of MBA hat on you go, what's the ROI of extra development and how things get built. Because the always the exciting thing for space geeks is like, if you're building cool stuff, it's exciting, but you still have to build. And cybersecurity has proven that security has to be baked in from the beginning and be thought as a system architecture. So you're still building things, which means you got to acquire things, you got to acquire parts, you got acquire build software and sustain it. How is security impacting the acquisition and the sustainment of these systems for space? >> Yeah. From initial development, through planning for the acquisition, design, development, our production fielding and sustainment, it impacts all aspects of the life cycle, John. We simply, especially from the concept of baking in cybersecurity, we can't wait until something is built and then try and figure out how to make it cyber secure. So we've moved way further towards working side by side with our system developers to strengthen cybersecurity from the very beginning of a systems development, cyber security, and the resilience associated with it really have to be treated as a key system attribute. As I mentioned earlier, equivalent with data rates or other metrics of performance. We like to talk in the space world about mission assurance and mission assurance has always sort of taken us as we technically geek out. Mission assurance has always taken us to the will this system work in space. Can it work in a vacuum? Can it work in as it transfers through the Van Allen radiation belt or through the Southern hemisphere's electromagnetic anomaly? Will it work out in space? And now from a resiliency perspective, yeah, it has to work in space. It's got to be functional in space, but it's also got to be resistant to these cybersecurity threats. It's not just, I think a General D.T Thompson quoted this term. It's not just widget assurance anymore. It's mission assurance. How does that satellite operator that ground control segment operate while under attack? So let me break your question a little bit, just for purposes of discussion into really two parts, cybersecurity, for systems that are new and cybersecurity for systems that are in sustainment are kind of old and legacy. Obviously there's cyber vulnerabilities that threatened both, and we really have to employ different strategies for defensive of each one. For new systems. We're desperately trying to implement across the Department of Defense and particularly in the space world, a kind of a dev sec ops methodology and practice to delivering software faster and with greater security for our space systems. Here at SMC, we have a program called enterprise ground services, which is a toolkit, basically a collection of tools for common command and control of different satellite systems, EGS as we call it has an integrated suite for defensive cyber capabilities. Network operators can use these tools to gain unprecedented insight to data flows and to monitor space network traffic for anomalies or other potential indicators of a bad behavior, malicious behavior, if you will, it's rudimentary at this point, but because we're using DevSecOps and that incremental development approach, as we scale it, it just becomes more and more capable. Every product increment that we feel. Here at LA Air Force Base, we have the United Space Force's West Coast Software Factory, which we've dubbed the Kobayashi Maru. They're using those agile DevOps software development practices to deliver a space awareness software to the combined space operations center. Affectionately called the CSpock that CSpock is just on the road from Cal Poly there in San Luis Obispo at Vandenberg Air Force Base. They've so securely linked the sea Spock with other space operation centers around the planet, our allies, Australia, Canada, and the UK. We're partnering with all of them to enable secure and enhanced combined space operations. So lots of new stuff going on as we bake in new development capabilities for our space systems. But as I mentioned earlier, we've got large constellations of satellites on orbit right now. Some of them are well in excess of a decade or more or old on orbit. And so the design aspects of those satellites are several decades old. But we still have to worry about them cause they're critical to our space capabilities. We've been working with an air force material command organization called CROWS, which stands for the Cyber Resiliency Office for Weapon Systems to assess all of those legacy platforms from a cyber security perspective and develop defensive strategies and potential hardware and software upgrades to those systems to better enable them to live through this increasingly cybersecurity concerned era that we currently live in. Our industry partners have been critical to both of those different avenues. Both new systems and legacy systems. We're working closely with them to defend and upgrade national assets and develop the capabilities to do similar with new national assets coming online. The vulnerabilities of our space systems really kind of threatened the way we've done business in the past, both militarily and in the case of GPS economically. The impacts of that cybersecurity risk are clear in our acquisition and sustainment processes, but I've got to tell you, as the threat vectors change, as the vulnerabilities change, we've got to be nimble enough, agile enough, to be able to bounce back and forth. We can't just say, many people in the audience are probably familiar with the RMF or the Risk Management Framework approach to reviewing the cyber security of a system. We can't have program managers and engineers just accomplish an RMF on a system. And then, hey, high five, we're all good. It's a journey, not a destination, that's cybersecurity. And it's a constant battle rhythm through our weapon systems lifecycle, not just a single event. >> I want to get to this commercial business needs and your needs on the next question. But before I go there, you mentioned agile. And I see that clearly because when you have accelerated innovation cycles, you've got to be faster. And we saw this in the computer industry, mainframes, mini computers, and then we started getting beyond maybe when the internet hit and PCs came out, you saw the big enterprises, the banks and government start to work with startups. And it used to be a joke in the entrepreneurial circles is that, there's no way if you are a startup you're ever going to get a contract with a big business enterprise. Now that used to be for public sector and certainly for you guys. So as you see startups out there and there's acquisition involved, I'm sure would love to have a contract with Space Force. There's an ROI calculation where if it's in space and you have a sustainment view and it's software, you might have a new kind of business model that could be attractive to startups. Could you share your thoughts on the folks who want to be a supplier to you, whether they're a startup or an existing business that wants to be agile, but they might not be that big company. >> John, that's a fantastic question. We're desperately trying to reach out to those new space advocates, to those startups, to those what we sometimes refer to, within the Department of Defense, those non traditional defense contractors. A couple of things just for thinking purposes on some of the things that we're trying to highlight. Three years ago, we created here at Space and Missile System Center, the Space Enterprise Consortium to provide a platform, a contractual vehicle, really to enable us to rapidly prototype, development of space systems and to collaborate between the US Space Force, traditional defense contractors, non traditional vendors like startups, and even some academic institutions. SPEC, as we call it, Space Enterprise Consortium uses a specialized contracting tool to get contracts awarded quickly. Many in the audience may be familiar with other transaction agreements. And that's what SPEC is based on. And so far in just three years, SPEC has awarded 75 different prototyping contracts worth over $800 million with a 36% reduction in time to award. And because it's a consortium based competition for these kinds of prototyping efforts, the barrier to entry for small and nontraditional, for startups, even for academic institutions to be able to compete for these kinds of prototyping has really lowered. These types of partnerships that we've been working through on spec have really helped us work with smaller companies who might not have the background or expertise in dealing with the government or in working with cyber security for their systems, both our developmental systems and the systems that they're designing and trying to build. We want to provide ways for companies large and small to partner together in support kind of mutually beneficial relationships between all. Recently at the Annual Air Force Association conference that I mentioned earlier, I moderated a panel with several space industry leaders, all from big traditional defense contractors, by the way. And they all stressed the importance of building bridges and partnerships between major contractors in the defense industry and new entrance. And that helps us capture the benefits of speed and agility that come with small companies and startups, as well as the expertise and specialized skill sets of some of those larger contractors that we rely on day in and day out. Advanced cyber security protections and utilization of secure facilities are just a couple of things that I think we could be prioritizing more so in those collaborations. As I mentioned earlier, the SPEC has been very successful in awarding a number of different prototyping contracts and large dollar values. And it's just going to get better. There's over 400 members of the space enterprise consortium, 80% of them are non traditional kinds of vendors. And we just love working with them. Another thing that many people in the audience may be familiar with in terms of our outreach to innovators, if you will, and innovators that include cyber security experts is our space pitch day events. So we held our first event last November in San Francisco, where we awarded over a two day period about $46 million to 30 different companies that had potentially game changing ideas. These were phase two small business innovative research efforts that we awarded with cash on the spot. We're planning on holding our second space pitch day in the spring of 2021. We're planning on doing it right here in Los Angeles, COVID-19 environment permitting. And we think that these are fantastic venues for identifying and working with high-speed startups, and small businesses who are interested in really, truly partnering with the US Air Force. It's, as I said before, it's a really exciting time to be a part of this business. And working with the innovation economy is something that the Department of Defense really needs to do in that the innovation that we used to think was ours. That 80% of the industrial base innovation that came from the Department of Defense, the script has been flipped there. And so now more than 70%, particularly in space innovation comes from the commercial sector, not from the defense business itself. And so that's a tsunami of investment and a tsunami of a capability. And I need to figure out how to get my surfboard out and ride it, you know what I mean? >> Yeah, It's one of those things where the script has been flipped, but it's exciting because it's impacting everything. When you're talking about systems architecture? You're talking about software, you're talking about a business model. You're talking about dev sec opsx from a technical perspective, but now you have a business model innovation. All the theaters are exploding in innovation, technical, business, personnel. This brings up the workforce challenge. You've got the cyber needs for the US Space Force, It's probably great ROI model for new kinds of software development that could be priced into contracts. That's a entrepreneurial innovation, you've got the business model theater, you've got the personnel. How does the industry adopt and change? You guys are clearly driving this. How does the industry adjust to you? >> Yeah. So I think a great way to answer that question is to just talk about the kind of people that we're trying to prioritize in the US Space Force from an acquisition perspective, and in this particular case from a cybersecurity perspective. As I mentioned earlier, it's the most exciting time to be in space programs, really since the days of Apollo. Just to put it in terms that maybe have an impact with the audience. From 1957 until today, approximately 9,000 satellites have been launched from the various space varying countries around the planet. Less than 2000 of those 9,000 are still up on orbit and operational. And yet in the new space regime players like Space X have plans to launch, 12,000 satellites for some of their constellations alone. It really is a remarkable time in terms of innovation and fielding of space capabilities and all of those space capabilities, whether they're commercial, civil, or defense are going to require appropriate cybersecurity protections. It's just a really exciting time to be working in stuff like this. And so folks like the folks in this audience who have a passion about space and a passion about cybersecurity are just the kind of people that we want to work with. Cause we need to make sure our systems are secure and resilient. We need folks that have technical and computing expertise, engineering skills to be able to design cyber secure systems that can detect and mitigate attacks. But we also, as you alluded to, we need people that have that business and business acumen, human networking background, so that we can launch the startups and work with the non traditional businesses. Help to bring them on board help, to secure both their data and our data and make sure our processes and systems are free as much as possible from attack. For preparation, for audience members who are young and maybe thinking about getting into this trade space, you got to be smart on digital networking. You got to understand basic internet protocols, concepts, programming languages, database design. Learn what you can for penetration or vulnerability testing and a risk assessment. I will tell you this, and I don't think he will, I know he will not mind me telling you this, but you got to be a lifelong learner and so two years ago, I'm at home evening and I get a phone call on my cell phone and it's my boss, the commander of Air Force Space command, General, J. Raymond, who is now currently the Chief of Space Operations. And he is on temporary duty, flying overseas. He lands where he's going and first thing he does when he lands is he calls me and he goes JT, while I was traveling, I noticed that there were eBooks available on the commercial airliner I was traveling on and there was an ebook on something called scrumming and agile DevSecOps. And I read it, have you read it? And I said, no, sir. But if you tell me what the title of the book is, I will read it. And so I got to go to my staff meeting, the very next week, the next time we had a staff meeting and tell everybody in the staff meeting, hey, if the four star and the three star can read the book about scrumming, then I'm pretty sure all of you around this table and all our lieutenants and our captains our GS13s, All of our government employees can get smart on the scrumming development process. And interestingly as another side, I had a telephone call with him last year during the holidays, where he was trying to take some leave. And I said, sir, what are you up to today? Are you making eggnog for the event tonight or whatever. And the Chief of Space Operations told me no, I'm trying to teach myself Python. I'm at lesson two, and it's not going so well, but I'm going to figure this out. And so that kind of thing, if the chief of staff or the Chief of Space Operations can prioritize scrumming and Python language and innovation in his daily schedule, then we're definitely looking for other people who can do that. And we'll just say, lower levels of rank throughout our entire space force enterprise. Look, we don't need people that can code a satellite from scratch, but we need to know, we need to have people that have a basic grasp of the programming basics and cybersecurity requirements. And that can turn those things into meaningful actions, obviously in the space domain, things like basic physics and orbital mechanics are also important spaces, not an intuitive domain. So under understanding how things survive on orbit is really critical to making the right design and operational decisions. And I know there's probably a lot, because of this conference. I know there's probably a whole lot of high speed cybersecurity experts out in the audience. And I need those people in the US Space Force. The country is counting on it, but I wouldn't discount having people that are just cyber aware or cyber savvy. I have contracting officers and logisticians and program managers, and they don't have to be high end cybersecurity experts, but they have to be aware enough about it to be able to implement cyber security protections into our space systems. So the skill set is really, really broad. Our adversaries are pouring billions of dollars into designing and fielding offensive and destructive space, cybersecurity weapons. They repeatedly shown really a blatant disregard of safety and international norms for good behavior on orbit. And the cyber security aspects of our space systems is really a key battleground going forward so that we can maintain that. As I mentioned before, peaceful global comments of space, we really need all hands on deck. If you're interested in helping in uniform, if you're interested in helping, not in uniform, but as a government employee, a commercial or civil employee to help us make cyber security more important or more able to be developed for our space systems. And we'd really love to work with you or have you on the team to build that safe and secure future for our space systems. >> Lieutenant General John Thompson, great insight. Thank you for sharing all that awesome stories too, and motivation for the young next generation. The United States Space Force approach to cybersecurity. Really amazing talk, thank you for your time. Final parting question is, as you look out and you have your magic wand, what's your view for the next few years in terms of things that we could accomplish? It's a super exciting time. What do you hope for? >> So first of all, John, thanks to you and thanks to Cal Poly for the invitation and thanks to everybody for their interest in cybersecurity, especially as it relates to space systems, that's here at the conference. There's a quote, and I'll read it here from Bernard Schriever, who was the founder, if you will, a legend in a DoD space, the founder of the Western development division, which was a predecessor organization to Space and Missile System Center, General Schriever, I think captures the essence of how we see the next couple of years. "The world has an ample supply of people "who can always come up with a dozen good reasons "why new ideas will not work and should not be tried, "but the people who produce progress are breed apart. "They have the imagination, "the courage and the persistence to find solutions." And so I think if you're hoping that the next few years of space innovation and cybersecurity innovation are going to be upon a pony ride at the County fair, then perhaps you should look for another line of work, because I think the next few years in space and cybersecurity innovation are going to be more like a rodeo and a very dynamic rodeo as it goes. It is an awesome privilege to be part of this ecosystem. It's really an honor for me to be able to play some small role in the space ecosystem and trying to improve it while I'm trying to improve the chances of the United States of America in a space war fighting environment. And so I thank all of you for participating today and for this little bit of time that you've allowed me to share with you. Thank you. >> Sir, thank you for your leadership and thank you for the time for this awesome event, Space and Cyber Cybersecurity Symposium 2020, I'm John Furrier on behalf of Cal Poly, thanks for watching. (mellow music)

(upbeat electronic music) >> Narrator: From theCUBE studios in Palo Alto and Boston, connecting with thought leaders all around the world, this is a CUBE conversation. >> Okay, hello everyone. I'm John Furrier with theCUBE. We're here with Meet the Analysts segment Sunday morning. We've got everyone around the world here to discuss a bit of the news around the EU killing the privacy deal, striking it down, among other topics around, you know, data privacy and global commerce. We got great guests here, Ray Wang, CEO of Constellation Research. Bill Mew, founder and CEO of Cyber Crisis Management from the Firm Crisis Team. And JD, CEO of Spearhead Management. JD, I can let you say your name because I really can't pronounce it. How do I (laughs) pronounce it, doctor? >> I wouldn't even try it unless you are Dutch, otherwise it will seriously hurt your throat. (Ray laughing) So, JD works perfect for me. >> Doctor Drooghaag. >> And Sarbjeet Johal, who's obviously an influencer, a cloud awesome native expert. Great, guys. Great to have you on, appreciate it, thanks for comin' on. And Bill, thank you for initiating this, I appreciate all your tweets. >> Happy Sunday. (Bill laughing) >> You guys have been really tweeting up a storm, I want to get everyone together, kind of as an analyst, Meet the Analyst segment. Let's go through with it. The news is the EU and U.S. Privacy Shield for data struck down by the court, that's the BBC headline. Variety of news, different perspectives, you've got an American perspective and you've got an international perspective. Bill, we'll start with you. What does this news mean? I mean, basically half the people in the world probably don't know what the Privacy Shield means, so why is this ruling so important, and why should it be discussed? >> Well, thanks to sharing between Europe and America, it's based on a two-way promise that when data goes from Europe to America, the Americans promise to respect our privacy, and when data goes form America to Europe, the Europeans promise to respect the American privacy. Unfortunately, there are big cultural differences between the two blocks. The Europeans have a massive orientation around privacy as a human right. And in the U.S., there's somewhat more of a prioritization on national security, and therefore for some time there's been a mismatch here, and it could be argued that the Americans haven't been living up to their promise because they've had various different laws, and look how much talk about FISA and the Cloud Act that actually contravene European privacy and are incompatible with the promise Americans have given. That promise, first of all, was in the form of a treaty called Safe Harbor. This went to court and was struck down. It was replaced by Privacy Shield, which was pretty much the same thing really, and that has recently been to the court as well, and that has been struck down. There now is no other means of legally sharing data between Europe and America other than what are being called standard contractual clauses. This isn't a broad treaty between two nations, these are drawn by each individual country. But also in the ruling, they said that standard contractual clauses could not be used by any companies that were subject to mass surveillance. And actually in the U.S., the FISA courts enforce a level of mass surveillance through all of the major IT firms, of all major U.S. telcos, cloud firms, or indeed, social media firms. So, this means that for all of the companies out there and their clients, business should be carrying on as usual apart from if you're one of those major U.S. IT firms, or one of their clients. >> So, why did this come about? Was there like a major incident? Why now, was it in the court, stuck in the courts? Were people bitchin' and moanin' about it? Why did this go down, what's the real issue? >> For those of us who have been following this attentively, things have been getting more and more precarious for a number of years now. We've had a situation where there are different measures being taken in the U.S., that have continued to erode the different protections that there were for Europeans. FISA is an example that I've given, and that is the sort of secret courts and secret warrants that are issued to seize data without anyone's knowledge. There's the Cloud Act, which is a sort of extrajudicial law that means that warrants can be served in America to U.S. organizations, and they have to hand over data wherever that data resides, anywhere in the world. So, data could exist on a European server, if it was under the control of an American company, they'd have to hand that over. So, whilst FISA is in direct conflict with the promises that the Americans made, things like the Cloud Act are not only in controversion with the promise they've made, there's conflicting law here, because if you're a U.S. subsidiary of a big U.S. firm, and you're based in Europe, who do you obey, the European law that says you can't hand it over because of GDPR, or the American laws that says they've got extrajudicial control, and that you've got to hand it over. So, it's made things a complete mess. And to say has this stuff, hasn't really happened? No, there's been a gradual erosion, and this has been going through the courts for a number of years. And many of us have seen it coming, and now it just hit us. >> So, if I get you right in what you're saying, it's basically all this mishmash of different laws, and there's no coherency, and consistency, is that the core issue? >> On the European side you could argue there's quite a lot of consistency, because we uphold people's privacy, in theory. But there have been incidents which we could talk about with that, but in theory, we hold your rights dear, and also the rights of Europeans, so everyone's data should be safe here from the sort of mass surveillance we're seeing. In the U.S., there's more of a direct conflict between everything, including there's been a, in his first week in the White House, Donald Trump signed an executive order saying that the Privacy Act in the U.S., which had been the main protection for people in the U.S., no longer applied to non-U.S. citizens. Which was, if you wanted try and cause a storm, and if you wanted to try and undermine the treaty, there's no better way of doing it than that. >> A lot of ways, Ray, I mean simplify this for me, because I'm a startup, I'm hustlin', or I'm a big company, I don't even know who runs the servers anymore, and I've got data stored in multiple clouds, I got in regions, and Oracle just announced more regions, you got Amazon, a gazillion regions, I could be on-premise. I mean bottom line, what is this about? I mean, and -- >> Bill's right, I mean when Max Schrems, the Austrian. Bill's right, when Max Schrems the Austrian activist actually filed his case against Facebook for where data was being stored, data residency wasn't as popular. And you know, what it means for companies that are in the cloud is that you have to make sure your data's being stored in the region, and following those specific region rules, you can't skirt those rules anymore. And I think the cloud companies know that this has been coming for some time, and that's why there's been announced in a lot of regions, a lot of areas that are actually happening, so I think that's the important part. But going back to Bill's earlier point, which is important, is America is basically the Canary Islands of privacy, right? Privacy is there, but it isn't there in a very, very explicit sense, and I think we've been skirting the rules for quite some time, because a lot of our economy depends on that data, and the marketing of the data. And so we often confuse privacy with consent, and also with value exchange, and I think that's part of the problem of what's going on here. Companies that have been building their business models on free data, free private data, free personally identifiable data information are the ones that are at risk! And I think that's what's going on here. >> It's the classic Facebook issue, you're the product, and the data is your product. Well, I want to get into what this means, 'cause my personal take away, not knowing the specifics, and just following say, cyber security for instance, one of the tenets there is that data sharing is an invaluable, important ethos in the community. Now, everyone has their own privacy, or security data, they don't want to let everyone know about their exploits but, but it's well known in the security world that sharing data with each other, different companies and countries is actually a good thing. So, the question that comes in my mind, is this really about data sharing or data privacy, or both? >> I think it's about both. And actually what the ruling is saying here is, all we're asking from the European side is please stop spying on us and please give us a level of equal protection that you give to your own citizens. Because data comes from America to Europe, whatever that data belongs to, a U.S. citizen or a European citizen, it's given equal protection. It is only if data goes in the other direction, where you have secret courts, secret warrants, seizure of data on this massive scale, and also a level of lack of equivalence that has been imposed. And we're just asking that once you've sorted out a few of those things, we'd say everything's back on the table, away we go again! >> Why don't we merge the EU with the United States? Wouldn't that solve the problem? (Bill laughing) >> We just left Europe! (laughs heartily) >> Actually I always -- >> A hostile takeover of the UK maybe, the 52nd state. (Bill laughing loudly) >> I always pick on Bill, like Bill, you got all screaming loud and clear about all these concerns, but UKs trying to get out of that economic union. It is a union at the end of the day, and I think the problem is the institutional mismatch between the EU and U.S., U.S. is old democracy, bigger country, population wise, bigger economy. Whereas Europe is several countries trying to put together, band together as one entity, and the institutions are new, like you know, they're 15 years old, right? They're maturing. I think that's where the big mismatch is and -- >> Well, Ray, I want to get your thoughts on this, Ray wrote a book, I forget what year it was, this digital disruption, basically it was digital transformation before it was actually a trend. I mean to me it's like, do you do the process first and then figure out where the value extraction is, and this may be a Silicon Valley or an American thing, but go create value, then figure out how to create process or understand regulations. So, if data and entrepreneurship is going to be a new modern era of value, why wouldn't we want to create a rule based system that's open and enabling, and not restrictive? >> So, that's a great point, right? And the innovation culture means you go do it first, and you figure out the rules later, and that's been a very American way of getting things done, and very Silicon Valley in our perspective, not everyone, but I think in general that's kind of the trend. I think the challenge here is that we are trading privacy for security, privacy for convenience, privacy for personalization, right? And on the security level, it's a very different conversation than what it is on the consumer end, you know, personalization side. On the security side I think most Americans are okay with a little bit of "spying," at least on your own side, you know, to keep the country safe. We're not okay with a China level type of spying, which we're not sure exactly what that means or what's enforceable in the courts. We look like China to the Europeans in the way we treat privacy, and I think that's the perspective we need to understand because Europeans are very explicit about how privacy is being protected. And so this really comes back to a point where we actually have to get to a consent model on privacy, as to knowing what data is being shared, you have the right to say no, and when you have the right to say no. And then if you have a value exchange on that data, then it's really like sometimes it's monetary, sometimes it's non-monetary, sometimes there's other areas around consensus where you can actually put that into place. And I think that's what's missing at this point, saying, you know, "Do we pay for your data? Do we explicitly get your consent first before we use it?" And we haven't had that in place, and I think that's where we're headed towards. And you know sometimes we actually say privacy should be a human right, it is in the UN Charter, but we haven't figured out how to enforce it or talk about it in the digital age. And so I think that's the challenge. >> Okay, people, until they lose it, they don't really understand what it means. I mean, look at Americans. I have to say that we're idiots on this front, (Bill chuckling) but you know, the thing is most people don't even understand how much value's getting sucked out of their digital exhaust. Like, our kids, TikTok and whatnot. So I mean, I get that, I think there's some, there's going to be blow back for America for sure. I just worry it's going to increase the cost of doing business, and take away from the innovation for citizen value, the people, because at the end of the day, it's for the people right? I mean, at the end of the day it's like, what's my privacy mean if I lose value? >> Even before we start talking about the value of the data and the innovation that we can do through data use, you have to understand the European perspective here. For the European there's a level of double standards and an erosion of trust. There's double standards in the fact that in California you have new privacy regulations that are slightly different to GDPR, but they're very much GDPR like. And if the boot was on the other foot, to say if we were spying on Californians and looking at their personal data, and contravening CCPA, the Californians would be up in arms! Likewise if we having promised to have a level of equality, had enacted a local rule in Europe that said that when data from America's over here, actually the privacy of Americans counts for nothing, we're only going to prioritize the privacy of Europeans. Again, the Americans would be up in arms! And therefore you can see that there are real double standards here that are a massive issue, and until those addressed, we're not going to trust the Americans. And likewise, the very fact that on a number of occasions Americans have signed up to treaties and promised to protect our data as they did with Safe Harbor, as they did with Privacy Shield, and then have blatantly, blatantly failed to do so means that actually to get back to even a level playing field, where we were, you have a great deal of trust to overcome! And the thing from the perspective of the big IT firms, they've seen this coming for a long time, as Ray was saying, and they sought to try and have a presence in Europe and other things. But the way this ruling has gone is that, I'm sorry, that isn't going to be sufficient! These big IT firms based in the U.S. that have been happy to hand over data, well some of them maybe more happy than others, but they all need to hand over data to the NSA or the CIA. They've been doing this for some time now without actually respecting this data privacy agreement that has existed between the two trading blocks. And now they've been called out, and the position now is that the U.S. is no longer trusted, and neither are any of these large American technology firms. And until the snooping stops and equality is introduced, they can now no longer, even from their European operations, they can no longer use standard contractual clauses to transfer data, which is going to be a massive restriction on their business. And if they had any sense, they'd be lobbying very, very hard right now to the Senate, to the House, to try and persuade U.S. lawmakers actually to stick to some these treaties! To stop introducing really mad laws that ride roughshod over other people's privacy, and have a certain amount of respect. >> Let's let JD weigh in, 'cause he just got in, sorry on the video, I made him back on a host 'cause he dropped off. Just, Bill, real quick, I mean I think it's like when, you know, I go to Europe there's the line for Americans, there's the line for EU. Or EU and everybody else. I mean we might be there, but ultimately this has to be solved. So, JD, I want to let you weigh in, Germany has been at the beginning forefront of privacy, and they've been hardcore, and how's this all playing out in your perspective? >> Well, the first thing that we have to understand is that in Germany, there is a very strong law for regulation. Germans panic as soon as they know regulation, so they need to understand what am I allowed to do, and what am I not allowed to do. And they expect the same from the others. For the record I'm not German, but I live in Germany for some 20 years, so I got a bit of a feeling for them. And that sense of need for regulation has spread very fast throughout the European Union, because most of the European member states of the European Union consider this, that it makes sense, and then we found that Britain had already a very good framework for privacy, so GDPR itself is very largely based on what the United Kingdom already had in place with their privacy act. Moving forward, we try to find agreement and consensus with other countries, especially the United States because that's where most of the tech providers are, only to find out, and that is where it started to go really, really bad, 2014, when the mass production by Edward Snowden came out, to find out it's not data from citizens, it's surveillance programs which include companies. I joined a purchasing conference a few weeks ago where the purchase of a large European multinational, where the purchasing director explicitly stated that usage of U.S. based tech providers for sensitive data is prohibited as a result of them finding out that they have been under surveillance. So, it's not just the citizens, there's mass -- >> There you have it, guys! We did trust you! We did have agreements there that you could have abided by, but you chose not to, you chose to abuse our trust! And you're now in a position where you are no longer trusted, and unless you can lobby your own elected representatives to actually recreate a level playing field, we're not going to continue trusting you. >> So, I think really I -- >> Well I mean that, you know, innovation has to come from somewhere, and you know, has to come from America if that's the case, you guys have to get on board, right? Is that what it -- >> Innovation without trust? >> Is that the perspective? >> I don't think it's a country thing, I mean like, it's not you or them, I think everybody -- >> I'm just bustin' Bill's chops there. >> No, but I think everybody, everybody is looking for what the privacy rules are, and that's important. And you can have that innovation with consent, and I think that's really where we're going to get to. And this is why I keep pushing that issue. I mean, privacy should be a fundamental right, and how you get paid for that privacy is interesting, or how you get compensated for that privacy if you know what the explicit value exchange is. What you're talking about here is the surveillance that's going on by companies, which shouldn't be happening, right? That shouldn't be happening at the company level. At the government level I can understand that that is happening, and I think those are treaties that the governments have to agree upon as to how much they're going to impinge on our personal privacy for the trade off for security, and I don't think they've had those discussions either. Or they decided and didn't tell any of their citizens, and I think that's probably more likely the case. >> I mean, I think what's happening here, Bill, you guys were pointing out, and Ray, you articulated there on the other side, and my kind of colorful joke aside, is that we're living a first generation modern sociology problem. I mean, this is a policy challenge that extends across multiple industries, cyber security, citizen's rights, geopolitical. I mean when would look, and even when we were doing CUBE events overseas in Europe, in North American companies we'd call it abroad, we'd just recycle the American program, and we found there's so much localization value. So, Ray, this is the digital disruption, it's the virtualization of physical for digital worlds, and it's a lot of network theory, which is computer science, a lot of sociology. This is a modern challenge, and I don't think it so much has a silver bullet, it's just that we need smart people working on this. That's my take away! >> I think we can describe the ideal endpoint being somewhere we have meaningful protection alongside the maximization of economic and social value through innovation. So, that should be what we would all agree would be the ideal endpoint. But we need both, we need meaningful protection, and we need the maximization of economic and social value through innovation! >> Can I add another axis? Another axis, security as well. >> Well, I could -- >> I put meaningful protection as becoming both security and privacy. >> Well, I'll speak for the American perspective here, and I won't speak, 'cause I'm not the President of the United States, but I will say as someone who's been from Silicon Valley and the east coast as a technical person, not a political person, our lawmakers are idiots when it comes to tech, just generally. (Ray laughing) They're not really -- (Bill laughing loudly) >> They really don't understand. They really don't understand the tech at all! >> So, the problem is -- >> I'm not claiming ours are a great deal better. (laughs) >> Well, this is why I think this is a modern problem. Like, the young people I talk to are like, "Why do we have this rules?" They're all lawyers that got into these positions of Congress on the American side, and so with the American JEDI Contract you guys have been following very closely is, it's been like the old school Oracle, IBM, and then Amazon is leading with an innovative solution, and Microsoft has come in and re-pivoted. And so what you have is a fight for the digital future of citizenship! And I think what's happening is that we're in a massive societal transition, where the people in charge don't know what the hell they're talkin' about, technically. And they don't know who to tap to solve the problems, or even shape or frame the problems. Now, there's pockets of people that are workin' on it, but to me as someone who looks at this saying, it's a pretty simple solution, no one's ever seen this before. So, there's a metaphor you can draw, but it's a completely different problem space because it's, this is all digital, data's involved. >> We've got a lobbyists out there, and we've got some tech firms spending an enormous amount of lobbying. If those lobbyists aren't trying to steer their representatives in the right direction to come up with law that aren't going to massively undermine trade and data sharing between Europe and America, then they're making a big mistake, because we got here through some really dumb lawmaking in the U.S., I mean, there are none of the laws in Europe that are a problem here. 'Cause GDPR isn't a great difference, a great deal different from some of the laws that we have already in California and elsewhere. >> Bill, Bill. >> The laws that are at issue here -- >> Bill, Bill! You have to like, back up a little bit from that rhetoric that EU is perfect and U.S. is not, that's not true actually. >> I'm not saying we're perfect! >> No, no, you say that all the time. >> But I'm saying there's a massive lack of innovation. Yeah, yeah. >> I don't, I've never said it! >> Arm wrestle! >> Yes, yes. >> When I'm being critical of some of the dumb laws in the U.S, (Sarbjeet laughing) I'm not saying Europe is perfect. What we're trying to say is that in this particular instance, I said there was an equal balance here between meaningful protection and the maximization of economic and social value. On the meaningful protection side, America's got it very wrong in terms of the meaningful protection it provides to civil European data. On the maximization of economic and social value, I think Europe's got it wrong. I think there are a lot of things we could do in Europe to actually have far more innovation. >> Yeah. >> It's a cultural issue. The Germans want rules, that's what they crave for. America's the other way, we don't want rules, I mean, pretty much is a rebel society. And that's kind of the ethos of most tech companies. But I think you know, to me the media, there's two things that go on with this tech business. The company's themselves have to be checked by say, government, and I believe in not a lot of regulation, but enough to check the power of bad actors. Media so called "checking power", both of these major roles, they don't really know what they're talking about, and this is back to the education piece. The people who are in the media so called "checking power" and the government checking power assume that the companies are bad. Right, so yeah, because eight out of ten companies like Amazon, actually try to do good things. If you don't know what good is, you don't really, (laughs) you know, you're in the wrong game. So, I think media and government have a huge education opportunity to look at this because they don't even know what they're measuring. >> I support the level of innovation -- >> I think we're unreeling from the globalization. Like, we are undoing the globalization, and that these are the side effects, these conflicts are a side effect of that. >> Yeah, so all I'm saying is I support the focus on innovation in America, and that has driven an enormous amount of wealth and value. What I'm questioning here is do you really need to spy on us, your allies, in order to help that innovation? And I'm starting to, I mean, do you need mass surveillance of your allies? I mean, I can see you may want to have some surveillance of people who are a threat to you, but wait, guys, we're meant to be on your side, and you haven't been treating our privacy with a great deal of respect! >> You know, Saudi Arabia was our ally. You know, 9/11 happened because of them, their people, right? There is no ally here, and there is no enemy, in a way. We don't know where the rogue actors are sitting, like they don't know, they can be within the walls -- >> It's well understood I think, I agree, sorry. it's well understood that nation states are enabling terrorist groups to take out cyber attacks. That's well known, the source enables it. So, I think there's the privacy versus -- >> I'm not sure it's true in your case that it's Europeans that's doing this though. >> No, no, well you know, they share -- >> I'm a former officer in the Royal Navy, I've stood shoulder to shoulder with my U.S. counterparts. I put my life on the line on NATO exercises in real war zones, and I'm now a disabled ex-serviceman as a result of that. I mean, if I put my line on the line shoulder to shoulder with Americans, why is my privacy not respected? >> Hold on -- >> I feel it's, I was going to say actually that it's not that, like even the U.S., right? Part of the spying internally is we have internal actors that are behaving poorly. >> Yeah. >> Right, we have Marxist organizations posing as, you know, whatever it is, I'll leave it at that. But my point being is we've got a lot of that, every country has that, every country has actors and citizens and people in the system that are destined to try to overthrow the system. And I think that's what that surveillance is about. The question is, we don't have treaties, or we didn't have your explicit agreements. And that's why I'm pushing really hard here, like, they're separating privacy versus security, which is the national security, and privacy versus us as citizens in terms of our data being basically taken over for free, being used for free. >> John: I agree with that. >> That I think we have some agreement on. I just think that our governments haven't really had that conversation about what surveillance means. Maybe someone agreed and said, "Okay, that's fine. You guys can go do that, we won't tell anybody." And that's what it feels like. And I don't think we deliberately are saying, "Hey, we wanted to spy on your citizens." I think someone said, "Hey, there's a benefit here too." Otherwise I don't think the EU would have let this happen for that long unless Max had made that case and started this ball rolling, so, and Edward Snowden and other folks. >> Yeah, and I totally support the need for security. >> I want to enter the -- >> I mean we need to, where there are domestic terrorists, we need to stop them, and we need to have local action in UK to stop it happening here, and in America to stop it happening there. But if we're doing that, there is absolutely no need for the Americans to be spying on us. And there's absolutely no need for the Americans to say that privacy applies to U.S. citizens only, and not to Europeans, these are daft, it's just daft! >> That's a fair point. I'm sure GCHQ and everyone else has this covered, I mean I'm sure they do. (laughs) >> Oh, Bill, I know, I've been involved, I've been involved, and I know for a fact the U.S. and the UK are discussing I know a company called IronNet, which is run by General Keith Alexander, funded by C5 Capital. There's a lot of collaboration, because again, they're tryin' to get their arms around how to frame it. And they all agree that sharing data for the security side is super important, right? And I think IronNet has this thing called Iron Dome, which is essentially like they're saying, hey, we'll just consistency around the rules of shared data, and we can both, everyone can have their own little data. So, I think there's recognition at the highest levels of some smart people on both countries. (laughs) "Hey, let's work together!" The issue I have is just policy, and I think there's a lot of clustering going on. Clustered here around just getting out of their own way. That's my take on that. >> Are we a PG show? Wait, are we a PG show? I just got to remember that. (laughs) (Bill laughing) >> It's the internet, there's no regulation, there's no rules! >> There's no regulation! >> The European rules or is it the American rules? (Ray laughing) >> I would like to jump back quickly to the purpose of the surveillance, and especially when mass surveillance is done under the cover of national security and terror prevention. I worked with five clients in the past decade who all have been targeted under mass surveillance, which was revealed by Edward Snowden, and when they did their own investigation, and partially was confirmed by Edward Snowden in person, they found out that their purchasing department, their engineering department, big parts of their pricing data was targeted in mass surveillance. There's no way that anyone can explain me that that has anything to do with preventing terror attacks, or finding the bad guys. That is economical espionage, you cannot call it in any other way. And that was authorized by the same legislation that authorizes the surveillance for the right purposes. I'm all for fighting terror, and anything that can help us prevent terror from happening, I would be the first person to welcome it. But I do not welcome when that regulation is abused for a lot of other things under the cover of national interest. I understand -- >> Back to the lawmakers again. And again, America's been victim to the Chinese some of the individual properties, well documented, well known in tech circles. >> Yeah, but just 'cause the Chinese have targeted you doesn't give you free right to target us. >> I'm not saying that, but its abuse of power -- >> If the U.S. can sort out a little bit of reform, in the Senate and the House, I think that would go a long way to solving the issues that Europeans have right now, and a long way to sort of reaching a far better place from which we can all innovate and cooperate. >> Here's the challenge that I see. If you want to be instrumenting everything, you need a closed society, because if you have a free country like America and the UK, a democracy, you're open. If you're open, you can't stop everything, right? So, there has to be a trust, to your point, Bill. As to me that I'm just, I just can't get my arms around that idea of complete lockdown and data surveillance because I don't think it's gettable in the United States, like it's a free world, it's like, open. It should be open. But here we've got the grids, and we've got the critical infrastructure that should be protected. So, that's one hand. I just can't get around that, 'cause once you start getting to locking down stuff and measuring everything, that's just a series of walled gardens. >> So, to JD's point on the procurement data and pricing data, I have been involved in some of those kind of operations, and I think it's financial espionage that they're looking at, financial security, trying to figure out a way to track down capital flows and what was purchased. I hope that was it in your client's case, but I think it's trying to figure out where the money flow is going, more so than trying to understand the pricing data from competitive purposes. If it is the latter, where they're stealing the competitive information on pricing, and data's getting back to a competitor, that is definitely a no-no! But if it's really to figure out where the money trail went, which is what I think most of those financial analysts are doing, especially in the CIA, or in the FBI, that's really what that probably would have been. >> Yeah, I don't think that the CIA is selling the data to your competitors, as a company, to Microsoft or to Google, they're not selling it to each other, right? They're not giving it to each other, right? So, I think the one big problem I studied with FISA is that they get the data, but how long they can keep the data and how long they can mine the data. So, they should use that data as exhaust. Means like, they use it and just throw it away. But they don't, they keep mining that data at a later date, and FISA is only good for five years. Like, I learned that every five years we revisit that, and that's what happened this time, that we renewed it for six years this time, not five, for some reason one extra year. So, I think we revisit all these laws -- >> Could be an election cycle. >> Huh? >> Could be an election cycle maybe. (laughs) >> Yes, exactly! So, we revisit all these laws with Congress and Senate here periodically just to make sure that they are up to date, and that they're not infringing on human rights, or citizen's rights, or stuff like that. >> When you say you update to check they're not conflicting with anything, did you not support that it was conflicting with Privacy Shield and some of the promises you made to Europeans? At what point did that fail to become obvious? >> It does, because there's heightened urgency. Every big incident happens, 9/11 caused a lot of new sort of like regulations and laws coming into the picture. And then the last time, that the Russian interference in our election, that created some sort of heightened urgency. Like, "We need to do something guys here, like if some country can topple our elections, right, that's not acceptable." So, yeah -- >> And what was it that your allies did that caused you to spy on us and to downgrade our privacy? >> I'm not expert on the political systems here. I think our allies are, okay, loose on their, okay, I call it village politics. Like, world is like a village. Like it's so only few countries, it's not millions of countries, right? That's how I see it, a city versus a village, and that's how I see the countries, like village politics. Like there are two camps, like there's Russia and China camp, and then there's U.S. camp on the other side. Like, we used to have Russia and U.S., two forces, big guys, and they managed the whole world balance somehow, right? Like some people with one camp, the other with the other, right? That's how they used to work. Now that Russia has gone, hold on, let me finish, let me finish. >> Yeah. >> Russia's gone, there's this void, right? And China's trying to fill the void. Chinese are not like, acting diplomatic enough to fill that void, and there's, it's all like we're on this imbalance, I believe. And then Russia becomes a rogue actor kind of in a way, that's how I see it, and then they are funding all these bad people. You see that all along, like what happened in the Middle East and all that stuff. >> You said there are different camps. We thought we were in your camp! We didn't expect to be spied on by you, or to have our rights downgraded by you. >> No, I understand but -- >> We thought we were on your side! >> But, but you have to guys to trust us also, like in a village. Let me tell you, I come from a village, that's why I use the villager as a hashtag in my twitter also. Like in village, there are usually one or two families which keep the village intact, that's our roles. >> Right. >> Like, I don't know if you have lived in a village or not -- >> Well, Bill, you're making some great statements. Where's the evidence on the surveillance, where can people find more information on this? Can you share? >> I think there's plenty of evidence, and I can send some stuff on, and I'm a little bit shocked given the awareness of the FISA Act, the Cloud Act, the fact that these things are in existence and they're not exactly unknown. And many people have been complaining about them for years. I mean, we've had Safe Harbor overturned, we've had Privacy Shield overturned, and these weren't just on a whim! >> Yeah, what does JD have in his hand? I want to know. >> The Edward Snowden book! (laughs) >> By Edward Snowden, which gives you plenty. But it wasn't enough, and it's something that we have to keep in mind, because we can always claim that whatever Edward Snowden wrote, that he made it up. Every publication by Edward Snowden is an avalanche of technical confirmation. One of the things that he described about the Cisco switches, which Bill prefers to quote every time, which is a proven case, there were bundles of researchers saying, "I told you guys!" Nobody paid attention to those researchers, and Edward Snowden was smart enough to get the mass media representation in there. But there's one thing, a question I have for Sabjeet, because in the two parties strategy, it is interesting that you always take out the European Union as part. And the European Union is a big player, and it will continue to grow. It has a growing amount of trade agreements with a growing amount of countries, and I still hope, and I think think Bill -- >> Well, I think the number of countries is reducing, you've just lost one! >> Only one. (Bill laughing loudly) Actually though, those are four countries under one kingdom, but that's another point. (Bill chortling heartily) >> Guys, final topic, 5G impact, 'cause you mentioned Cisco, couldn't help think about -- >> Let me finish please my question, John. >> Okay, go ahead. How would you the United States respond if the European Union would now legalize to spy on everybody and every company, and every governmental institution within the United States and say, "No, no, it's our privilege, we need that." How would the United States respond? >> You can try that and see economically what happens to you, that's how the village politics work, you have to listen to the mightier than you, and we are economically mightier, that's the fact. Actually it's hard to swallow fact for, even for anybody else. >> If you guys built a great app, I would use it, and surveil all you want. >> Yeah, but so this is going to be driven by the economics. (John laughing) But the -- >> That's exactly what John said. >> This is going to be driven by the economics here. The big U.S. cloud firms are got to find this ruling enormously difficult for them, and they are inevitably going to lobby for a level of reform. And I think a level of a reform is needed. Nobody on your side is actually arguing very vociferously that the Cloud Act and the discrimination against Europeans is actually a particularly good idea. The problem is that once you've done the reform, are we going to believe you when you say, "Oh, it's all good now, we've stopped it!" Because with Crypto AG scandal in Switzerland you weren't exactly honest about what you were doing. With the FISA courts, so I mean FISA secret courts, the secret warrants, how do we know and what proof can we have that you've stopped doing all these bad things? And I think one of the challenges, A, going to be the reform, and then B, got to be able to show that you actually got your act together and you're now clean. And until you can solve those two, many of your big tech companies are going to be at a competitive disadvantage, and they're going to be screaming for this reform. >> Well, I think that, you know, General Mattis said in his book about Trump and the United states, is that you need alliances, and I think your point about trust and executing together, without alliances, it really doesn't work. So, unless there's some sort of real alliance, (laughs) like understanding that there's going to be some teamwork here, (Bill laughing) I don't think it's going to go anywhere. So, otherwise it'll continue to be siloed and network based, right? So to the village point, if TikTok can become a massively successful app, and they're surveilling, so and then we have to decide that we're going to put up with that, I mean, that's not my decision, but that's what's goin' on here. It's like, what is TikTok, is it good or bad? Amazon sent out an email, and they've retracted it, that's because it went public. I guarantee you that they're talkin' about that at Amazon, like, "Why would we want infiltration by the Chinese?" And I'm speculating, I have no data, I'm just saying, you know. They email those out, then they pull it back, "Oh, we didn't mean to send that." Really, hmm? (laughs) You know, so this kind of -- >> But the TRA Balin's good, you always want to get TRA Balin out there. >> Yeah, exactly. There's some spying going on! So, this is the reality. >> So, John, you were talking about 5G, and I think you know, the role of 5G, you know, the battle between Cisco and Huawei, you just have to look at it this way, would you rather have the U.S. spy on you, or would you rather have China? And that's really your binary choice at this moment. And you know both is happening, and so the question is which one is better. Like, the one that you're in alliance with? The one that you're not in alliance with, the one that wants to bury you, and decimate your country, and steal all your secrets and then commercialize 'em? Or the one kind of does it, but doesn't really do it explicitly? So, you've got to choose. (laughs) >> It's supposed to be -- >> Or you can say no, we're going to create our own standard for 5G and kick both out, that's an option. >> It's probably not as straightforward a question as, or an answer to that question as you say, because if we were to fast-forward 50 years, I would argue that China is going to be the largest trading nation in the world. I believe that China is going to have the upper hand on many of these technologies, and therefore why would we not want to use some of their innovation, some of their technology, why would we not actually be more orientated around trading with them than we might be with the U.S.? I think the U.S. is throwing its weight around at this moment in time, but if we were to fast-forward I think looking in the longterm, if I had to put my money on Huawei or some of its competitors, I think given its level of investments in research and whatever, I think the better longterm bet is Huawei. >> No, no, actually you guys need to pick a camp. It's a village again. You have to pick a camp, you can't be with both guys. >> Global village. >> Oh, right, so we have to go with the guys that have been spying on us? >> How do you know the Chinese haven't been spying on you? (Ray and John laughing loudly) >> I think I'm very happy, you find a backdoor in the Huawei equipment and you show it to us, we'll take them to task on it. But don't start bullying us into making decisions based on what-ifs. >> I don't think I'm, I'm not qualified to represent the U.S., but what we would want to say is that if you look at the dynamics of what's going on, China, we've been studying that as well in terms of the geopolitical aspects of what happens in technology, they have to do what they're doing right now. Because in 20 years our population dynamics go like this, right? You've got the one child policy, and they won't have the ability to go out and fight for those same resources where they are, so what they're doing makes sense from a country perspective and country policy. But I think they're going to look like Japan in 20 years, right? Because the xenophobia, the lack of immigration, the lack of inside stuff coming in, an aging population. I mean, those are all factors that slow down your economy in the long run. And the lack of bringing new people in for ideas, I mean that's part of it, they're a closed system. And so I think the longterm dynamics of every closed system is that they tend to fail versus open systems. So, I'm not sure, they may have better technology along the way. But I think a lot of us are probably in the camp now thinking that we're not going to aid and abet them, in that sense to get there. >> You're competing a country with a company, I didn't say that China had necessarily everything rosy in its future, it'll be a bigger economy, and it'll be a bigger trading partner, but it's got its problems, the one child policy and the repercussions of that. But that is not one of the things, Huawei, I think Huawei's a massively unlimited company that has got a massive lead, certainly in 5G technology, and may continue to maintain a lead into 6G and beyond. >> Oh yeah, yeah, Huawei's done a great job on the 5G side, and I don't disagree with that. And they're ahead in many aspects compared to the U.S., and they're already working on the 6G technologies as well, and the roll outs have been further ahead. So, that's definitely -- >> And they've got a great backer too, the financer, the country China. Okay guys, (Ray laughing) let's wrap up the segment. Thanks for everyone's time. Final thoughts, just each of you on this core issue of the news that we discussed and the impact that was the conversation. What's the core issue? What should people think about? What's your solution? What's your opinion of how this plays out? Just final statements. We'll start with Bill, Ray, Sarbjeet and JD. >> All I'm going to ask you is stop spying on us, treat us equally, treat us like the allies that we are, and then I think we've got to a bright future together! >> John: Ray? >> I would say that Bill's right in that aspect in terms of how security agreements work, I think that we've needed to be more explicit about those. I can't represent the U.S. government, but I think the larger issue is really how do we view privacy, and how we do trade offs between security and convenience, and you know, what's required for personalization, and companies that are built on data. So, the sooner we get to those kind of rules, an understanding of what's possible, what's a consensus between different countries and companies, I think the better off we will all be a society. >> Yeah, I believe the most important kind of independence is the economic independence. Like, economically sound parties dictate the terms, that's what U.S. is doing. And the smaller countries have to live with it or pick the other bigger player, number two in this case is China. John said earlier, I think, also what JD said is the fine balance between national security and the privacy. You can't have, you have to strike that balance, because the rogue actors are sitting in your country, and across the boundaries of the countries, right? So, it's not that FISA is being fought by Europeans only. Our internal people are fighting that too, like how when you are mining our data, like what are you using it for? Like, I get concerned too, when you can use that data against me, that you have some data against me, right? So, I think it's the fine balance between security and privacy, we have to strike that. Awesome. JD? I'll include a little fake check, fact check, at the moment China is the largest economy, the European Union is the second largest economy, followed directly by the USA, it's a very small difference, and I recommend that these two big parties behind the largest economy start to collaborate and start to do that eye to eye, because if you want to balance the economical and manufacturing power of China, you cannot do that as being number two and number three. You have to join up forces, and that starts with sticking with the treaties that you signed, and that has not happened in the past, almost four years. So, let's go back to the table, let's work on rules where from both sides the rights and the privileges are properly reflected, and then do the most important thing, stick to them! >> Yep, I think that's awesome. I think I would say that these young kids in high school and college, they need to come up and solve the problems, this is going to be a new generational shift where the geopolitical landscape will change radically, you mentioned the top three there. And new alliances, new kinds of re-imagination has to be there, and from America's standpoint I'll just say that I'd like to see lawmakers have, instead of a LinkedIn handle, a GitHub handle. You know, when they all go out on campaign talk about what code they've written. So, I think having a technical background or some sort of knowledge of computer science and how the internet works with sociology and societal impact will be critical for our citizenships to advance. So, you know rather a lawyer, right so? (laughs) Maybe get some law involved in that, I mean the critical lawyers, but today most people are lawyers in American politics, but show me a GitHub handle of that congressman, that senator, I'd be impressed. So, that's what we need. >> Thanks, good night! >> Ray, you want to say something? >> I wanted to say something, because I thought the U.S. economy was 21 trillion, the EU is sittin' at about 16, and China was sitting about 14, but okay, I don't know. >> You need to do math man. >> Hey, we went over our 30 minutes time, we can do an hour with you guys, so you're still good. (laughs) >> Can't take anymore. >> No go on, get in there, go at it when you've got something to say. >> I don't think it's immaterial the exact size of the economy, I think that we're better off collaborating on even and fair terms, we are -- >> We're all better off collaborating. >> Yeah. >> Gentlemen -- >> But the collaboration has to be on equal and fair terms, you know. (laughs) >> How do you define fair, good point. Fair and balanced, you know, we've got the new -- >> We did define fair, we struck a treaty! We absolutely defined it, absolutely! >> Yeah. >> And then one side didn't stick to it. >> We will leave it right there, and we'll follow up (Bill laughing) in a later conversation. Gentlemen, you guys are good. Thank you. (relaxing electronic music)

>> Announcer: From theCUBE studios in Palo Alto, in Boston, connecting with thought leaders all around the world. This is a CUBE conversation. >> Hey, welcome back, you're ready. Jeff Frick here with theCUBE. We are still getting through the year of 2020. It's still the year of COVID and there's no end in sight I think until we get to a vaccine. That said, we're really excited to have one of our favorite guests. We haven't had him on for a while. I haven't talked to him for a long time. He used to I think have the record for the most CUBE appearances of probably any CUBE alumni. We're excited to have him joining us from his house in Palo Alto. Bill Schmarzo, you know him as the Dean of Big Data, he's got more titles. He's the chief innovation officer at Hitachi Vantara. He's also, we used to call him the Dean of Big Data, kind of for fun. Well, Bill goes out and writes a bunch of books. And now he teaches at the University of San Francisco, School of Management as an executive fellow. He's an honorary professor at NUI Galway. I think he's just, he likes to go that side of the pond and a many time author now, go check him out. His author profile on Amazon, the "Big Data MBA," "The Art of Thinking Like A Data Scientist" and another Big Data, kind of a workbook. Bill, great to see you. >> Thanks, Jeff, you know, I miss my time on theCUBE. These conversations have always been great. We've always kind of poked around the edges of things. A lot of our conversations have always been I thought, very leading edge and the title Dean of Big Data is courtesy of theCUBE. You guys were the first ones to give me that name out of one of the very first Strata Conferences where you dubbed me the Dean of Big Data, because I taught a class there called the Big Data MBA and look what's happened since then. >> I love it. >> It's all on you guys. >> I love it, and we've outlasted Strata, Strata doesn't exist as a conference anymore. So, you know, part of that I think is because Big Data is now everywhere, right? It's not the standalone thing. But there's a topic, and I'm holding in my hands a paper that you worked on with a colleague, Dr. Sidaoui, talking about what is the value of data? What is the economic value of data? And this is a topic that's been thrown around quite a bit. I think you list a total of 28 reference sources in this document. So it's a well researched piece of material, but it's a really challenging problem. So before we kind of get into the details, you know, from your position, having done this for a long time, and I don't know what you're doing today, you used to travel every single week to go out and visit customers and actually do implementations and really help people think these through. When you think about the value, the economic value, how did you start to kind of frame that to make sense and make it kind of a manageable problem to attack? >> So, Jeff, the research project was eyeopening for me. And one of the advantages of being a professor is, you have access to all these very smart, very motivated, very free research sources. And one of the problems that I've wrestled with as long as I've been in this industry is, how do you figure out what is data worth? And so what I did is I took these research students and I stick them on this problem. I said, "I want you to do some research. Let me understand what is the value of data?" I've seen all these different papers and analysts and consulting firms talk about it, but nobody's really got this thing clicked. And so we launched this research project at USF, professor Mouwafac Sidaoui and I together, and we were bumping along the same old path that everyone else got, which was inched on, how do we get data on our balance sheet? That was always the motivation, because as a company we're worth so much more because our data is so valuable, and how do I get it on the balance sheet? So we're headed down that path and trying to figure out how do you get it on the balance sheet? And then one of my research students, she comes up to me and she says, "Professor Schmarzo," she goes, "Data is kind of an unusual asset." I said, "Well, what do you mean?" She goes, "Well, you think about data as an asset. It never depletes, it never wears out. And the same dataset can be used across an unlimited number of use cases at a marginal cost equal to zero." And when she said that, it's like, "Holy crap." The light bulb went off. It's like, "Wait a second. I've been thinking about this entirely wrong for the last 30 some years of my life in this space. I've had the wrong frame. I keep thinking about this as an act, as an accounting conversation. An accounting determines valuation based on what somebody is willing to pay for." So if you go back to Adam Smith, 1776, "Wealth of Nations," he talks about valuation techniques. And one of the valuation techniques he talks about is valuation and exchange. That is the value of an asset is what someone's willing to pay you for it. So the value of this bottle of water is what someone's willing to pay you for it. So everybody fixates on this asset, valuation in exchange methodology. That's how you put it on balance sheet. That's how you run depreciation schedules, that dictates everything. But Adam Smith also talked about in that book, another valuation methodology, which is valuation in use, which is an economics conversation, not an accounting conversation. And when I realized that my frame was wrong, yeah, I had the right book. I had Adam Smith, I had "Wealth of Nations." I had all that good stuff, but I hadn't read the whole book. I had missed this whole concept about the economic value, where value is determined by not how much someone's willing to pay you for it, but the value you can drive by using it. So, Jeff, when that person made that comment, the entire research project, and I got to tell you, my entire life did a total 180, right? Just total of 180 degree change of how I was thinking about data as an asset. >> Right, well, Bill, it's funny though, that's kind of captured, I always think of kind of finance versus accounting, right? And then you're right on accounting. And we learn a lot of things in accounting. Basically we learn more that we don't know, but it's really hard to put it in an accounting framework, because as you said, it's not like a regular asset. You can use it a lot of times, you can use it across lots of use cases, it doesn't degradate over time. In fact, it used to be a liability. 'cause you had to buy all this hardware and software to maintain it. But if you look at the finance side, if you look at the pure play internet companies like Google, like Facebook, like Amazon, and you look at their valuation, right? We used to have this thing, we still have this thing called Goodwill, which was kind of this capture between what the market established the value of the company to be. But wasn't reflected when you summed up all the assets on the balance sheet and you had this leftover thing, you could just plug in goodwill. And I would hypothesize that for these big giant tech companies, the market has baked in the value of the data, has kind of put in that present value on that for a long period of time over multiple projects. And we see it captured probably in goodwill, versus being kind of called out as an individual balance sheet item. >> So I don't think it's, I don't know accounting. I'm not an accountant, thank God, right? And I know that goodwill is one of those things if I remember from my MBA program is something that when you buy a company and you look at the value you paid versus what it was worth, it stuck into this category called goodwill, because no one knew how to figure it out. So the company at book value was a billion dollars, but you paid five billion for it. Well, you're not an idiot, so that four billion extra you paid must be in goodwill and they'd stick it in goodwill. And I think there's actually a way that goodwill gets depreciated as well. So it could be that, but I'm totally away from the accounting framework. I think that's distracting, trying to work within the gap rules is more of an inhibitor. And we talk about the Googles of the world and the Facebooks of the world and the Netflix of the world and the Amazons and companies that are great at monetizing data. Well, they're great at monetizing it because they're not selling it, they're using it. Google is using their data to dominate search, right? Netflix is using it to be the leader in on-demand videos. And it's how they use all the data, how they use the insights about their customers, their products, and their operations to really drive new sources of value. So to me, it's this, when you start thinking about from an economics perspective, for example, why is the same car that I buy and an Uber driver buys, why is that car more valuable to an Uber driver than it is to me? Well, the bottom line is, Uber drivers are going to use that car to generate value, right? That $40,000, that car they bought is worth a lot more, because they're going to use that to generate value. For me it sits in the driveway and the birds poop on it. So, right, so it's this value in use concept. And when organizations can make that, by the way, most organizations really struggle with this. They struggle with this value in use concept. They want to, when you talk to them about data monetization and say, "Well, I'm thinking about the chief data officer, try not to trying to sell data, knocking on doors, shaking their tin cup, saying, 'Buy my data.'" No, no one wants your data. Your data is more valuable for how you use it to drive your operations then it's a sell to somebody else. >> Right, right. Well, on of the other things that's really important from an economics concept is scarcity, right? And a whole lot of economics is driven around scarcity. And how do you price for scarcity so that the market evens out and the price matches up to the supply? What's interesting about the data concept is, there is no scarcity anymore. And you know, you've outlined and everyone has giant numbers going up into the right, in terms of the quantity of the data and how much data there is and is going to be. But what you point out very eloquently in this paper is the scarcity is around the resources to actually do the work on the data to get the value out of the data. And I think there's just this interesting step function between just raw data, which has really no value in and of itself, right? Until you start to apply some concepts to it, you start to analyze it. And most importantly, that you have some context by which you're doing all this analysis to then drive that value. And I thought it was really an interesting part of this paper, which is get beyond the arguing that we're kind of discussing here and get into some specifics where you can measure value around a specific business objective. And not only that, but then now the investment of the resources on top of the data to be able to extract the value to then drive your business process for it. So it's a really different way to think about scarcity, not on the data per se, but on the ability to do something with it. >> You're spot on, Jeff, because organizations don't fail because of a lack of use cases. They fail because they have too many. So how do you prioritize? Now that scarcity is not an issue on the data side, but it is this issue on the people resources side, you don't have unlimited data scientists, right? So how do you prioritize and focus on those opportunities that are most important? I'll tell you, that's not a data science conversation, that's a business conversation, right? And figuring out how you align organizations to identify and focus on those use cases that are most important. Like in the paper we go through several different use cases using Chipotle as an example. The reason why I picked Chipotle is because, well, I like Chipotle. So I could go there and I could write it off as research. But there's a, think about the number of use cases where a company like Chipotle or any other company can leverage your data to drive their key business initiatives and their key operational use cases. It's almost unbounded, which by the way, is a huge challenge. In fact, I think part of the problem we see with a lot of organizations is because they do such a poor job of prioritizing and focusing, they try to solve the entire problem with one big fell swoop, right? It's slightly the old ERP big bang projects. Well, I'm just going to spend $20 million to buy this analytic capability from company X and I'm going to install it and then magic is going to happen. And then magic is going to happen, right? And then magic is going to happen, right? And magic never happens. We get crickets instead, because the biggest challenge isn't around how do I leverage the data, it's about where do I start? What problems do I go after? And how do I make sure the organization is bought in to basically use case by use case, build out your data and analytics architecture and capabilities. >> Yeah, and you start backwards from really specific business objectives in the use cases that you outline here, right? I want to increase my average ticket by X. I want to increase my frequency of visits by X. I want to increase the amount of items per order from X to 1.2 X, or 1.3 X. So from there you get a nice kind of big revenue hit that you can plan around and then work backwards into the amount of effort that it takes and then you can come up, "Is this a good investment or not?" So it's a really different way to get back to the value of the data. And more importantly, the analytics and the work to actually call out the information. >> The technologies, the data and analytic technologies available to us. The very composable nature of these allow us to take this use case by use case approach. I can build out my data lake one use case at a time. I don't need to stuff 25 data sources into my data lake and hope there's someone more valuable. I can use the first use case to say, "Oh, I need these three data sources to solve that use case. I'm going to put those three data sources in the data lake. I'm going to go through the entire curation process of making sure the data has been transformed and cleansed and aligned and enriched and met of, all the other governance, all that kind of stuff this goes on. But I'm going to do that use case by use case, 'cause a use case can tell me which data sources are most important for that given situation. And I can build up my data lake and I can build up my analytics then one use case at a time. And there is a huge impact then, huge impact when I build out use case by use case. That does not happen. Let me throw something that's not really covered in the paper, but it is very much covered in my new book that I'm working on, which is, in knowledge-based industries, the economies of learning are more powerful than the economies of scale. Now think about that for a second. >> Say that again, say that again. >> Yeah, the economies of learning are more powerful than the economies of scale. And what that means is what I learned on the first use case that I build out, I can apply that learning to the second use case, to the third use case, to the fourth use case. So when I put my data into my data lake for my first use case, and the paper covers this, well, once it's in my data lake, the cost of reusing that data in a second, third and fourth use cases is basically, you know marginal cost is zero. So I get this ability to learn about what data sets are most important and to reapply that across the organization. So this learning concept, I learn use case by use case, I don't have to do a big economies of scale approach and start with 25 datasets of which only three or four might be useful. But I'm incurring the overhead for all those other non-important data sets because I didn't take the time to go through and figure out what are my most important use cases and what data do I need to support those use cases. >> I mean, should people even think of the data per se or should they really readjust their thinking around the application of the data? Because the data in and of itself means nothing, right? 55, is that fast or slow? Is that old or young? Well, it depends on a whole lot of things. Am I walking or am I in a brand new Corvette? So it just, it's funny to me that the data in and of itself really doesn't have any value and doesn't really provide any direction into a decision or a higher order, predictive analytics until you start to manipulate the data. So is it even the wrong discussion? Is data the right discussion? Or should we really be talking about the capabilities to do stuff within and really get people focused on that? >> So Jeff, there's so many points to hit on there. So the application of data is what's the value, and the queue of you guys used to be famous for saying, "Separating noise from the signal." >> Signal from the noise. Signal from a noise, right. Well, how do you know in your dataset what's signal and what's noise? Well, the use case will tell you. If you don't know the use case and you have no way of figuring out what's important. One of the things I use, I still rail against, and it happens still. Somebody will walk up my data science team and say, "Here's some data, tell me what's interesting in it." Well, how do you separate signal from noise if I don't know the use case? So I think you're spot on, Jeff. The way to think about this is, don't become data-driven, become value-driven and value is driven from the use case or the application or the use of the data to solve that particular use case. So organizations that get fixated on being data-driven, I hate the term data-driven. It's like as if there's some sort of frigging magic from having data. No, data has no value. It's how you use it to derive customer product and operational insights that drive value,. >> Right, so there's an interesting step function, and we talk about it all the time. You're out in the weeds, working with Chipotle lately, and increase their average ticket by 1.2 X. We talk more here, kind of conceptually. And one of the great kind of conceptual holy grails within a data-driven economy is kind of working up this step function. And you've talked about it here. It's from descriptive, to diagnostic, to predictive. And then the Holy grail prescriptive, we're way ahead of the curve. This comes into tons of stuff around unscheduled maintenance. And you know, there's a lot of specific applications, but do you think we spend too much time kind of shooting for the fourth order of greatness impact, instead of kind of focusing on the small wins? >> Well, you certainly have to build your way there. I don't think you can get to prescriptive without doing predictive, and you can't do predictive without doing descriptive and such. But let me throw a really one at you, Jeff, I think there's even one beyond prescriptive. One we're talking more and more about, autonomous, a ton of analytics, right? And one of the things that paper talked about that didn't click with me at the time was this idea of orphaned analytics. You and I kind of talked about this before the call here. And one thing we noticed in the research was that a lot of these very mature organizations who had advanced from the retrospective analytics of BI to the descriptive, to the predicted, to the prescriptive, they were building one off analytics to solve a problem and getting value from it, but never reusing this analytics over and over again. They were done one off and then they were thrown away and these organizations were so good at data science and analytics, that it was easier for them to just build from scratch than to try to dig around and try to find something that was never actually ever built to be reused. And so I have this whole idea of orphaned analytics, right? It didn't really occur to me. It didn't make any sense into me until I read this quote from Elon Musk, and Elon Musk made this statement. He says, " I believe that when you buy a Tesla, you're buying an asset that appreciates in value, not depreciates through usage." I was thinking, "Wait a second, what does that mean?" He didn't actually say it, "Through usage." He said, "He believes you're buying an asset that appreciates not depreciates in value." And of course the first response I had was, "Oh, it's like a 1964 and a half Mustang. It's rare, so everybody is going to want these things. So buy one, stick it in your garage. And 20 years later, you're bringing it out and it's worth more money." No, no, there's 600,000 of these things roaming around the streets, they're not rare. What he meant is that he is building an autonomous asset. That the more that it's used, the more valuable it's getting, the more reliable, the more efficient, the more predictive, the more safe this asset's getting. So there is this level beyond prescriptive where we can think about, "How do we leverage artificial intelligence, reinforcement, learning, deep learning, to build these assets that the more that they are used, the smarter they get." That's beyond prescriptive. That's an environment where these things are learning. In many cases, they're learning with minimal or no human intervention. That's the real aha moment. That's what I miss with orphaned analytics and why it's important to build analytics that can be reused over and over again. Because every time you use these analytics in a different use case, they get smarter, they get more valuable, they get more predictive. To me that's the aha moment that blew my mind. I realized I had missed that in the paper entirely. And it took me basically two years later to realize, dough, I missed the most important part of the paper. >> Right, well, it's an interesting take really on why the valuation I would argue is reflected in Tesla, which is a function of the data. And there's a phenomenal video if you've never seen it, where they have autonomous vehicle day, it might be a year or so old. And he's got his number one engineer from, I think the Microprocessor Group, The Computer Vision Group, as well as the autonomous driving group. And there's a couple of really great concepts I want to follow up on what you said. One is that they have this thing called The Fleet. To your point, there's hundreds of thousands of these things, if they haven't hit a million, that are calling home reporting home every day as to exactly how everyone took the Northbound 101 on-ramp off of University Avenue. How fast did they go? What line did they take? What G-forces did they take? And every one of those cars feeds into the system, so that when they do the autonomous update, not only are they using all their regular things that they would use to map out that 101 Northbound entry, but they've got all the data from all the cars that have been doing it. And you know, when that other car, the autonomous car couple years ago hit the pedestrian, I think in Phoenix, which is not good, sad, killed a person, dark tough situation. But you know, we are doing an autonomous vehicle show and the guy who made a really interesting point, right? That when something like that happens, typically if I was in a car wreck or you're in a car wreck, hopefully not, I learned the person that we hit learns and maybe a couple of witnesses learn, maybe the inspector. >> But nobody else learns. >> But nobody else learns. But now with the autonomy, every single person can learn from every single experience with every vehicle contributing data within that fleet. To your point, it's just an order of magnitude, different way to think about things. >> Think about a 1% improvement compounded 365 times, equals I think 38 X improvement. The power of 1% improvements over these 600,000 plus cars that are learning. By the way, even when the autonomous FSD, the full self-driving mode module isn't turned on, even when it's not turned on, it runs in shadow mode. So it's learning from the human drivers, the human overlords, it's constantly learning. And by the way, not only they're collecting all this data, I did a little research, I pulled out some of their job search ads and they've built a giant simulator, right? And they're there basically every night, simulating billions and billions of more driven miles because of the simulator. They are building, he's going to have a simulator, not only for driving, but think about all the data he's capturing as these cars are riding down the road. By the way, they don't use Lidar, they use video, right? So he's driving by malls. He knows how many cars are in the mall. He's driving down roads, he knows how old the cars are and which ones should be replaced. I mean, he has this, he's sitting on this incredible wealth of data. If anybody could simulate what's going on in the world and figure out how to get out of this COVID problem, it's probably Elon Musk and the data he's captured, be courtesy of all those cars. >> Yeah, yeah, it's really interesting, and we're seeing it now. There's a new autonomous drone out, the Skydio, and they just announced their commercial product. And again, it completely changes the way you think about how you use that tool, because you've just eliminated the complexity of driving. I don't want to drive that, I want to tell it what to do. And so you're saying, this whole application of air force and companies around things like measuring piles of coal and measuring these huge assets that are volume metric measured, that these things can go and map out and farming, et cetera, et cetera. So the autonomy piece, that's really insightful. I want to shift gears a little bit, Bill, and talk about, you had some theories in here about thinking of data as an asset, data as a currency, data as monetization. I mean, how should people think of it? 'Cause I don't think currency is very good. It's really not kind of an exchange of value that we're doing this kind of classic asset. I think the data as oil is horrible, right? To your point, it doesn't get burned up once and can't be used again. It can be used over and over and over. It's basically like feedstock for all kinds of stuff, but the feedstock never goes away. So again, or is it that even the right way to think about, do we really need to shift our conversation and get past the idea of data and get much more into the idea of information and actionable information and useful information that, oh, by the way, happens to be powered by data under the covers? >> Yeah, good question, Jeff. Data is an asset in the same way that a human is an asset. But just having humans in your company doesn't drive value, it's how you use those humans. And so it's really again the application of the data around the use cases. So I still think data is an asset, but I don't want to, I'm not fixated on, put it on my balance sheet. That nice talk about put it on a balance sheet, I immediately put the blinders on. It inhibits what I can do. I want to think about this as an asset that I can use to drive value, value to my customers. So I'm trying to learn more about my customer's tendencies and propensities and interests and passions, and try to learn the same thing about my car's behaviors and tendencies and my operations have tendencies. And so I do think data is an asset, but it's a latent asset in the sense that it has potential value, but it actually has no value per se, inputting it into a balance sheet. So I think it's an asset. I worry about the accounting concept medially hijacking what we can do with it. To me the value of data becomes and how it interacts with, maybe with other assets. So maybe data itself is not so much an asset as it's fuel for driving the value of assets. So, you know, it fuels my use cases. It fuels my ability to retain and get more out of my customers. It fuels ability to predict what my products are going to break down and even have products who self-monitor, self-diagnosis and self-heal. So, data is an asset, but it's only a latent asset in the sense that it sits there and it doesn't have any value until you actually put something to it and shock it into action. >> So let's shift gears a little bit and start talking about the data and talk about the human factors. 'Cause you said, one of the challenges is people trying to bite off more than they can chew. And we have the role of chief data officer now. And to your point, maybe that mucks things up more than it helps. But in all the customer cases that you've worked on, is there a consistent kind of pattern of behavior, personality, types of projects that enables some people to grab those resources to apply to their data to have successful projects, because to your point there's too much data and there's too many projects and you talk a lot about prioritization. But there's a lot of assumptions in the prioritization model that you can, that you know a whole lot of things, especially if you're comparing project A over in group A with project B, with group B and the two may not really know the economics across that. But from an individual person who sees the potential, what advice do you give them? What kind of characteristics do you see, either in the type of the project, the type of the boss, the type of the individual that really lends itself to a higher probability of a successful outcome? >> So first off you need to find somebody who has a vision for how they want to use the data, and not just collect it. But how they're going to try to change the fortunes of the organization. So it always takes a visionary, may not be the CEO, might be somebody who's a head of marketing or the head of logistics, or it could be a CIO, it could be a chief data officer as well. But you've got to find somebody who says, "We have this latent asset we could be doing more with, and we have a series of organizational problem challenges against which I could apply this asset. And I need to be the matchmaker that brings these together." Now the tool that I think is the most powerful tool in marrying the latent capabilities of data with all the revenue generating opportunities in the application side, because there's a countless number, the most important tool that I found doing that is design thinking. Now, the reason why I think design thinking is so important, because one of the things that design thinking does a great job is it gives everybody a voice in the process of identifying, validating, valuing, and prioritizing use cases you're going to go after. Let me say that again. The challenge organizations have is identifying, validating, valuing, and prioritizing the use cases they want to go after. Design thinking is a marvelous tool for driving organizational alignment around where we're going to start and what's going to be next and why we're going to start there and how we're going to bring everybody together. Big data and data science projects don't die because of technology failure. Most of them die because of passive aggressive behaviors in the organization that you didn't bring everybody into the process. Everybody's voice didn't get a chance to be heard. And that one person who's voice didn't get a chance to get heard, they're going to get you. They may own a certain piece of data. They may own something, but they're just waiting and lay, they're just laying there waiting for their chance to come up and snag it. So what you got to do is you got to proactively bring these people together. We call this, this is part of our value engineering process. We have a value engineering process around envisioning where we bring all these people together. We help them to understand how data in itself is a latent asset, but how it can be used from an economics perspective, drive all those value. We get them all fired up on how these can solve any one of these use cases. But you got to start with one, and you've got to embrace this idea that I can build out my data and analytic capabilities, one use case at a time. And the first use case I go after and solve, makes my second one easier, makes my third one easier, right? It has this ability that when you start going use case by use case two really magical things happen. Number one, your marginal cost flatten. That is because you're building out your data lake one use case at a time, and you're bringing all the important data lake, that data lake one use case at a time. At some point in time, you've got most of the important data you need, and the ability that you don't need to add another data source. You got what you need, so your marginal costs start to flatten. And by the way, if you build your analytics as composable, reusable, continuous learning analytic assets, not as orphaned analytics, pretty soon you have all the analytics you need as well. So your marginal cost flatten, but effect number two is that you've, because you've have the data and the analytics, I can accelerate time to value, and I can de-risked projects as I go use case by use case. And so then the biggest challenge becomes not in the data and the analytics, it's getting the all the business stakeholders to agree on, here's a roadmap we're going to go after. This one's first, and this one is going first because it helps to drive the value of the second and third one. And then this one drives this, and you create a whole roadmap of rippling through of how the data and analytics are driving this value to across all these use cases at a marginal cost approaching zero. >> So should we have chief design thinking officers instead of chief data officers that really actually move the data process along? I mean, I first heard about design thinking years ago, actually interviewing Dan Gordon from Gordon Biersch, and they were, he had just hired a couple of Stanford grads, I think is where they pioneered it, and they were doing some work about introducing, I think it was a a new apple-based alcoholic beverage, apple cider, and they talked a lot about it. And it's pretty interesting, but I mean, are you seeing design thinking proliferate into the organizations that you work with? Either formally as design thinking or as some derivation of it that pulls some of those attributes that you highlighted that are so key to success? >> So I think we're seeing the birth of this new role that's marrying capabilities of design thinking with the capabilities of data and analytics. And they're calling this dude or dudette the chief innovation officer. Surprise. >> Title for someone we know. >> And I got to tell a little story. So I have a very experienced design thinker on my team. All of our data science projects have a design thinker on them. Every one of our data science projects has a design thinker, because the nature of how you build and successfully execute a data science project, models almost exactly how design thinking works. I've written several papers on it, and it's a marvelous way. Design thinking and data science are different sides of the same coin. But my respect for data science or for design thinking took a major shot in the arm, major boost when my design thinking person on my team, whose name is John Morley introduced me to a senior data scientist at Google. And I was bottom coffee. I said, "No," this is back in, before I even joined Hitachi Vantara, and I said, "So tell me the secret to Google's data science success? You guys are marvelous, you're doing things that no one else was even contemplating, and what's your key to success?" And he giggles and laughs and he goes, "Design thinking." I go, "What the hell is that? Design thinking, I've never even heard of the stupid thing before." He goes, "I'd make a deal with you, Friday afternoon let's pop over to Stanford's B school and I'll teach you about design thinking." So I went with him on a Friday to the d.school, Design School over at Stanford and I was blown away, not just in how design thinking was used to ideate and bring and to explore. But I was blown away about how powerful that concept is when you marry it with data science. What is data science in its simplest sense? Data science is about identifying the variables and metrics that might be better predictors of performance. It's that might phrase that's the real key. And who are the people who have the best insights into what values or metrics or KPIs you might want to test? It ain't the data scientists, it's the subject matter experts on the business side. And when you use design thinking to bring this subject matter experts with the data scientists together, all kinds of magic stuff happens. It's unbelievable how well it works. And all of our projects leverage design thinking. Our whole value engineering process is built around marrying design thinking with data science, around this prioritization, around these concepts of, all ideas are worthy of consideration and all voices need to be heard. And the idea how you embrace ambiguity and diversity of perspectives to drive innovation, it's marvelous. But I feel like I'm a lone voice out in the wilderness, crying out, "Yeah, Tesla gets it, Google gets it, Apple gets it, Facebook gets it." But you know, most other organizations in the world, they don't think like that. They think design thinking is this Wufoo thing. Oh yeah, you're going to bring people together and sing Kumbaya. It's like, "No, I'm not singing Kumbaya. I'm picking their brains because they're going to help make their data science team much more effective and knowing what problems we're going to go after and how I'm going to measure success and progress. >> Maybe that's the next Dean for the next 10 years, the Dean of design thinking instead of data science, and who knew they're one and the same? Well, Bill, that's a super insightful, I mean, it's so, is validated and supported by the trends that we see all over the place, just in terms of democratization, right? Democratization of the tools, more people having access to data, more opinions, more perspective, more people that have the ability to manipulate the data and basically experiment, does drive better business outcomes. And it's so consistent. >> If I could add one thing, Jeff, I think that what's really powerful about design thinking is when I think about what's happening with artificial intelligence or AI, there's all these conversations about, "Oh, AI is going to wipe out all these jobs. Is going to take all these jobs away." And what we're actually finding is that if we think about machine learning, driven by AI and human empowerment, driven by design thinking, we're seeing the opportunity to exploit these economies of learning at the front lines where every customer engagement, every operational execution is an opportunity to gather not only more data, but to gather more learnings, to empower the humans at the front lines of the organization to constantly be seeking, to try different things, to explore and to learn from each of these engagements. I think it's, AI to me is incredibly powerful. And I think about it as a source of driving more learning, a continuous learning and continuously adapting an organization where it's not just the machines that are doing this, but it's the humans who've been empowered to do that. And my chapter nine in my new book, Jeff, is all about team empowerment, because nothing you do with AI is going to matter of squat if you don't have empowered teams who know how to take and leverage that continuous learning opportunity at the front lines of customer and operational engagement. >> Bill, I couldn't set a better, I think we'll leave it there. That's a great close, when is the next book coming out? >> So today I do my second to last final review. Then it goes back to the editor and he does a review and we start looking at formatting. So I think we're probably four to six weeks out. >> Okay, well, thank you so much, congratulations on all the success. I just love how the Dean is really the Dean now, teaching all over the world, sharing the knowledge and attacking some of these big problems. And like all great economics problems, often the answer is not economics at all. It's completely really twist the lens and don't think of it in that, all that construct. >> Exactly. >> All right, Bill. Thanks again and have a great week. >> Thanks, Jeff. >> All right. He's Bill Schmarzo, I'm Jeff Frick. You're watching theCUBE. Thanks for watching, we'll see you next time. (gentle music)