(bright upbeat music) >> Welcome to theCUBE's continuous coverage of "AWS re:Invent 2021". I'm Dave Nicholson, and here at theCUBE, we're running one of the most important largest events in tech industry history with two live sets right here, live in Las Vegas, along with our two studios. And I'm delighted here in our studio to welcome Scott Warren US AWS practice, vice president for Capgemini. Welcome. >> Thank you. >> Dave: How's the show been going for you so far? >> Very, very good so far. It's great to be back in person. >> So tell me about your role at Capgemini. What you focus on. You're responsible for the relationship with AWS? >> Absolutely. So managing the relationship with AWS and how we partner, and then probably more importantly, kind of how we go to market with the AWS offering for our customers. So kind of understanding what the customer demand is, how we can help accelerate and get them moving faster out to the cloud, and then building that up as well as kind of industry specific offers on how we can accelerate cloud adoption. >> So when you talk about acceleration often in an organization like yours, there is the tug of war between the spoke solution hearing and pre-packaged things that serve to be accelerators. How do you go about balancing those things and tell us about some of the accelerators that you've developed? >> Absolutely. I think it's always kind of going to be a hybrid between the bespoken out of the box solutions. The out of the box solutions are inevitably always going to take some sort of customization or something like that to make them applicable within a customer's environment. But we all know it's very time consuming and expensive to build something completely bespoke from the ground up. So the way we really address that is we've built something at Capgemini we called it the cloud boost library. It is an online get lab library of thousands of code templates, infrastructure as code snippets that solve deploying your infrastructure and provision your infrastructure on the cloud, microservice design for healthcare and financial services and manufacturing and automotive. >> So industry specific? >> Not just specific and cloud in general. And so we bring that to every cloud engagement we work on. It's our real motto around that is we should never be starting on zero, starting from ground zero and anything we push out to AWS and we can always borrow, steal, modify, and change part of that library specific to that customer demand and need, and really speed up the implementation and get them out to AWS faster. >> Can you kind of double click on that? Give us an example of an accelerator inaction. You don't have to necessarily, if you've got a customer name, fantastic, or you can keep it generic. >> Yeah, absolutely. So we work for a big financial services company that's doing kind of an online data dissemination system, so thousands of public API is to disseminate data out to their customers and partners and vendors and things like that. So we were able to use that library to kind of get the framework for every single one of those APIs. A template, a kind of base function for that, and then use that kind of repeatably across those thousands of API. So we never really started from zero and said, provided 70, 80% kind of efficiency gain on that project versus kind of building it from the ground up. >> So with a customer like that, how did the initial engagement start? Was this a preexisting Capgemini relationship? Was this AWS at the table strategizing bringing in Capgemini. How does that work with your relationships with customers? >> So this was an existing customer of ours that we'd been doing application management in their data center for years. And several years ago, they had a kind of a leadership change happened and a new CTO came in and he laid down the edict that they're now a cloud first organization. So of course all his direct reports and managers started asking, what does that really mean? And they came to us as a trusted partner. And so we started walking them through our framework and template of how we bring our customers from ground zero completely in the data center, completely to a cloud first organization. And at that same time, we also began engaging our counterparts at AWS because we want to make sure we're in lockstep with what they're doing at AWS and kind of one consistent message out to our customer and doing the things the way they want them to be done. We want to unlock the funding programs available from AWS to incentivize that customer, to move out to the cloud. And then really having that kind of three legged partnership with us, the customer and AWS, puts them on the right path for success and in faster adoption of the cloud. >> Capgemini didn't just roll out of college a couple of years ago. (laughs) >> Been around a while. Been around a while. >> So you have an interesting perspective because you just mentioned being involved in the management of a customer's environment and IT landscape that is outside the purview of cloud, at least at some stage of the game. How do you turn being a legacy provider of services into a superpower instead of a liability? >> Absolutely. Yeah. >> How do you do that? And the reason why I say that superpower is because you said cap earlier and I thought in America, but it's a serious question. Some would say, well, Capgemini legacy. No, no, no. What's your reply? >> Absolutely. So what we found is the most important thing about a move to the cloud is understanding the entire application portfolio and landscape and the best way to move into the cloud. Some applications that are very prime for lift and shift. We just want to get them out of the data center, into the cloud very quickly. Other ones that are very mission critical on customer facing very important for the future of an organization. Really need to be looked at with a more modern lens in the clouds. How do we modernize this, make it cost effective, and in a long-term asset, that's going to run in the cloud in a PaaS or SaaS based service offering rather than just IaaS. So all of the legacy work under the previous work we've done for our customers, we understand their application and in data center landscape better, they do in most scenarios. So having all of that data allows us to feed that into kind of some of our tooling around assessing applications and figuring out the best migration path or modernization path. So all of that legacy knowledge kind of puts us in the driver's seat for being the best partner to actually help them with that cloud modernization. >> So with your AWS responsibility as part of Capgemini, it's a bit like having a foot on the dock and a foot on the boat? >> Scott: Yep. >> In terms of an individual customer's requirements, obviously Capgemini can continue to manage what we would refer to as legacy infrastructure while helping to modernize and migrate to cloud. What about this sort of combination of the two that represents the future specifically, AWS is support of hybrid cloud technology. The idea of Outposts, is that something that you are involved with? >> Absolutely. We're seeing kind of Outpost adoption trend up recently, actually. So when we see in certain sectors where a lot of kind of work is being done on the edge, a great example is an agriculture company we work for that has field in soil and weather sensors all over the planet. So monitoring the moisture in the soil, the nitrogen levels, the wind air pressure and temperature and humidity. And oftentimes those fields are in very remote disconnected locations. So we're seeing things like Outpost and snowball edge and different services like that become more and more prevalent for those edge use cases where compute can actually be done on the field and decisions can be made by the farmers that are planters in the field like real time. And then when connectivity comes back around, they can actually beam that back to AWS if necessary. The other kind of scenario we see Outposts really being prevalent is in very sensitive data scenarios. So we have customers in federal government work or things like that. There's just some data due to regulatory compliance that cannot be on the public cloud node yet, yet being the key word there. So Outposts becomes really important in those scenarios where the vast majority of the data and the assets go out to AWS, but the very, very sensitive data due to regulatory reasons, we keep in the Outpost can still kind of harness the power of AWS on that. >> You know, that brings up another interesting subject, the difference between where technology actually exists today and where people exist culturally today in terms of their acceptance and adoption of technology. There are absolutely cases where data residency, data governance requires that it be onsite. >> Scott: Absolutely. >> Then again, there are a lot of cases where people are just concerned about not having their arms around the data. So the perception that it isn't as safe in the cloud, as it is in the customer's data center is often a misguided, >> Scott: Very much so. >> Perception. So that's obviously an inhibiting factor to cloud adoption in some way. What are some of the other things that you see that are headwinds? Because it's been talked about widely here 80% or more of IT spend is still what we would think of as on-premises. >> Scott: Data center. Yeah. >> Not cloud. Those lines are being blurred with things like Outpost. I contend that in five years, when we talk about cloud, that's going to be sort of an irrelevant term. >> Yeah. >> It's really like, well, because it doesn't matter where it is. It's all virtualized. >> Compute and storage somewhere. Yeah. >> The headwinds that you're seeing. And again, they can be irrational headwinds or they can be technical bottlenecks. >> Yeah. I think the biggest one is business understanding what the cloud is and them adopting it. I've had a couple meetings that were a new thing for me this week, where I met with the chief marketing officer for one of our customers. So we're meeting with CTO, CIO, VPs, directors in the IT space, but this marketing officer wanted to meet with us. And she was kind of very cloud knowledgeable. She understood IaaS, SaaS, PaaS and the costing models of cloud consumption and some of the services. In her organization is kind of already all in on AWS. And she had seen this happen, this transformation happened on the IT side. And she wanted to know how can I, as the head of my marketing department start to harness the power of the public cloud to drive business outcomes within my area. And that was a really interesting conversation for me and kind of got me thinking that I think the business is going to start understanding, and that the lines between IT and business are going to begin to get blurred a little bit with the power of AWS and other hyperscalers and all the capability that's available to our customers once they get moved out there. >> In today's keynote, Swami talked a lot about data and the data-driven companies, or rather companies that are not data-driven. >> Yep. >> Are going to be left behind. And I thought it was interesting in the survey. He mentioned 9% of companies reported not looking at data at all for their decision-making process. We need a list of those companies so we can short their stocks. (laughs) And we can help them out. (laughs) Or you can help out, or you can help them out. Exactly. I'll refer a half to you, and I'll short the rest. How's that feel? Is that a deal? So within your world of things you do with AWS, with Capgemini on behalf of the customers, what are some of the tip of the spear things that are the most exciting from a buzz perspective and what are sort of the next gen things that you're thinking of? It could be something you literally just heard about announced over the last couple of days. What does the future hold? >> Absolutely. We kind of look at that is what we classify our intelligent industry offering. And so it's really industry specific offers and services that are going to kind of change how specific industries do business. A really good example is we do a lot with the automotive industry. We started working with the OEMs that are kind of producing electric vehicles and autonomous driving vehicles. And we've actually built a framework that lives on top of AWS called connected mobility solutions. So connecting all of the driverless functions of a car back to the mothership or the cloud, the cloud instance. And I think things like that are really kind of tip of the spear where it's, again, out on the edge, not in a data center or in a cloud, but gathering all that data from connected devices in different areas and kind of how we're going to manage that and enable that and make it secure and safe and reliable and things like that. >> Yeah. Yeah. I have direct experience with some of that. I have a car that won't allow me to access all of its self-driving features. I bet I can guess because of the way I drive. (laughs) Yep. The cloud is not all wonderful. It's not all lollipops and rainbows. There is a bit of a downside to it if you're a crazy maniac like myself. So Capgemini, hasn't just been a standalone organization. You've absorbed and merged with all sorts of different organizations. I imagine you have organizations that are specifically focused on AWS in addition to other clouds. >> Scott: Absolutely. I can manage that culturally. >> That's a good question. So three years ago, me as the Capgemini group as a whole entered into a three-year partnership called Project Liberty with AWS. And it was a three-year plan we had targets and numbers on both sides, but it really kind of unified how we were going to do AWS and cloud work across the Capgemini organization, all working under one program towards one common goal, on developing accelerators and solutions and go to market offerings, kind of with one thing in mind to drive that AWS partnership and growth. So that's really been kind of the big driver for us within Capgemini over the past three years, is that what we call Project Liberty internally. And then just recently about a year and a half, maybe two years ago, we acquired one of the world's leading digital engineering firms called Altron. Big presence in Europe, Southeast Asia and North America. And they brought kind of a whole new flavor of how we do cloud when we're talking about digital twin in the cloud, on the factory floor and actually engineering of products and in driverless vehicles and electric vehicles and things like that. So bringing all training and being able to include them in our overall kind of cloud AWS message and bringing their book of offers in has really expanded our offering as well. >> How has talent recruitment and acquisition been for you guys? Are you faced with the same challenges that others are? Which is we need educated people. Give the pitch, so my kids hear it. So they understand. The graduate was plastics, right? That's the future? >> Yeah. >> Cloud services, without Capgemini, all the technology that AWS produces is essentially worthless. If you can't connect it to business value and outcome, and that's what you do. So how has that looked for you? >> Yeah, we hae the same talent challenges as everyone right now. So we're really taking the thought process of let's take people who aren't traditionally in the technology field and begin training them up on the cloud and the different technology areas. >> You do that at Capgemini? >> We do that at Capgemini, yeah. So we're running in conjunction with AWS big boot camps where we bring people in and- >> Who are this people? Not to interrupt, just a few seconds left. What's the profile of somewhere? >> Yeah. So a lot of- >> I want to hear the unconventional ones, not the computer science person who doesn't know cloud. Who are you bringing in on this one? >> New college hires who majored in the non-related IT field completely psychology, social sciences, whatever it may be. But who had the aptitude and then kind of the one to learn cloud in IT. So we bring them in. And then looking in our Capgemini Organization internally at our recruiting organization, our marketing organization, our partnership organization, and some of those people who are early on in their careers and may want to pivot to the technology side. We're starting to ramp them up as well. So it's been a very effective program for us. And I think something we're going to continue to invest in further. >> That's a very satisfying part of what you do to be a part of. >> Absolutely. >> Well, Scott, I got to tell you it's been a great conversation. For the rest of us here at theCUBE our continuous coverage continues here at AWS re:Invent 2021. I'm Dave Nicholson signing off for a moment. But keep it right here theCUBE is your technology hybrid event leader. (upbeat music)

(upbeat music) >> We're back at AWS reinvent 2021. You're watching The Cube, I'm Dave Vellante with my co-host Dave Nicholson. David Nicholson, I'm Dave he's David. >> We're trying something new here at the cube. A little stand up cube. You've heard of the pop-up cube, maybe. We're going to stand up. I work at a stand, standing desk at my office, so let's try it. Four days, two sets, a hundred plus guests. Why not? So Manish Sood is here, he's the founder and CTO of Reltio, Cube alum. >> Dave: Manish, thank you for standing and good to see you again. >> Dave, It's great to see you again, and David, thank you for having me here. >> So, tell us a little bit about your, yourself, your background. I'm always interested to ask founders why you started your company, but tell us the background. >> Yeah, so a little bit of my background and the company's history. I, most of my background has been in data management and creating products for data management. I was at a company called Informatica, came through an acquisition through Informatica, back in 2010. And Started Reltio in 2011. The reason why we started Reltio was that, if you look at the enterprise space and how things have been evolving, there have been an explosion of applications. There's almost an application for every little business process that you can possibly imagine. Enterprise customers who used to struggle with 12 or 24 different systems, are now coming to us and saying they have 300 or 500 different applications that they use to run their business. And that's at the lower end of the spectrum. Even a business like Reltio today, runs on a hundred plus SAAS applications, end to end. And that it is creating one of the biggest opportunities, as well as one of the biggest friction points in the enterprise. Because in order to create better, efficient business outcomes, you have silos of data and you don't know where the source of truth is. And that is something that we saw early on in 2011. At the same time, we also saw that digital transformation or cloud transformation type of requirements, were going to drive a larger need for this kind of capability, where Reltio type of products could act as that single source of truth to unify all of the multi-source siloed information. So, that's what got us started down this journey. >> So, okay. So, when see people hear single source of truth, they think, oh, database, right? But that's not what you guys do, right? I mean, it's, it's, can I call it master data management? But it's really modern master data management. You're kind of recreating a new or creating a new category that- >> Manish: A little bit. >> solves a similar problem. Maybe you could explain that. >> Yeah. A little bit of background. So the term master data management came about the 1920s. (Dave laughing) You believe that? When during the pandemic, the U.S. government was trying to figure out how to know who is still alive versus, you know, not there anymore. And they created something called the death master. Now a very ominous name, for a concept of just bringing data together and figuring out what's going on in the economy, but that need, or problem hasn't gone away. It has just become a harder problem to solve because now we have so many different systems, to deal with. And both internal as well as third-party data sources that companies have to work with. And that's where the need has been around, but the technical capabilities to really keep solving the problem and delivering the solution in a manner where it can keep pace with the evolving needs, that capability has been missing. And that's where the "aha" moment for us was that we really needed to build it out as a foundation that would continue to grow and scale, with the magnitude of the problem that we were going to see in the future. >> Okay, so this idea of single version of the truth, obviously critically important for reporting, financials, you can't, you can't tell an auditor one thing, you know, your, your customers are another thing, your consumers, it's got to be consistent. And especially in regulated industries. Is there a difference Manish, between sort of that type of data and the data maybe that's in the line of business that doesn't necessarily affect the rest of the business? Can they have their own version of the truth, which is just their version, their, their, their single version? It doesn't necessarily have to affect anything else. Do you, are you seeing that changing data landscape, where things are getting more distributed and ownership is becoming more distributed? >> So, the change in the paradigm that we are seeing is because of the proliferation of the data, there is a need to establish, what is the aggregated view of the information. Aggregated and unified, which means that, you know, if there is a record for Dave Vellante or David Vellante. It's the same person. Establishing that fact as the truth across any number of systems that you have, versus the multiple versions of the truth, where somebody comes in and says, for compliance reasons, I want the entire collection of data versus for marketing reasons, I only want one third the slice of this information. So that's where this concept of aggregate once, unify that information, but then make it ready and available for multiple consumers to partake from that. That's becoming the norm. >> Dave: Got it. >> And you mentioned something, Dave, that analytics, reporting, BI, data science, those have been some of the traditional playgrounds for this kind of information to be unified, because if you're trying to roll up the revenue for, you know, the business that you do with Coke or Coca-Cola, you know, you don't know which name you used, then you have to go back to the analytics warehouse and aggregate all of that information and do the reporting. But the same problem is coming up in real time, digital experiences as well. The only difference is, that instead of having the luxury of a few hours, now you have to make the decision in a few milliseconds. >> So, when you talk about those silos of data and seeking to have a unification of those silos, how has that changed in the era of cloud? Is it that Reltio is integrating those disparate sources that now exist in cloud, or is it that you are leveraging cloud to address the problem that's been with us for a long time? And I have to say that Dave Vellante, take him off the the death master. He's definitely still with us. (Manish and Dave laugh) >> Dave: Another good day. >> I'm pretty sure too. But how, how, how has, how have things changed as you know, with, with the dawn of cloud? >> With the dawn of cloud, there are two things that have become available to us. One is using the power of the cloud compute to solve the problem, so that you can keep growing with the footprint of the problem itself and have a solution that scales along with it. But at the same time, you have systems of record, could be your mainframe systems, could be your SAP, ERP type of deployments that you have. Some of those functional applications, they're not going away anytime soon, they're there to stay. But at the same time, you also need the new digital experiences to be delivered on. The glue between those two worlds is the source of truth data that sits in the middle and the best place for it to sit is the cloud, because you have to open it up to the rest of the ecosystem that sits in the cloud, but you also have to maintain a connection to the on the ground type of systems. Putting it behind the firewall and trying to do that is next to impossible, but doing it in the cloud opens up all the doors that you need for your transformation to take place. >> You know Dave, there was a time when I was part of an industry where coding, not writing code, but coding data to basically say, look, this field here is the person's last name. This field is the address where the mortgage is being held. How much of that is still manual, as opposed to applying some form of AI to the problem? Let's say you have 200 different sources of information, where Dave Vellante's name shows up in a variety of contexts. Are we still having to go in manually and sift through to make those correlations? How much of that has been automated at this point? >> So, there are systems of capture where some of that information, because your loan mortgage application was entered by somebody into a system, will still be captured in those places, but we'll take in that information. That's the starting point, but if there are other sources, then we will apply AIML type of capabilities to bring on those new emerging sources. Because at the same time, think about this equation where, you started with five systems or, you know, a dozen systems. Now you're talking about 300 plus systems. You cannot keep doing this manually for every system possible. And this number is only going to grow as we move forward. So AIML definitely has a role to play and further automate this landscape. >> I had to, I saw an amazing stat the other day, the source was the Sand Hill Econometrics, you know, a Silicon valley company. And the stat was that 70% of the series, A, B and C companies, fail to return at least one X to their investors. So you've made it through that nut hole. Congratulations you just raised $120 million dollar round. That's got to be super exciting for you. >> David: No pressure by the way. >> Dave: Tell us about that. Well, I mean, you'd think the industry would have de-risked by now, right. But anyway, so, tell us about that raise. Where are you, where are you guys are at? Very exciting times for you. >> Yeah, really, really exciting time for us. We just raised $120 million dollars. The company was valued at $1.7 billion dollars. >> Dave: Awesome. Congratulations. >> And the round was, you know, all of our existing investors participated in it. We also had a new investor join in the process, as well. >> Dave: They wanted their pro-rata. (Dave and Manish laugh) >> Everybody, everybody wanted their pro-rata. >> Dave: That's great. >> But you know, one of the things that we have been very careful about in this whole process and journey, is something that you and I were talking about, the step function of scale. We're making sure that we are efficient stewards of capital and applying it in a manner where we are at every turn, looking at what's the next step function that we need to graduate to, because we want to make use of this capital to efficiently grow our business and be a Rule of 40 growth company. And that's something that you don't typically hear these days from a lot of the growth companies, but we are certainly focused on building long-term value and focusing on that Rule of 40 growth efficiency. >> Yeah, so Rule of 40 is growth plus EBITDA, or sometimes they use other metrics, but is that how you look at it? Growth plus EBITDA. >> Yes. Yeah. >> Great. >> And that's the formula that we are driving for. And most of our investments with this round of capital are going to be not only pushing forward with the go-to market strategy, because we have a lot of growth opportunity, we have been North America focused, now we can take this global. At the same time, looking at the verticals where we need to double down and invest more, given that we have been a horizontal platform that is core to our capabilities, that we have built with Reltio. But at the same time, making sure that we are investing in the key verticals that we are present in. >> Yeah. So, you were explaining to me that you, you started in the pharmaceutical industry, that's where you got go to market fit. And then you went to other industries. When you went to those other industries where they're similar patterns, or do you do almost have to start from ground zero again, to get that product market fit? >> No. So from the very beginning, the concept has been that this is a horizontal data problem. And at the heart of it, it's information about people, organizations, product, locations, and most of the businesses run on that type of information. That's the core part of the data that they build their business on. Life sciences was a perfect starting point for us, because it had examples of all of those data. When you start with commercial operations, which is sales and marketing, you have people, organization, product type of information. When you go into clinical trials, you have site investigators and patient type of information. When you go into R and D within that same space, you have drugs, compounds, substances, finished products, type of information, all coming from multiple sources. So it was a perfect place for us to prove out, all of the capabilities end to end, which we like to call multi-domain capabilities. And then we looked at what other verticals have similar patterns. And that's why we went after healthcare, financial services, insurance, retail, high tech. Those are some of the key verticals that we are in right now. >> That's awesome. Great vision. Last question, could you give us a sense of the futures, where you're going? Well, first of all, what are you doing with the money? Is it, you go to market, throwing gas on the fire? And what can we expect in the coming year and years? >> Go to market expansion is a key area of investment, but also doubling down on the customer experience that we deliver, how we invest in the product, what are some of the adjacent capabilities that we need to invest in? Because you know, data is a great starting point and data should not hold businesses back. Data should be the accelerant to the business. And that's our philosophy, that we are trying to bring to life. So making sure that we are making the data, readily available, accessible and usable for all of our customers is the key goal to aim for. And that's where all the investment is going. >> Well, Manish was a pleasure having you on at the AWS startup showcase, and then subsequently you become a unicorn. So congratulations on that. Really excited to watch the continued progress. Thanks for coming back in The Cube. >> Well, thank you so much, Dave and David, thanks for having me. >> David: Thanks for validating that Mr. Vellante is still with us. >> (laughs) He's going to be with us for a long time. >> I hope so, I hope so, I got, I got one more to put through college. Thank you for watching this edition of The Cube, at AWS reinvent. I'm Dave Vellante, for Dave Nicholson. We are The Cube, the leader in high-tech coverage, Be right back. (somber music)

from the cube studios in palo alto in boston bringing you data-driven insights from the cube and etr this is breaking analysis with dave vellante nvidia wants to completely transform enterprise computing by making data centers run 10x faster at one tenth the cost and video's ceo jensen wang is crafting a strategy to re-architect today's on-prem data centers public clouds and edge computing installations with a vision that leverages the company's strong position in ai architectures the keys to this end-to-end strategy include a clarity of vision massive chip design skills a new arm-based architecture approach that integrates memory processors i o and networking and a compelling software consumption model even if nvidia is unsuccessful at acquiring arm we believe it will still be able to execute on this strategy by actively participating in the arm ecosystem however if its attempts to acquire arm are successful we believe it will transform nvidia from the world's most valuable chip company into the world's most valuable supplier of integrated computing architectures hello everyone and welcome to this week's wikibon cube insights powered by etr in this breaking analysis we'll explain why we believe nvidia is in the right position to power the world's computing centers and how it plans to disrupt the grip that x86 architectures have had on the data center for decades the data center market is in transition like the universe the cloud is expanding at an accelerated pace no longer is the cloud an opaque set of remote services i always say somewhere out there sitting in a mega data center no rather the cloud is extending to on-premises data centers data centers are moving into the cloud and they're connecting through adjacent locations that create hybrid interactions clouds are being meshed together across regions and eventually will stretch to the far edge this new definition or view of cloud will be hyper distributed and run by software kubernetes is changing the world of software development and enabling workloads to run anywhere open apis external applications expanding the digital supply chains and this expanding cloud they all increase the threat surface and vulnerability to the most sensitive information that resides within the data center and around the world zero trust has become a mandate we're also seeing ai being injected into every application and it's the technology area that we see with the most momentum coming out of the pandemic this new world will not be powered by general purpose x86 processors rather it will be supported by an ecosystem of arm-based providers in our opinion that are affecting an unprecedented increase in processor performance as we have been reporting and nvidia in our view is sitting in the poll position and is currently the favorite to dominate the next era of computing architecture for global data centers public clouds as well as the near and far edge let's talk about jensen wang's clarity of vision for this new world here's a chart that underscores some of the fundamental assumptions that he's leveraging to expand his market the first is that there's a lot of waste in the data center he claims that only half of the cpu cores deployed in the data center today actually support applications the other half are processing the infrastructure all around the applications that run the software defined data center and they're terribly under utilized nvidia's blue field three dpu the data processing unit was described in a blog post on siliconangle by analyst zias caravala as a complete mini server on a card i like that with software defined networking storage and security acceleration built in this product has the bandwidth and according to nvidia can replace 300 general purpose x86 cores jensen believes that every network chip will be intelligent programmable and capable of this type of acceleration to offload conventional cpus he believes that every server node will have this capability and enable every packed of every packet and every application to be monitored in real time all the time for intrusion and as servers move to the edge bluefield will be included as a core component in his view and this last statement by jensen is critical in our opinion he says ai is the most powerful force of our time whether you agree with that or not it's relevant because ai is everywhere an invidious position in ai and the architectures the company is building are the fundamental linchpin of its data center enterprise strategy so let's take a look at some etr spending data to see where ai fits on the priority list here's a set of data in a view that we often like to share the horizontal axis is market share or pervasiveness in the etr data but we want to call your attention to the vertical axis that's really really what really we want to pay attention today that's net score or spending momentum exiting the pandemic we've seen ai capture the number one position in the last two surveys and we think this dynamic will continue for quite some time as ai becomes the staple of digital transformations and automations an ai will be infused in every single dot you see on this chart nvidia's architectures it just so happens are tailor made for ai workloads and that is how it will enter these markets let's quantify what that means and lay out our view of how nvidia with the help of arm will go after the enterprise market here's some data from wikibon research that depicts the percent of worldwide spending on server infrastructure by workload type here are the key points first the market last year was around 78 billion dollars worldwide and is expected to approach 115 billion by the end of the decade this might even be a conservative figure and we've split the market into three broad workload categories the blue is ai and other related applications what david floyer calls matrix workloads the orange is general purpose think things like erp supply chain hcm collaboration basically oracle saps and microsoft work that's being supported today and of course many other software providers and the gray that's the area that jensen was referring to is about being wasted the offload work for networking and storage and all the software defined management in the data centers around the world okay you can see the squeeze that we think compute infrastructure is gonna gonna occur around that orange area that general-purpose workloads that we think is going to really get squeezed in the next several years on a percentage basis and on an absolute basis it's really not growing nearly as fast as the other two and video with arm in our view is well positioned to attack that blue area and the gray area those those workload offsets and the new emerging ai applications but even the orange as we've reported is under pressure as for example companies like aws and oracle they use arm-based designs to service general purpose workloads why are they doing that cost is the reason because x86 generally and intel specifically are not delivering the price performance and efficiency required to keep up with the demands to reduce data center costs and if intel doesn't respond which we believe it will but if it doesn't act arm we think will get 50 percent of the general purpose workloads by the end of the decade and with nvidia it will dominate the blue the ai and the gray the offload work when we say dominate we're talking like capture 90 percent of the available market if intel doesn't respond now intel they're not just going to sit back and let that happen pat gelsinger is well aware of this in moving intel to a new strategy but nvidia and arm are way ahead in the game in our view and as we've reported this is going to be a real challenge for intel to catch up now let's take a quick look at what nvidia is doing with relevant parts of its pretty massive portfolio here's a slide that shows nvidia's three chip strategy the company is shifting to arm-based architectures which we'll describe in more detail in a moment the slide shows at the top line nvidia's ampere architecture not to be confused with the company ampere computing nvidia is taking a gpu centric approach no surprise obvious reasons there that's their sort of stronghold but we think over time it may rethink this a little bit and lean more into npus the neural processing unit we look at what apple's doing what tesla are doing we see opportunities for companies like nvidia to really sort of go after that but we'll save that for another day nvidia has announced its grace cpu a nod to the famous computer scientist grace hopper grace is a new architecture that doesn't rely on x86 and much more efficiently uses memory resources we'll again describe this in more detail later and the bottom line there that roadmap line shows the bluefield dpu which we described is essentially a complete server on a card in this approach using arm will reduce the elapsed time to go from chip design to production by 50 we're talking about shaving years down to 18 months or less we don't have time to do a deep dive into nvidia's portfolio it's large but we want to share some things that we think are important and this next graphic is one of them this shows some of the details of nvidia's jetson architecture which is designed to accelerate those ai plus workloads that we showed earlier and the reason is that this is important in our view is because the same software supports from small to very large including edge systems and we think this type of architecture is very well suited for ai inference at the edge as well as core data center applications that use ai and as we've said before a lot of the action in ai is going to happen at the edge so this is a good example of leveraging an architecture across a wide spectrum of performance and cost now we want to take a moment to explain why the moved arm-based architectures is so critical to nvidia one of the biggest cost challenges for nvidia today is keeping the gpu utilized typical utilization of gpu is well below 20 percent here's why the left hand side of this chart shows essentially racks if you will of traditional compute and the bottlenecks that nvidia faces the processor and dram they're tied together in separate blocks imagine there are thousands thousands of cores in a rack and every time you need data that lives in another processor you have to send a request and go retrieve it it's very overhead intensive now technologies like rocky are designed to help but it doesn't solve the fundamental architectural bottleneck every gpu shown here also has its own dram and it has to communicate with the processors to get the data i.e they can't communicate with each other efficiently now the right hand side side shows where nvidia is headed start in the middle with system on chip socs cpus are packaged in with npus ipu's that's the image processing unit you know x dot dot dot x pu's the the alternative processors they're all connected with sram which is think of that as a high speed layer like an layer one cache the os for the system on a chip lives inside of this and that's where nvidia has this killer software model what they're doing is they're licensing the consumption of the operating system that's running this system on chip in this entire system and they're affecting a new and really compelling subscription model you know maybe they should just give away the chips and charge for the software like a razer blade model talk about disruptive now the outer layer is the the dpu and the shared dram and other resources like the ampere computing the company this time cpus ssds and other resources these are the processors that will manage the socs together this design is based on nvidia's three chip approach using bluefield dpu leveraging melanox that's the networking component the network enables shared dram across the cpus which will eventually be all arm based grace lives inside the system on a chip and also on the outside layers and of course the gpu lives inside the soc in a scaled-down version like for instance a rendering gpu and we show some gpus on the outer layer as well for ai workloads at least in the near term you know eventually we think they may reside solely in the system on chip but only time will tell okay so you as you can see nvidia is making some serious moves and by teaming up with arm and leaning into the arm ecosystem it plans to take the company to its next level so let's talk about how we think competition for the next era of compute stacks up here's that same xy graph that we love to show market share or pervasiveness on the horizontal tracking against next net score on the vertical net score again is spending velocity and we've cut the etr data to capture players that are that are big in compute and storage and networking we've plugged in a couple of the cloud players these are the guys that we feel are vying for data center leadership around compute aws is a very strong position we believe that more than half of its revenues comes from compute you know ec2 we're talking about more than 25 billion on a run rate basis that's huge the company designs its own silicon graviton 2 etc and is working with isvs to run general purpose workloads on arm-based graviton chips microsoft and google they're going to follow suit they're big consumers of compute they sell a lot but microsoft in particular you know they're likely to continue to work with oem partners to attack that on-prem data center opportunity but it's really intel that's the provider of compute to the likes of hpe and dell and cisco and the odms which are the odms are not shown here now hpe let's talk about them for a second they have architectures and i hate to bring it up but remember the machine i know it's the butt of many jokes especially from competitors it had been you know frankly hpe and hp they deserve some of that heat for all the fanfare and then that they they put out there and then quietly you know pulled the machine or put it out the pasture but hpe has a strong position in high performance computing and the work that it did on new computing architectures with the machine and shared memories that might be still kicking around somewhere inside of hp and could come in handy for some day in the future so hpe has some chops there plus hpe has been known hp historically has been known to design its own custom silicon so i would not count them out as an innovator in this race cisco is interesting because it not only has custom silicon designs but its entry into the compute business with ucs a decade ago was notable and they created a new way to think about integrating resources particularly compute and networking with partnerships to add in the storage piece initially it was within within emc prior to the dell acquisition but you know it continues with netapp and pure and others cisco invests they spend money investing in architectures and we expect the next generation of ucs oh ucs2 ucs 2.0 will mark another notable milestone in the company's data center business dell just had an amazing quarterly earnings report the company grew top line revenue by around 12 percent and it wasn't because of an easy compare to last year dells is simply executing despite continued softness in the legacy emc storage business laptop the laptop demand continued to soar in dell server business it's growing again but we don't see dell as an architectural innovator per se in compute rather we think the company will be content to partner with suppliers whether it's intel nvidia arm-based partners or all of the above dell we think will rely on its massive portfolio its excellent supply chain and execution ethos to compete now ibm is notable for historical reasons with its mainframe ibm created the first great compute monopoly before it unwind and wittingly handed it to intel along with microsoft we don't see ibm necessarily aspiring to retake that compute platform mantle that once once held with mainframes rather red hat in the march to hybrid cloud is the path that we think in our view is ibm's approach now let's get down to the elephants in the room intel nvidia and china inc china is of course relevant because of companies like alibaba and huawei and the chinese chinese government's desire to be self-sufficient in semiconductor technology and technology generally but our premise here is that the trends are favoring nvidia over intel in this picture because nvidia is making moves to further position itself for new workloads in the data center and compete for intel's stronghold intel is going to attempt to remake itself but it should have been doing this seven years ago what pat gelsinger is doing today intel is simply far behind and it's going to take at least a couple years for them to really start to to make inroads in this new model let's stay on the nvidia v intel comparison for a moment and take a snapshot of the two companies here's a quick chart that we put together with some basic kpis some of these figures are approximations or they're rounded so don't stress over it too much but you can see intel is an 80 billion dollar company 4x the size of nvidia but nvidia's market cap far exceeds that of intel why is that of course growth in our view it's justified due to that growth and nvidia's strategic positioning intel used to be the gross margin king but nvidia has much higher gross margins interesting now when it comes down to free cash flow intel is still dominant as it pertains to the balance sheet intel is way more capital intensive than nvidia and as it starts to build out its foundries that's going to eat into intel's cash position now what we did is we put together a little pro forma on the third column of nvidia plus arm circa let's say the end of 2022. we think they could get to a run rate that is about half the size of intel and that can propel the company's market cap to well over half a trillion dollars if they get any credit for arm they're paying 40 billion dollars for arm a company that's you know sub 2 billion the risk is that because of the arm because the arm deal is based on cash plus tons of stock it could put pressure on the market capitalization for some time arm has 90 percent gross margins because it pretty much has a pure license model so it helps the gross margin line a little bit for this in this pro forma and the balance sheet is a swag arm has said that it's not going to take on debt to do the transaction but we haven't had time to really dig into that and figure out how they're going to structure it so we took a took a swag in in what we would do with this low interest rate environment but but take that with a grain of salt we'll do more research in there the point is given the momentum and growth of nvidia its strategic position in ai is in its deep engineering they're aimed at all the right places and its potential to unlock huge value with arm on paper it looks like the horse to beat if it can execute all right let's wrap up here's a summary look the architectures on which nvidia is building its dominant ai business are evolving and nvidia is well positioned to drive a truck right to the enterprise in our view the power has shifted from intel to the arm ecosystem and nvidia is leaning in big time whereas intel it has to preserve its current business while recreating itself at the same time this is going to take a couple of years but intel potentially has the powerful backing of the us government too strategic to fail the wild card is will nvidia be successful in acquiring arm certain factions in the uk and eu are fighting the deal because they don't want the u.s dictating to whom arm can sell its technology for example the restrictions placed on huawei for many suppliers of arm-based chips based on u.s sanctions nvidia's competitors like broadcom qualcomm at all are nervous that if nvidia gets armed they will be at a competitive disadvantage they being invidious competitors and for sure china doesn't want nvidia controlling arm for obvious reasons and it will do what it can to block the deal and or put handcuffs on how business can be done in china we can see a scenario where the u.s government pressures the uk and eu regulators to let this deal go through look ai and semiconductors you can't get much more strategic than that for the u.s military and the u.s long-term competitiveness in exchange for maybe facilitating the deal the government pressures nvidia to guarantee some feed to the intel foundry business while at the same time imposing conditions that secure access to arm-based technology for nvidia's competitors and maybe as we've talked about before having them funnel business to intel's foundry actually we've talked about the us government enticing apple to do so but it could also entice nvidia's competitors to do so propping up intel's foundry business which is clearly starting from ground zero and is going to need help outside of intel's own semiconductor manufacturing internally look we don't have any inside information as to what's happening behind the scenes with the us government and so forth but on its earning call on its earnings call nvidia said they're working with regulators that are on track to complete the deal in early 2022. we'll see okay that's it for today thank you to david floyer who co-created this episode with me and remember i publish each week on wikibon.com and siliconangle.com these episodes they're all available as podcasts all you're going to do is search breaking analysis podcast and you can always connect with me on twitter at dvalante or email me at david.valante siliconangle.com i always appreciate the comments on linkedin and in the clubhouse please follow me so you can be notified when we start a room and riff on these topics and don't forget to check out etr.plus for all the survey data this is dave vellante for the cube insights powered by etr be well and we'll see you next time [Music] you

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

>> From theCUBE Studios in Palo Alto in Boston, bringing you data-driven insights from theCUBE in ETR. This is Breaking Analysis with Dave Vellante. >> Cloud computing has been the single most transformative force in IT over the last decade. As we enter the 2020s, we believe that cloud will become the underpinning of a ubiquitous, intelligent and autonomous resource that will disrupt the operational stacks of virtually every company in every industry. Welcome to this week's special edition of Wikibon's CUBE Insights Powered by ETR. In this breaking analysis, and as part of theCUBE365's coverage of AWS re:Invent 2020, we're going to put forth our scenario for the next decade of cloud evolution. We'll also drill into the most recent data on AWS from ETR's October 2020 survey of more than 1,400 CIOs and IT professionals. So let's get right into it and take a look at how we see the cloud of yesterday, today and tomorrow. This graphic shows our view of the critical inflection points that catalyze the cloud adoption. In the middle of the 2000s, the IT industry was recovering from the shock of the dot-com bubble and of course 9/11. CIOs, they were still licking their wounds from the narrative, does IT even matter? AWS launched its Simple Storage Service and later EC2 with a little fanfare in 2006, but developers at startups and small businesses, they noticed that overnight AWS turned the data center into an API. Analysts like myself who saw the writing on the wall and CEO after CEO, they poo-pooed Amazon's entrance into their territory and they promised a cloud strategy that would allow them to easily defend their respective turfs. We'd seen the industry in denial before, and this was no different. The financial crisis was a boon for the cloud. CFOs saw a way to conserve cash, shift CAPEX to OPEX and avoid getting locked in to long-term capital depreciation schedules or constrictive leases. We also saw shadow IT take hold, and then bleed in to the 2010s in a big way. This of course created problems for organizations rightly concerned about security and rogue tech projects. CIOs were asked to come in and clean up the crime scene, and in doing so, realized the inevitable, i.e., that they could transform their IT operational models, shift infrastructure management to more strategic initiatives, and drop money to the bottom lines of their businesses. The 2010s saw an era of rapid innovation and a level of data explosion that we'd not seen before. AWS led the charge with a torrent pace of innovation via frequent rollouts or frequent feature rollouts. Virtually every industry, including the all-important public sector, got into the act. Again, led by AWS with the Seminole, a CIA deal. Google got in the game early, but they never really took the enterprise business seriously until 2015 when it hired Diane Green. But Microsoft saw the opportunity and leaned in heavily and made remarkable strides in the second half of the decade, leveraging its massive software stake. The 2010s also saw the rapid adoption of containers and an exit from the long AI winter, which along with the data explosion, created new workloads that began to go mainstream. Now, during this decade, we saw hybrid investments begin to take shape and show some promise. As the ecosystem realized broadly that it had to play in the AWS sandbox or it would lose customers. And we also saw the emergence of edge and IoT use cases like for example, AWS Ground Station, those emerge. Okay, so that's a quick history of cloud from our vantage point. The question is, what's coming next? What should we expect over the next decade? Whereas the last 10 years was largely about shifting the heavy burden of IT infrastructure management to the cloud, in the coming decade, we see the emergence of a true digital revolution. And most people agree that COVID has accelerated this shift by at least two to three years. We see all industries as ripe for disruption as they create a 360 degree view across their operational stacks. Meaning, for example, sales, marketing, customer service, logistics, etc., they're unified such that the customer experience is also unified. We see data flows coming together as well, where domain-specific knowledge workers are first party citizens in the data pipeline, i.e. not subservient to hyper-specialized technology experts. No industry is safe from this disruption. And the pandemic has given us a glimpse of what this is going to look like. Healthcare is going increasingly remote and becoming personalized. Machines are making more accurate diagnoses than humans, in some cases. Manufacturing, we'll see new levels of automation. Digital cash, blockchain and new payment systems will challenge traditional banking norms. Retail has been completely disrupted in the last nine months, as has education. And we're seeing the rise of Tesla as a possible harbinger to a day where owning and driving your own vehicle could become the exception rather than the norm. Farming, insurance, on and on and on. Virtually every industry will be transformed as this intelligent, responsive, autonomous, hyper-distributed system provides services that are ubiquitous and largely invisible. How's that for some buzzwords? But I'm here to tell you, it's coming. Now, a lot of questions remain. First, you may even ask, is this cloud that you're talking about? And I can understand why some people would ask that question. And I would say this, the definition of cloud is expanding. Cloud has defined the consumption model for technology. You're seeing cloud-like pricing models moving on-prem with initiatives like HPE's GreenLake and now Dell's APEX. SaaS pricing is evolving. You're seeing companies like Snowflake and Datadog challenging traditional SaaS models with a true cloud consumption pricing option. Not option, that's the way they price. And this, we think, is going to become the norm. Now, as hybrid cloud emerges and pushes to the edge, the cloud becomes this what we call, again, hyper-distributed system with a deployment and programming model that becomes much more uniform and ubiquitous. So maybe this s-curve that we've drawn here needs an adjacent s-curve with a steeper vertical. This decade, jumping s-curves, if you will, into this new era. And perhaps the nomenclature evolves, but we believe that cloud will still be the underpinning of whatever we call this future platform. We also point out on this chart, that public policy is going to evolve to address the privacy and concentrated industry power concerns that will vary by region and geography. So we don't expect the big tech lash to abate in the coming years. And finally, we definitely see alternative hardware and software models emerging, as witnessed by Nvidia and Arm and DPA's from companies like Fungible, and AWS and others designing their own silicon for specific workloads to control their costs and reduce their reliance on Intel. So the bottom line is that we see programming models evolving from infrastructure as code to programmable digital businesses, where ecosystems power the next wave of data creation, data sharing and innovation. Okay, let's bring it back to the current state and take a look at how we see the market for cloud today. This chart shows a just-released update of our IaaS and PaaS revenue for the big three cloud players, AWS, Azure, and Google. And you can see we've estimated Q4 revenues for each player and the full year, 2020. Now please remember our normal caveats on this data. AWS reports clean numbers, whereas Azure and GCP are estimates based on the little tidbits and breadcrumbs each company tosses our way. And we add in our own surveys and our own information from theCUBE Network. Now the following points are worth noting. First, while AWS's growth is lower than the other two, note what happens with the laws of large numbers? Yes, growth slows down, but the absolute dollars are substantial. Let me give an example. For AWS, Azure and Google, in Q4 2020 versus Q4 '19, we project annual quarter over quarter growth rate of 25% for AWS, 46% for Azure and 58% for Google Cloud Platform. So meaningfully lower growth rates for AWS compared to the other two. Yet AWS's revenue in absolute terms grows sequentially, 11.6 billion versus 12.4 billion. Whereas the others are flat to down sequentially. Azure and GCP, they'll have to come in with substantially higher annual growth to increase revenue from Q3 to Q4, that sequential increase that AWS can achieve with lower growth rates year to year, because it's so large. Now, having said that, on an annual basis, you can see both Azure and GCP are showing impressive growth in both percentage and absolute terms. AWS is going to add more than $10 billion to its revenue this year, with Azure growing nearly 9 billion or adding nearly 9 billion, and GCP adding just over 3 billion. So there's no denying that Azure is making ground as we've been reporting. GCP still has a long way to go. Thirdly, we also want to point out that these three companies alone now account for nearly $80 billion in infrastructure services annually. And the IaaS and PaaS business for these three companies combined is growing at around 40% per year. So much for repatriation. Now, let's take a deeper look at AWS specifically and bring in some of the ETR survey data. This wheel chart that we're showing here really shows you the granularity of how ETR calculates net score or spending momentum. Now each quarter ETR, they go get responses from thousands of CIOs and IT buyers, and they ask them, are you spending more or less than a particular platform or vendor? Net score is derived by taking adoption plus increase and subtracting out decrease plus replacing. So subtracting the reds from the greens. Now remember, AWS is a $45 billion company, and it has a net score of 51%. So despite its exposure to virtually every industry, including hospitality and airlines and other hard hit sectors, far more customers are spending more with AWS than are spending less. Now let's take a look inside of the AWS portfolio and really try to understand where that spending goes. This chart shows the net score across the AWS portfolio for three survey dates going back to last October, that's the gray. The summer is the blue. And October 2020, the most recent survey, is the yellow. Now remember, net score is an indicator of spending velocity and despite the deceleration, as shown in the yellow bars, these are very elevated net scores for AWS. Only Chime video conferencing is showing notable weakness in the AWS data set from the ETR survey, with an anemic 7% net score. But every other sector has elevated spending scores. Let's start with Lambda on the left-hand side. You can see that Lambda has a 65% net score. Now for context, very few companies have net scores that high. Snowflake and Kubernetes spend are two examples with higher net scores. But this is rarefied air for AWS Lambda, i.e. functions. Similarly, you can see AI, containers, cloud, cloud overall and analytics all with over 50% net scores. Now, while database is still elevated with a 46% net score, it has come down from its highs of late. And perhaps that's because AWS has so many options in database and its own portfolio and its ecosystem, and the survey maybe doesn't have enough granularity there, but in this competition, so I don't really know, but that's something that we're watching. But overall, there's a very strong portfolio from a spending momentum standpoint. Now what we want to do, let's flip the view and look at defections off of the AWS platform. Okay, look at this chart. We find this mind-boggling. The chart shows the same portfolio view, but isolates on the bright red portion of that wheel that I showed you earlier, the replacements. And basically you're seeing very few defections show up for AWS in the ETR survey. Again, only Chime is the sore spot. But everywhere else in the portfolio, we're seeing low single digit replacements. That's very, very impressive. Now, one more data chart. And then I want to go to some direct customer feedback, and then we'll wrap. Now we've shown this chart before. It plots net score or spending velocity on the vertical axis and market share, which measures pervasiveness in the dataset on the horizontal axis. And in the table portion in the upper-right corner, you can see the actual numbers that drive the plotting position. And you can see the data confirms what we know. This is a two-horse race right now between AWS and Microsoft. Google, they're kind of hanging out with the on-prem crowd vying for relevance at the data center. We've talked extensively about how we would like to see Google evolve its business and rely less on appropriating our data to serve ads and focus more on cloud. There's so much opportunity there. But nonetheless, you can see the so-called hybrid zone emerging. Hybrid is becoming real. Customers want hybrid and AWS is going to have to learn how to support hybrid deployments with offerings like outposts and others. But the data doesn't lie. The foundation has been set for the 2020s and AWS is extremely well-positioned to maintain its leadership, in our view. Now, the last chart we'll show takes some verbatim comments from customers that sum up the situation. These quotes were pulled from several ETR event roundtables that occurred in 2020. The first one talks to the cloud compute bill. It spikes and sometimes can be unpredictable. The second comment is from a CIO at IT/Telco. Let me paraphrase what he or she is saying. AWS is leading the pack and is number one. And this individual believes that AWS will continue to be number one by a wide margin. The third quote is from a CTO at an S&P 500 organization who talks to the cloud independence of the architecture that they're setting up and the strategy that they're pursuing. The central concern of this person is the software engineering pipeline, the cICB pipeline. The strategy is to clearly go multicloud, avoid getting locked in and ensuring that developers can be productive and independent of the cloud platform. Essentially separating the underlying infrastructure from the software development process. All right, let's wrap. So we talked about how the cloud will evolve to become an even more hyper-distributed system that can sense, act and serve, and provides sets of intelligence services on which digital businesses will be constructed and transformed. We expect AWS to continue to lead in this build-out with its heritage of delivering innovations and features at a torrid pace. We believe that ecosystems will become the main spring of innovation in the coming decade. And we feel that AWS has to embrace not only hybrid, but cross-cloud services. And it has to be careful not to push its ecosystem partners to competitors. It has to walk a fine line between competing and nurturing its ecosystem. To date, its success has been key to that balance as AWS has been able to, for the most part, call the shots. However, we shall see if competition and public policy attenuate its dominant position in this regard. What will be fascinating to watch is how AWS behaves, given its famed customer obsession and how it decodes the customer's needs. As Steve Jobs famously said, "Some people say, give the customers what they want. "That's not my approach. "Our job is to figure out "what they're going to want before they do." I think Henry Ford once asked, "If I'd ask customers what they wanted, "they would've told me a faster horse." Okay, that's it for now. It was great having you for this special report from theCUBE Insights Powered by ETR. Keep it right there for more great content on theCUBE from re:Invent 2020 virtual. (cheerful music)

>>from the Cube Studios in Palo Alto in Boston, connecting with thought leaders all around the world. This is a cube conversation, >>Everyone. Welcome to this cube conversation. I'm John for host of the Cube here in the Cubes Palo Alto studios during the co vid crisis. Square Quarantine with our crew, but we got the remote interviews. Got great to get great guests here from 44 to guard Fortinet, 40 Guard Labs, Derek Manky chief Security Insights and Global Threat alliances. At 14 it's 40 guard labs and, um, are Lakhani. Who's the lead researcher for the Guard Labs. Guys, great to see you. Derek. Good to see you again. Um, are you meet you? >>Hey, it's it's it's been a while and that it happened so fast, >>it just seems, are say it was just the other day. Derek, we've done a couple interviews in between. A lot of flow coming out of Florida net for the guards. A lot of action, certainly with co vid everyone's pulled back home. The bad actors taking advantage of the situation. The surface areas increased really is the perfect storm for security. Uh, in terms of action, bad actors are at all time high new threats here is going on. Take us through what you guys were doing. What's your team makeup look like? What are some of the roles and you guys were seeing on your team? And how's that transcend to the market? >>Yeah, sure, Absolutely. So you're right. I mean, like, you know, like I was saying earlier this this is all this always happens fast and furious. We couldn't do this without, you know, a world class team at 40 guard labs eso we've grown our team now to over 235 globally. There's different rules within the team. You know, if we look 20 years ago, the rules used to be just very pigeonholed into, say, anti virus analysis. Right now we have Thio account for when we're looking at threats. We have to look at that growing attack surface. We have to look at where these threats coming from. How frequently are they hitting? What verticals are they hitting? You know what regions? What are the particular techniques? Tactics, procedures, You know, we have threat. This is the world of threat Intelligence, Of course. Contextualizing that information and it takes different skill sets on the back end, and a lot of people don't really realize the behind the scenes. You know what's happening on bears. A lot of magic happen not only from what we talked about before in our last conversation from artificial intelligence and machine learning, that we do a 40 yard labs and automation, but the people. And so today we want to focus on the people on and talk about you know how on the back ends, we approach a particular threat. We're going to talk to the world, a ransom and ransomware. Look at how we dissect threats. How correlate that how we use tools in terms of threat hunting as an example, And then how we actually take that to that last mile and and make it actionable so that, you know, customers are protected. How we share that information with Keith, right until sharing partners. But again it comes down to the people. We never have enough people in the industry. There's a big shortages, we know, but it it's a really key critical element, and we've been building these training programs for over a decade within 40 guard lab. So you know, you know, John, this this to me is why, exactly why, I always say, and I'm sure Americans share this to that. There's never a dull day in the office. I know we hear that all the time, but I think today you know, all the viewers really get a new idea of why that is, because this is very dynamic. And on the back end, there's a lot of things that doing together our hands dirty with this, >>you know, the old expression started playing Silicon Valley is if you're in the arena, that's where the action and it's different than sitting in the stands watching the game. You guys are certainly in that arena. And, you know, we've talked and we cover your your threat report that comes out, Um, frequently. But for the folks that aren't in the weeds on all the nuances of security, can you kind of give the 101 ransomware. What's going on? What's the state of the ransomware situation? Um, set the stage because that's still continues to be a threat. I don't go a week, but I don't read a story about another ransomware and then it leaks out. Yeah, they paid 10 million in Bitcoin or something like I mean, this Israel. That's a real ongoing threat. What is it, >>quite a bit? Yeah, eso I'll give sort of the one on one and then maybe capacity toe mark, who's on the front lines dealing with this every day. You know, if we look at the world of I mean, first of all, the concept to ransom, obviously you have people that that has gone extended way, way before, you know, cybersecurity. Right? Um, in the world of physical crime s Oh, of course. You know the world's first ransom, where viruses actually called PC cyborg. This is in 1989. The ransom payment was demanded to appeal box from leave. It was Panama City at the time not to effective on floppy disk. Very small audience. Not a big attack surface. I didn't hear much about it for years. Um, you know, in really it was around 2000 and 10. We started to see ransomware becoming prolific, and what they did was somewhat cybercriminals. Did was shift on success from ah, fake antivirus software model, which was, you know, popping up a whole bunch of, you know said your computer is infected with 50 or 60 viruses. Chaos will give you an anti virus solution, Which was, of course, fake. You know, people started catching on. You know, the giggles up people caught onto that. So they weren't making a lot of money selling this project software. Uh, enter Ransomware. And this is where ransomware really started to take hold because it wasn't optional to pay for the software. It was mandatory almost for a lot of people because they were losing their data. They couldn't reverse engineer the current. Uh, the encryption kind of decrypt it with any universal tool. Ransomware today is very rigid. We just released our threat report for the first half of 2020. And we saw we've seen things like master boot record nbr around somewhere. This is persistent. It sits before your operating system when you boot up your computer. So it's hard to get rid of, um, very strong. Um, you know, public by the key cryptography that's being so each victim is infected with the different key is an example. The list goes on, and you know I'll save that for for the demo today. But that's basically it's It's very it's prolific and we're seeing shit. Not only just ransomware attacks for data, we're now starting to see ransom for extortion, for targeted ransom cases that we're going after, you know, critical business. Essentially, it's like a D O s holding revenue streams around too. So the ransom demands were getting higher because of this is Well, it's complicated. >>Yeah, I was mentioning, Omar, I want you to weigh in. I mean, 10 million is a lot we reported earlier this month. Garment was the company that was act I t guy completely locked down. They pay 10 million. Um, garment makes all those devices and a Z. We know this is impacting That's real numbers. So I mean, it's another little ones, but for the most part, it's new. It's, you know, pain in the butt Thio full on business disruption and extortion. Can you explain how it all works before I got it? Before we go to the demo, >>you know, you're you're absolutely right. It is a big number, and a lot of organizations are willing to pay that number to get their data back. Essentially their organization and their business is at a complete standstill. When they don't pay, all their files are inaccessible to them. Ransomware in general, what does end up from a very basic or review is it basically makes your files not available to you. They're encrypted. They have a essentially a pass code on them that you have to have the correct pass code to decode them. Ah, lot of times that's in the form of a program or actually a physical password you have type in. But you don't get that access to get your files back unless you pay the ransom. Ah, lot of corporations these days, they are not only paying the ransom, they're actually negotiating with the criminals as well. They're trying to say, Oh, you want 10 million? How about four million? Sometimes that it goes on as well, but it's Ah, it's something that organizations know that if they don't have the proper backups and the Attackers are getting smart, they're trying to go after the backups as well. They're trying to go after your duplicate files, so sometimes you don't have a choice, and organizations will will pay the ransom >>and it's you know they're smart. There's a business they know the probability of buy versus build or pay versus rebuild, so they kind of know where to attack. They know the tactics. The name is vulnerable. It's not like just some kitty script thing going on. This is riel system fistic ated stuff. It's and it's and this highly targeted. Can you talk about some use cases there and what's goes on with that kind of attack? >>Absolutely. The cybercriminals are doing reconnaissance. They're trying to find out as much as they can about their victims. And what happens is they're trying to make sure that they can motivate their victims in the fastest way possible to pay the ransom as well. Eh? So there's a lot of attacks going on. We usually we're finding now is ransomware is sometimes the last stage of an attack, so an attacker may go into on organization. They may already be taking data out of that organization. They may be stealing customer data P I, which is personal, identifiable information such as Social Security numbers or or driver's licenses or credit card information. Once they've done their entire attack, once they've gone, everything they can Ah, lot of times their end stage. There last attack is ransomware, and they encrypt all the files on the system and try and try and motivate the victim to pay as fast as possible and as much as possible as well. >>You know, it's interesting. I thought of my buddy today. It's like casing the joint. They check it out. They do their re kon reconnaissance. They go in, identify what's the move that's move to make. How to extract the most out of the victim in this case, Target. Um, and it really I mean, it's just go on a tangent, you know? Why don't we have the right to bear our own arms? Why can't we fight back? I mean, the end of the day, Derek, this is like, Who's protecting me? I mean, >>e do >>what? To protect my own, build my own army, or does the government help us? I mean, that's at some point, I got a right to bear my own arms here, right? I mean, this is the whole security paradigm. >>Yeah, so I mean, there's a couple of things, right? So first of all, this is exactly why we do a lot of that. I was mentioning the skills shortage and cyber cyber security professionals. Example. This is why we do a lot of the heavy lifting on the back end. Obviously, from a defensive standpoint, you obviously have the red team blue team aspect. How do you first, Um, no. There is what is to fight back by being defensive as well, too, and also by, you know, in the world that threat intelligence. One of the ways that we're fighting back is not necessarily by going and hacking the bad guys, because that's illegal in jurisdictions, right? But how we can actually find out who these people are, hit them where it hurts. Freeze assets go after money laundering that works. You follow the cash transactions where it's happening. This is where we actually work with key law enforcement partners such as Inter Pool is an example. This is the world, the threat intelligence. That's why we're doing a lot of that intelligence work on the back end. So there's other ways toe actually go on the offense without necessarily weaponizing it per se right like he's using, you know, bearing your own arms, Aziz said. There's different forms that people may not be aware of with that and that actually gets into the world of, you know, if you see attacks happening on your system, how you how you can use security tools and collaborate with threat intelligence? >>Yeah, I think that I think that's the key. I think the key is these new sharing technologies around collective intelligence is gonna be, ah, great way to kind of have more of an offensive collective strike. But I think fortifying the defense is critical. I mean, that's there's no other way to do that. >>Absolutely. I mean the you know, we say that's almost every week, but it's in simplicity. Our goal is always to make it more expensive for the cyber criminal to operate. And there's many ways to do that right you could be could be a pain to them by by having a very rigid, hard and defense. That means that if if it's too much effort on their end, I mean, they have roos and their in their sense, right, too much effort on there, and they're gonna go knocking somewhere else. Um, there's also, you know, a zay said things like disruption, so ripping infrastructure offline that cripples them. Yeah, it's wack a mole they're going to set up somewhere else. But then also going after people themselves, Um, again, the cash networks, these sorts of things. So it's sort of a holistic approach between anything. >>Hey, it's an arms race. Better ai better cloud scale always helps. You know, it's a ratchet game. Okay, tomorrow I want to get into this video. It's of ransomware four minute video. I'd like you to take us through you to lead you to read. Researcher, >>take us >>through this video and, uh, explain what we're looking at. Let's roll the video. >>All right? Sure s. So what we have here is we have the victims. That's top over here. We have a couple of things on this. Victims that stop. We have ah, batch file, which is essentially going to run the ransom where we have the payload, which is the code behind the ransomware. And then we have files in this folder, and this is where you typically find user files and, ah, really world case. This would be like Microsoft Microsoft Word documents or your Power point presentations. Over here, we just have a couple of text files that we've set up we're going to go ahead and run the ransomware and sometimes Attackers. What they do is they disguise this like they make it look like a like, important word document. They make it look like something else. But once you run, the ransomware usually get a ransom message. And in this case, the ransom message says your files are encrypted. Uh, please pay this money to this Bitcoin address. That obviously is not a real Bitcoin address that usually they look a little more complicated. But this is our fake Bitcoin address, but you'll see that the files now are encrypted. You cannot access them. They've been changed. And unless you pay the ransom, you don't get the files. Now, as the researchers, we see files like this all the time. We see ransomware all the all the time. So we use a variety of tools, internal tools, custom tools as well as open source tools. And what you're seeing here is open source tool is called the cuckoo sandbox, and it shows us the behavior of the ransomware. What exactly is a ransom we're doing in this case? You can see just clicking on that file launched a couple of different things that launched basically a command execute herbal, a power shell. It launched our windows shell and then it did things on the file. It basically had registry keys. It had network connections. It changed the disk. So this kind of gives us behind the scenes. Look at all the processes that's happening on the ransomware and just that one file itself. Like I said, there's multiple different things now what we want to do As researchers, we want to categorize this ransomware into families. We wanna try and determine the actors behind that. So we dump everything we know in the ransomware in the central databases. And then we mind these databases. What we're doing here is we're actually using another tool called malt ego and, uh, use custom tools as well as commercial and open source tools. But but this is a open source and commercial tool. But what we're doing is we're basically taking the ransomware and we're asking malty, go to look through our database and say, like, do you see any like files? Or do you see any types of incidences that have similar characteristics? Because what we want to do is we want to see the relationship between this one ransomware and anything else we may have in our system because that helps us identify maybe where the ransom that's connecting to where it's going thio other processes that may be doing. In this case, we can see multiple I P addresses that are connected to it so we can possibly see multiple infections weaken block different external websites. If we can identify a command and control system, we can categorize this to a family. And sometimes we can even categorize this to a threat actor that has claimed responsibility for it. Eso It's essentially visualizing all the connections and the relationship between one file and everything else we have in our database in this example. Off course, we put this in multiple ways. We can save these as reports as pdf type reports or, you know, usually HTML or other searchable data that we have back in our systems. And then the cool thing about this is this is available to all our products, all our researchers, all our specialty teams. So when we're researching botnets when we're researching file based attacks when we're researching, um, you know, I P reputation We have a lot of different IOC's or indicators of compromise that we can correlate where attacks goes through and maybe even detective new types of attacks as well. >>So the bottom line is you got the tools using combination of open source and commercial products. Toe look at the patterns of all ransomware across your observation space. Is that right? >>Exactly. I should you like a very simple demo. It's not only open source and commercial, but a lot of it is our own custom developed products as well. And when we find something that works, that logic that that technique, we make sure it's built into our own products as well. So our own customers have the ability to detect the same type of threats that we're detecting as well. At four of our labs intelligence that we acquire that product, that product of intelligence, it's consumed directly by our projects. >>Also take me through what, what's actually going on? What it means for the customers. So border guard labs. You're looking at all the ransom where you see in the patterns Are you guys proactively looking? Is is that you guys were researching you Look at something pops on the radar. I mean, take us through What is what What goes on? And then how does that translate into a customer notification or impact? >>So So, yeah, if you look at a typical life cycle of these attacks, there's always proactive and reactive. That's just the way it is in the industry, right? So of course we try to be a wear Some of the solutions we talked about before. And if you look at an incoming threat, first of all, you need visibility. You can't protect or analyze anything that you can't see. So you got to get your hands on visibility. We call these I, O. C s indicators a compromise. So this is usually something like, um, actual execute herbal file, like the virus from the malware itself. It could be other things that are related to it, like websites that could be hosting the malware as an example. So once we have that seed, we call it a seed. We could do threat hunting from there, so we can analyze that right? If it's ah piece of malware or a botnet weaken do analysis on that and discover more malicious things that this is doing. Then we go investigate those malicious things and we really you know, it's similar to the world of C. S. I write have these different gods that they're connecting. We're doing that at hyper scale on DWI. Use that through these tools that Omar was talking. So it's really a life cycle of getting, you know, the malware incoming seeing it first, um, analyzing it on, then doing action on that. Right? So it's sort of a three step process, and the action comes down to what tomorrow is saying water following that to our customers so that they're protected. But then in tandem with that, we're also going further. And I'm sharing it, if if applicable to, say, law enforcement partners, other threat Intel sharing partners to And, um, there's not just humans doing that, right? So the proactive peace again, This is where it comes to artificial intelligence machine learning. Um, there's a lot of cases where we're automatically doing that analysis without humans. So we have a I systems that are analyzing and actually creating protection on its own. Two. So it Zack white interest technology. >>A decision. At the end of the day, you want to protect your customers. And so this renders out if I'm afford a net customer across the portfolio. The goal here is to protect them from ransomware. Right? That's the end of game. >>Yeah, And that's a very important thing when you start talking these big dollar amounts that were talking earlier comes Thio the damages that air down from estimates. >>E not only is a good insurance, it's just good to have that fortification. Alright, So dark. I gotta ask you about the term the last mile because, you know, we were before we came on camera. You know, I'm band with junkie, always want more bandwidth. So the last mile used to be a term for last mile to the home where there was telephone lines. Now it's fiber and by five. But what does that mean to you guys and security is that Does that mean something specific? >>Yeah, Yeah, absolutely. The easiest way to describe that is actionable, right? So one of the challenges in the industry is we live in a very noisy industry when it comes thio cybersecurity. What I mean by that is because of that growing attacks for fists on do you know, you have these different attack vectors. You have attacks not only coming in from email, but websites from, you know, DDOS attacks. There's there's a lot of volume that's just going to continue to grow is the world of I G N O T. S O. What ends up happening is when you look at a lot of security operation centers for customers as an example, um, there are it's very noisy. It's, um you can guarantee that every day you're going to see some sort of probe, some sort of attack activity that's happening. And so what that means is you get a lot of protection events, a lot of logs, and when you have this worldwide shortage of security professionals, you don't have enough people to process those logs and actually started to say, Hey, this looks like an attack. I'm gonna go investigate it and block it. So this is where the last mile comes in because ah, lot of the times that you know these logs, they light up like Christmas. And I mean, there's a lot of events that are happening. How do you prioritize that? How do you automatically add action? Because The reality is, if it's just humans, doing it on that last mile is often going back to your bandwidth terms. There's too much too much lately. See right, So how do you reduce that late and see? That's where the automation the AI machine learning comes in. Thio solve that last mile problem toe automatically either protection. Especially important because you have to be quicker than the attacker. It's an arms race like E. >>I think what you guys do with four to Guard Labs is super important. Not like the industry, but for society at large, as you have kind of all this, you know, shadow, cloak and dagger kind of attacks systems, whether it's National Security international or just for, you know, mafias and racketeering and the bad guys. Can you guys take a minute and explain the role of 40 guards specifically and and why you guys exist? I mean, obviously there's a commercial reason you both on the four net that you know trickles down into the products. That's all good for the customers. I get that, but there's more to the fore to guard than just that. You guys talk about this trend and security business because it is very clear that there's a you know, uh, collective sharing culture developing rapidly for societal benefit. Can you take them into something that, >>Yeah, sure, I'll get my thoughts. Are you gonna that? So I'm going to that Teoh from my point of view, I mean, there's various functions, So we've just talked about that last mile problem. That's the commercial aspect we create through 40 yard labs, 40 yards, services that are dynamic and updated to security products because you need intelligence products to be ableto protect against intelligence attacks. That's just the defense again, going back to How can we take that further? I mean, we're not law enforcement ourselves. We know a lot about the bad guys and the actors because of the intelligence work that you do. But we can't go in and prosecute. We can share knowledge and we can train prosecutors, right? This is a big challenge in the industry. A lot of prosecutors don't know how to take cybersecurity courses to court, and because of that, a lot of these cybercriminals rain free. That's been a big challenge in the industry. So, you know, this has been close to my heart over 10 years, I've been building a lot of these key relationships between private public sector as an example, but also private sector things like Cyber Threat Alliance, where a founding member of the Cyber Threat Alliance, if over 28 members and that alliance. And it's about sharing intelligence to level that playing field because Attackers room freely. What I mean by that is there's no jurisdictions for them. Cybercrime has no borders. Um, they could do a million things, uh, wrong and they don't care. We do a million things right. One thing wrong, and it's a challenge. So there's this big collaboration that's a big part of 40 guard. Why exists to is to make the industry better. Thio, you know, work on protocols and automation and and really fight fight this together. Well, remaining competitors. I mean, we have competitors out there, of course, on DSO it comes down to that last mile problem. John is like we can share intelligence within the industry, but it's on Lee. Intelligence is just intelligence. How do you make it useful and actionable? That's where it comes down to technology integration. And, >>um, are what's your take on this, uh, societal benefit because, you know, I've been saying since the Sony hack years ago that, you know, when you have nation states that if they put troops on our soil, the government would respond. Um, but yet virtually they're here, and the private sector's defend for themselves. No support. So I think this private public partnership thing is very relevant. I think is ground zero of the future build out of policy because, you know, we pay for freedom. Why don't we have cyber freedom is if we're gonna run a business. Where's our help from the government? Pay taxes. So again, if a military showed up, you're not gonna see, you know, cos fighting the foreign enemy, right? So, again, this is a whole new change over it >>really is. You have to remember that cyberattacks puts everyone on even playing field, right? I mean, you know, now don't have to have a country that has invested a lot in weapons development or nuclear weapons or anything like that, right? Anyone can basically come up to speed on cyber weapons as long as they have an Internet connection. So it evens the playing field, which makes it dangerous, I guess, for our enemies, you know, But absolutely that I think a lot of us, You know, from a personal standpoint, a lot of us have seen researchers have seen organizations fail through cyber attacks. We've seen the frustration we've seen. Like, you know, besides organization, we've seen people like, just like grandma's loser pictures of their, you know, other loved ones because they can being attacked by ransom, where I think we take it very personally when people like innocent people get attacked and we make it our mission to make sure we can do everything we can to protect them. But But I will add that the least here in the U. S. The federal government actually has a lot of partnerships and ah, lot of programs to help organizations with cyber attacks. Three us cert is always continuously updating, you know, organizations about the latest attacks. Infra Guard is another organization run by the FBI, and a lot of companies like Fortinet and even a lot of other security companies participate in these organizations so everyone can come up to speed and everyone share information. So we all have a fighting chance. >>It's a whole new wave paradigm. You guys on the cutting edge, Derek? Always great to see a mark. Great to meet you remotely looking forward to meeting in person when the world comes back to normal as usual. Thanks for the great insights. Appreciate it. >>All right. Thank God. Pleasure is always >>okay. Q conversation here. I'm John for a host of the Cube. Great insightful conversation around security Ransomware with a great demo. Check it out from Derek and, um, are from 14 guard labs. I'm John Ferrier. Thanks for watching.

from the cube studios in palo alto in boston bringing you data driven insights from the cube and etr this is breaking analysis with dave vellante over the past 150 days virtually everybody that i know in the technology industry has become an expert on covid in some way shape or form we've all lived the reality that covet 19 has accelerated by at least two years many trends that were in motion well before the virus hit the cyber security sector is no exception and one of the best examples where we have witnessed the accelerated change hello everyone and welcome to this week's episode of wikibon cube insights powered by etr in this breaking analysis we'll update you on the all-important security sector which remains one of the top spending priorities for organizations and i want to give you a shout out to my colleague eric bradley from etr who gave me some really good data and some macro insights as well as some anecdotal data from csos for this episode let's take a look at the big picture first now for many years we've talked about the shifting patterns in networking moving from what's often referred to as a north-south architecture meaning a hierarchical network that supports you know age-old organizational structures well today the network is flattening into what they often refer to as an east-west model and the moat or perimeter it's been vaporized the perimeter is now wherever the user is and users are at home or they're at their beach houses thanks to kovid now this is a bad actor's dream as the threat surfaced has expanded by orders of magnitude and as we've said in the past the adversary is well funded extremely capable and highly motivated because the roi of infiltration and exfiltration is outstanding the cso's job quite simply stated is to lower that return on investment now the other big trend that we see is that the cloud and sas are reducing reliance on hardware-based solutions like traditional firewalls because so many workers are now at home they're in their accessing sensitive data identity and endpoint security are exploding xdr or extended detection and response and zero trust networks are on the rise organizations are increasingly relying on analytics and automation to detect and remediate threats you know alerts just don't cut it anymore i need action and so to do so they're turning to a number of best of breed point products that have the potential to become the next great security platforms and this is setting up an epic battle between hot startups that are growing very very quickly and entrenched incumbents that really aren't going to go down without a fight finally while security is clearly a top spending priority customers and their cfos continue to be somewhat circumspect with respect to how much they allocate toward security budgets especially in the context of a shrinking i.t spending climate that we have said is dropping between five and eight percent in 2020. now security is critical but even in these times spending is governed by these tight budgets well cyber remains a top category in the etr taxonomy in terms of its presence in the data set what this chart tells us is that cios and i.t buyers have other priorities that they have to fund this data shows a comparison of net scores over three survey dates october of last year april and july net score remember is an indicator of momentum which is calculated by subtracting the percent of customers spending less on the technology from those spending more it's more complicated than that but that's that's the basics and you can see that at a 29 net score the security sector is just one of many priorities that i.t buyers face now remember this is the july survey and it's asking customers are you planning to spend more or less in the second half of 2020 relative to the first half and it's a forward-looking metric so what may be happening here is that the height of the lockdown and in the u.s anyway and the pivot to work from home organizations were spending heavily and are now fine-tuning those investments and maybe addressing other digital priorities let's look back and do some pre and post-covet assessments of various players within the etr data set i'm gonna go fairly quickly through these next slides but i want to give you a perspective as to how the security landscape and the vendor momentum has changed in the past eight months first i'm going to take you back to the january data set we actually originally did this exercise last year and then we updated it right at the beginning of 2020. the chart shows the top-ranked cyber security companies based on two metrics the left-hand side sorts the data and ranks companies based on net score or spending momentum and the right-hand side shows the ranking by shared n which is a measure of the pervasiveness of a company in the data set i.e the number of mentions that they get in the sector and what we did is we gave four stars to those companies that showed up in the top of both of those rankings and two stars to those that were close so you can see that microsoft splunk palo alto and proofpoint as well as octa and crowdstrike and then we added z scalar in january as new and then cyber arc software all got four stars then we gave cisco and fortinet two stars now this next chart shows the same thing at the height of the u.s lockdown now you may say okay what's the difference there's still microsoft palo alto proof point octa cyber arc z scaler and crowdstrike at four stars with cisco and fortnite having two star stars splunk fell off but that's it well what's different is instead of making the cut the top 22 which we did last time we narrowed it down to the top ten in order for a company to make that grade so if we had done that in january octa crowdstrike zscaler and cyberark they wouldn't have made the cut but in april they did as their presence in the dataset grew and we strongly believe this is a direct result of the work from home pivot crowdstrike endpoint octa identity access management z-scaler cloud security and they're disrupting traditional appliance-based firewalls now just to note we placed dell emc which was rsa and ibm in the list just for context now let's take a look at the most recent july survey now a lot of i'm out on a limb a little bit here because many of these companies they haven't reported yet so we don't have full visibility on their business outlook but we show the same data for the most recent survey the red line that you see there is the top 10 cutoff point and you can see splunk which didn't make the cut in april is back on the four-star list it's very possible buyers took a pause last quarter and focused attention on work from home but splunk continues to impress as it shifts toward the subscription model that we've talked about in the past splunk has a very strong hold on the sim space but everyone wants a piece of splunk especially some of the traditional firewall companies who they're seeing their hardware business dying so we're watching the competition from these players but also some other players like tennable now proof point fell off the four-star list because its net score didn't make the top ten crowdstrike cyber arc and zscaler also fell back because they dropped below the top 10 in shared in but we still really like these companies and expect them to continue to do well you know it could be some anomalies in the survey but we're trying to be as transparent as possible with you share the data listen to it interpret it and really adjust our models accordingly each quarter now let me make a few points and try to interpret what might be happening here first i want to point out octa pops to the top of the net score ranking overtaking crowdstrike's momentum from the last survey now one customer in the financial services sector told eric bradley on a recent then we're seeing amazing things from octa but the traditional firewall companies are stepping into identity they may not be best of breed but they have a level of integration and that's appealing to this individual this person also specifically called out palo alto and fortinet is trying to encroach on that space so keep your eyes on that now crowdstrike has declined noticeably which surprised us z z scalar is actually showing more momentum relative to the last survey so that's a positive palo alto and microsoft are consistently holding serve and continue to be leaders proof point and cyber arc are showing a bit of a velocity drop and sales point and tenable are also catching our attention in this survey and of course sales sale point which is identity management had a great quarter and reinstituted its guidance giving us the benefit of hindsight on its performance so it was actually pretty easy to give them two stars now just a side note by the way we've cut the data here with those companies that have more than 50 mentions in the sector we didn't do that the first time we did this we allowed companies with less than 50. so we're trying to tighten that up a bit so we still maintain strongly that you're seeing cloud endpoint and identity as the big security themes here csos need tools to be responsive they don't want to just get an alert secops pros would rather immediately shut off access and risk pissing off a user than getting hacked and companies are increasingly turning to ai to detect and they're relying on automation to remediate or protect and fence off critical resources let's now look at the two players or players in our two-dimensional view followers of this program know that we like to plot vendors within a sector across two of our favorite metrics net score or spending momentum which is a simple metric that tracks those spending more versus less on the technology and market share which measu measures a vendor's pervasiveness in the data set and it's calculated by taking the number of mentions a vendor gets within a sector divided by the total responses what we show here are the key security players that we've highlighted over the last several quarters let me start with microsoft microsoft has consistently performed well in the security sector as well as other parts of the etr taxonomy as you know they have a huge presence in the survey which is indicated on the horizontal axis and you can see they have a very solid net score which is shown on the y-axis impressive for a company their size now one interesting thing is you don't see aws in this chart and it's because aws and microsoft at least so far have somewhat different strategies with respect to security microsoft with its long application software history and sas presence across office 365 and sharepoint etc with active directory has been really focused on selling security solutions to directly protect its apps they have offerings like defender atp which is advanced threat protection sentinel which is microsoft sim cloud offering azure identity access management and the company's really going hard after this space now aws of course prioritizes security but they don't show an etr data set the same way microsoft does it's almost like aws is hiding in plain sight look aws has always put a great deal of emphasis on security and securing its infrastructure like the s3 buckets and it's you know it announced iam for ec2 way back in 2012. and last year at its reinforced conference you saw an impressive focus on security in a burgeoning security ecosystem in fact when you think of getting started in aws you really think about three things ec2 s3 and iam so i'd expect to see aws really become more prominent over time in the data set now i'll spend a minute talking about octa for the first time since we've been analyzing the security space with etr data octa has the highest net score at 58 percent it had consistently been crowdstrike with this moniker and the momentum lead the company though is dropped in this quarter survey and that's something that we're watching and by the way we're not implying that octa and crowdstrike are direct competitors they're not now as you can see nonetheless that crowdstrike z scalar and sales point sale sale point show very elevated net scores and we've plotted tenable here which is also showing some strength so you can see the respective positions of proof point and fortinet these are more mature companies they were founded in the early part of the century so you'd expect them to have somewhat lower net scores given their history and maturity and then there's cisco they've got a huge presence in the data and big in security cisco's doing really well in that space it consistently grows its security business in the double digits each quarter and it's a real feather in the cisco portfolio cap this is important because cisco's traditional hardware business continues to come under pressure splunk we talked about a lot and it's no surprise at their leadership position but i want to talk a little bit more about palo alto networks here's a company that we've talked about quite a bit in the past they are a tier one player in security they got great service csos want to work with them because they are thought leaders they're like a gold standard and have an impressive portfolio of great solutions but their traditional firewall business is coming under pressure for the reasons that we discussed earlier now palo alto has expanded its portfolio into the cloud and with prisma the company's suite of security services it will maintain a leadership position in our view but palo alto networks as we've discussed had some missteps with its product transition its sales execution and some of some challenges with its pricing models and it hurt their stock price but we've always said that they would work through these issues and that that was a buying opportunity the other thing about palo alto is you know they're considered the expensive choice you got to pay for that gold standard but that's what customers you know will tell us and so you're paying up for those top tier offerings but that's a sort of two-edged sword for palo alto here's an example why people often compare fortinet to palo alto and as we've shared in previous segments the valuation divergence between palo alto and fortinet where the the latter was making a smoother transition to its future and people often tell us that fortinet well you know maybe it's considered not as elite as palo alto they are a value choice their stuff just works and fortinet is a great alternative to palo alto and that has served them very well now let's take a closer look at the valuations of some of these companies we started off this segment by saying that the pandemic has affected every sector and especially cyber security so the next chart that we're showing here is the progression of key valuation metrics since earlier this year what we show are the valuations of nine of the companies in the sector since mid-february the data tracks their respective valuations their revenue multiples their growth rates in both value and revenue revenue growth is shown in the last column for the most recent quarterly report now the companies in red have yet to report the report any day now so he said i'm flying a little bit blind here and we'll have to take a look after the earnings to see how the survey data aligns with the actual results but let me make a few points here first here's the s p in nasdaq performance you see it in february in june and august pandemic recession what are you talking about you'd never know it looking at this data the nasdaq especially is up 14 said since mid february which is quite astounding next i want to come back to the discussion about palo alto and fortinet fortinet already has reported this quarter and palo alto has not but you can see based on the revenue multiples highlighted in red that the valuation divergence is starting to shrink a little bit and we'll see if that holds up after palo alto reports now the big eye popper in this chart is the valuation increases from february to august for octa crowdstrike and z scalar 52 67 and 104 percent increase respectively now you can't say we didn't warn you that these companies were all well positioned when we reported last year and in our january episode but i did say actually to be honest in the last episode that these three i thought were getting a little expensive that was a couple months ago and since then they've continued to run up so if you've been waiting for an entry point based on my advice well i'm sorry for that but look at the revenue multiples look at the expansion in the orange octa goes from 34x to 52x crowdstrike from 39x to 66x z scalar 25x to 43x i mean wow let's see what happens after these three report by this time i would have hoped that they'd taken a little breather maybe over the summer and you could have jumped in to these stocks but they just keep going up and despite the decline in net score for crowdstrike i still really like all three of these companies and feel that they're very well positioned from a product standpoint and customer feedback perspective and finally i want to mention sale point which we said last time was one to watch sale point crushed its quarter bringing in some large deals and providing forward guidance nearly a 50 percent valuation increase since february in a revenue multiple expansion from last quarter where the street last quarter wasn't really thrilled with their numbers but identity management is hot and so now is sales point from the streets perspective the last thing i'll say here is watch the growth rates expectations are very high for some of these companies and the street will cream any of them that misses now that may be your opportunity to jump in because i like these companies i think they're disruptors but as always do your research and watch out for the big whales trying to freeze the markets on these guys all right let's wrap up we've covered a lot of ground today and surf the landscape a little bit so look the trend is plain as day the move to sas is entrenched and by the way this isn't necessarily all good news for buyers cios and cfos tell me that the dark side of capex to opex is unpredictable bills but the flexibility and business value gained is outweighing the downside and every vendor in this space is transitioning into a sas and annual recurring revenue model we believe the remote work trend is here to stay organizations are re-architecting their business around work from home and we think that they're seeing some real benefits they've made investments and it's driving new modes of work and productivity they're not just going to throw away those investments why should they what just to go back to the old way it's not going to happen and if we as we've said previously look the internet it's like the new private network so you've got a question vpns and sd-wan they start to look like stop gaps and of course you know the cloud endpoint security cloud-based iam they are clearly winning in the marketplace you know we're also seeing new security regimes emerge where the cso and the secops team are not this island we we've seen even some csos falling back under the cio which used to be taboo he used to be thought of that's like the fox guarding the hen house but this idea of shared responsibility is not just between the cloud providers and the secops teams because security is a board level priority everyone in the business is becoming more aware more attuned and despite the millennials fascination with and undotted courage when it comes to tick tock i digress now the last two points are interesting i remember reading a post by john oltzek who was an esg security analyst and he predicted last year that integrated suites would win out over the buffet of point products on the market and you know generally i i agreed with that assessment but look at least in the near term and probably mid-term that doesn't seem to be happening as we we've seen these hot companies really take off the ones that we've highlighted now these companies have ambitions beyond selling products and they would bristle at me lumping them into point products their boards are going after platform plays so they're on a collision course with each other and the big guys this should be fun to watch because the big integrated companies are well funded they got great cash flow they got large customer bases and and i've said they're not going down without a fight so i would expect eventually there's going to be more of an equilibrium to what seems to be right now a bifurcated and unbalanced market today so you're going to see more m a activity expect that however at these valuations some of these companies that we've highlighted they're becoming acquisition proof as such they'd better keep innovating or they're going to be in big trouble all right that's it for today remember these episodes are all available as podcasts wherever you listen so please subscribe i publish weekly on wikibon.com we've added in the wikibon menu bar a breaking analysis link that has all the episodes in there i also publish on siliconangle.com so check that out and please do comment on my linkedin posts don't forget to check out etr.plus for all the survey action get in touch on twitter i'm at d vellante or email me at david.vellante at siliconangle.com this is dave vellante for the cube insights powered by etr thanks for watching everybody be well and we'll see you next time [Music] you

>> Announcer: From theCUBE studios in Palo Alto in Boston, connecting with thought leaders all around the world. This is a CUBE conversation. >> Hi everyone. Welcome to this CUBE Conversation. I'm John Furrier host of theCUBE here in the CUBEs, Palo Alto studios during the COVID crisis. We're quarantine with our crew, but we got the remote interviews. Got two great guests here from Fortinet FortiGuard Labs, Derek Mankey, Chief Security Insights and global threat alliances at Fortinet FortiGuard Labs. And Aamir Lakhani who's the Lead Researcher for the FortiGuard Labs. You guys is great to see you. Derek, good to see you again, Aamir, good to meet you too. >> It's been a while and it happens so fast. >> It just seems was just the other day, Derek, we've done a couple of interviews in between a lot of flow coming out of Fortinet FortiGuard, a lot of action, certainly with COVID everyone's pulled back home, the bad actors taking advantage of the situation. The surface areas increased really is the perfect storm for security in terms of action, bad actors are at an all time high, new threats. Here's going on, take us through what you guys are doing. What's your team makeup look like? What are some of the roles and you guys are seeing on your team and how does that transcend to the market? >> Yeah, sure, absolutely. So you're right. I mean like I was saying earlier that is, this always happens fast and furious. We couldn't do this without a world class team at FortiGuard Labs. So we've grown our team now to over 235 globally. There's different rules within the team. If we look 20 years ago, the rules used to be just very pigeonholed into say antivirus analysis, right? Now we have to account for, when we're looking at threats, we have to look at that growing attack surface. We have to look at where are these threats coming from? How frequently are they hitting? What verticals are they hitting? What regions, what are the particular techniques, tactics, procedures? So we have threat. This is the world of threat intelligence, of course, contextualizing that information and it takes different skill sets on the backend. And a lot of people don't really realize the behind the scenes, what's happening. And there's a lot of magic happening, not only from what we talked about before in our last conversation from artificial intelligence and machine learning that we do at FortiGuard Labs and automation, but the people. And so today we want to focus on the people and talk about how on the backend we approached a particular threat, we're going to talk to the word ransom and ransomware, look at how we dissect threats, how correlate that, how we use tools in terms of threat hunting as an example, and then how we actually take that to that last mile and make it actionable so that customers are protected. I would share that information with keys, right, until sharing partners. But again, it comes down to the people. We never have enough people in the industry, there's a big shortage as we know, but it's a really key critical element. And we've been building these training programs for over a decade with them FortiGuard Labs. So, you know John, this to me is exactly why I always say, and I'm sure Aamir can share this too, that there's never a adult day in the office and all we hear that all the time. But I think today, all of you is really get an idea of why that is because it's very dynamic and on the backend, there's a lot of things that we're doing to get our hands dirty with this. >> You know the old expression startup plan Silicon Valley is if you're in the arena, that's where the action is. And it's different than sitting in the stands, watching the game. You guys are certainly in that arena and you got, we've talked and we cover your, the threat report that comes out frequently. But for the folks that aren't in the weeds on all the nuances of security, can you kind of give the 101 ransomware, what's going on? What's the state of the ransomware situation? Set the stage because that's still continues to be threat. I don't go a week, but I don't read a story about another ransomware. And then at least I hear they paid 10 million in Bitcoin or something like, I mean, this is real, that's a real ongoing threat. What is it? >> The (indistinct) quite a bit. But yeah. So I'll give sort of the 101 and then maybe we can pass it to Aamir who is on the front lines, dealing with this every day. You know if we look at the world of, I mean, first of all, the concept of ransom, obviously you have people that has gone extended way way before cybersecurity in the world of physical crime. So of course, the world's first ransom where a virus is actually called PC Cyborg. This is a 1989 around some payment that was demanded through P.O Box from the voters Panama city at the time, not too effective on floppiness, a very small audience, not a big attack surface. Didn't hear much about it for years. Really, it was around 2010 when we started to see ransomware becoming prolific. And what they did was, what cyber criminals did was shift on success from a fake antivirus software model, which was, popping up a whole bunch of, setting here, your computer's infected with 50 or 60 viruses, PaaS will give you an antivirus solution, which was of course fake. People started catching on, the giggles out people caught on to that. So they, weren't making a lot of money selling this fraudulent software, enter ransomware. And this is where ransomware, it really started to take hold because it wasn't optional to pay for this software. It was mandatory almost for a lot of people because they were losing their data. They couldn't reverse engineer that the encryption, couldn't decrypt it, but any universal tool. Ransomware today is very rigid. We just released our threat report for the first half of 2020. And we saw, we've seen things like master boot record, MVR, ransomware. This is persistent. It sits before your operating system, when you boot up your computer. So it's hard to get rid of it. Very strong public private key cryptography. So each victim is effective with the direct key, as an example, the list goes on and I'll save that for the demo today, but that's basically, it's just very, it's prolific. We're seeing shuts not only just ransomware attacks for data, we're now starting to see ransom for extortion, for targeted around some cases that are going after critical business. Essentially it's like a DoS holding revenue streams go ransom too. So the ransom demands are getting higher because of this as well. So it's complicated. >> Was mentioning Aamir, why don't you weigh in, I mean, 10 million is a lot. And we reported earlier in this month. Garmin was the company that was hacked, IT got completely locked down. They pay 10 million, Garmin makes all those devices. And as we know, this is impact and that's real numbers. I mean, it's not other little ones, but for the most part, it's nuance, it's a pain in the butt to full on business disruption and extortion. Can you explain how it all works before we go to the demo? >> You know, you're absolutely right. It is a big number and a lot of organizations are willing to pay that number, to get their data back. Essentially their organization and their business is at a complete standstill when they don't pay, all their files are inaccessible to them. Ransomware in general, what it does end up from a very basic overview is it basically makes your files not available to you. They're encrypted. They have essentially a passcode on them that you have to have the correct passcode to decode them. A lot of times that's in a form of a program or actually a physical password you have to type in, but you don't get that access to get your files back unless you pay the ransom. A lot of corporations these days, they are not only paying the ransom. They're actually negotiating with the criminals as well. They're trying to say, "Oh, you want 10 million? "How about 4 million?" Sometimes that goes on as well. But it's something that organizations know that if they didn't have the proper backups and the hackers are getting smart, they're trying to go after the backups as well. They're trying to go after your duplicated files. So sometimes you don't have a choice in organizations. Will pay the ransom. >> And it's, they're smart, there's a business. They know the probability of buy versus build or pay versus rebuild. So they kind of know where to attack. They know that the tactics and it's vulnerable. It's not like just some kitty script thing going on. This is real sophisticated stuff it's highly targeted. Can you talk about some use cases there and what goes on with that kind of a attack? >> Absolutely. The cyber criminals are doing reconnaissance and trying to find out as much as they can about their victims. And what happens is they're trying to make sure that they can motivate their victims in the fastest way possible to pay the ransom as well. So there's a lot of attacks going on. We usually, what we're finding now is ransomware is sometimes the last stage of an attack. So an attacker may go into an organization. They may already be taking data out of that organization. They may be stealing customer data, PII, which is personal identifiable information, such as social security numbers, or driver's licenses, or credit card information. Once they've done their entire tap. Once they've gone everything, they can. A lot of times their end stage, their last attack is ransomware. And they encrypt all the files on the system and try and motivate the victim to pay as fast as possible and as much as possible as well. >> I was talking to my buddy of the day. It's like casing the joint there, stay, check it out. They do their recon, reconnaissance. They go in identify what's the best move to make, how to extract the most out of the victim in this case, the target. And it really is, I mean, it's just to go on a tangent, why don't we have the right to bear our own arms? Why can't we fight back? I mean, at the end of the day, Derek, this is like, who's protecting me? I mean, what to protect my, build my own arms, or does the government help us? I mean, at some point I got a right to bear my own arms here. I mean, this is the whole security paradigm. >> Yeah. So, I mean, there's a couple of things. So first of all, this is exactly why we do a lot of, I was mentioning the skill shortage in cyber cybersecurity professionals as an example. This is why we do a lot of the heavy lifting on the backend. Obviously from a defensive standpoint, you obviously have the red team, blue team aspect. How do you first, there's what is to fight back by being defensive as well, too. And also by, in the world of threat intelligence, one of the ways that we're fighting back is not necessarily by going and hacking the bad guys because that's illegal jurisdictions. But how we can actually find out who these people are, hit them where it hurts, freeze assets, go after money laundering networks. If you follow the cash transactions where it's happening, this is where we actually work with key law enforcement partners, such as Interpol as an example, this is the world of threat intelligence. This is why we're doing a lot of that intelligence work on the backend. So there's other ways to actually go on the offense without necessarily weaponizing it per se, right? Like using, bearing your own arms as you said, there there's different forms that people may not be aware of with that. And that actually gets into the world of, if you see attacks happening on your system, how you can use the security tools and collaborate with threat intelligence. >> I think that's the key. I think the key is these new sharing technologies around collective intelligence is going to be a great way to kind of have more of an offensive collective strike. But I think fortifying, the defense is critical. I mean, that's, there's no other way to do that. >> Absolutely, I mean, we say this almost every week, but it's in simplicity. Our goal is always to make it more expensive for the cybercriminal to operate. And there's many ways to do that, right? You can be a pain to them by having a very rigid, hardened defense. That means if it's too much effort on their end, I mean, they have ROIs and in their sense, right? It's too much effort on there and they're going to go knocking somewhere else. There's also, as I said, things like disruption, so ripping infrastructure offline that cripples them, whack-a-mole, they're going to set up somewhere else. But then also going after people themselves, again, the cash networks, these sorts of things. So it's sort of a holistic approach between- >> It's an arms race, better AI, better cloud scale always helps. You know, it's a ratchet game. Aamir, I want to get into this video. It's a ransomware four minute video. I'd like you to take us through as you the Lead Researcher, take us through this video and explain what we're looking at. Let's roll the video. >> All right. Sure. So what we have here is we have the victims that's top over here. We have a couple of things on this victim's desktop. We have a batch file, which is essentially going to run the ransomware. We have the payload, which is the code behind the ransomware. And then we have files in this folder. And this is where you would typically find user files and a real world case. This would be like Microsoft or Microsoft word documents, or your PowerPoint presentations, or we're here we just have a couple of text files that we've set up. We're going to go ahead and run the ransomware. And sometimes attackers, what they do is they disguise this. Like they make it look like an important word document. They make it look like something else. But once you run the ransomware, you usually get a ransom message. And in this case, a ransom message says, your files are encrypted. Please pay this money to this Bitcoin address. That obviously is not a real Bitcoin address. I usually they look a little more complicated, but this is our fake Bitcoin address. But you'll see that the files now are encrypted. You cannot access them. They've been changed. And unless you pay the ransom, you don't get the files. Now, as researchers, we see files like this all the time. We see ransomware all the time. So we use a variety of tools, internal tools, custom tools, as well as open source tools. And what you're seeing here is an open source tool. It's called the Cuckoo Sandbox, and it shows us the behavior of the ransomware. What exactly is ransomware doing. In this case, you can see just clicking on that file, launched a couple of different things that launched basically a command executable, a power shell. They launched our windows shell. And then at, then add things on the file. It would basically, you had registry keys, it had on network connections. It changed the disk. So that's kind of gives us a behind the scenes, look at all the processes that's happening on the ransomware. And just that one file itself, like I said, does multiple different things. Now what we want to do as a researchers, we want to categorize this ransomware into families. We want to try and determine the actors behind that. So we dump everything we know in a ransomware in the central databases. And then we mine these databases. What we're doing here is we're actually using another tool called Maldito and use custom tools as well as commercial and open source tools. But this is a open source and commercial tool. But what we're doing is we're basically taking the ransomware and we're asking Maldito to look through our database and say like, do you see any like files? Or do you see any types of incidences that have similar characteristics? Because what we want to do is we want to see the relationship between this one ransomware and anything else we may have in our system, because that helps us identify maybe where the ransomware is connecting to, where it's going to other processes that I may be doing. In this case, we can see multiple IP addresses that are connected to it. So we can possibly see multiple infections. We can block different external websites that we can identify a command and control system. We can categorize this to a family, and sometimes we can even categorize this to a threat actor as claimed responsibility for it. So it's essentially visualizing all the connections and the relationship between one file and everything else we have in our database. And this example, of course, I'd put this in multiple ways. We can save these as reports, as PDF type reports or usually HTML or other searchable data that we have back in our systems. And then the cool thing about this is this is available to all our products, all our researchers, all our specialty teams. So when we're researching botnets, when we're researching file-based attacks, when we're researching IP reputation, we have a lot of different IOC or indicators of compromise that we can correlate where attacks go through and maybe even detect new types of attacks as well. >> So the bottom line is you got the tools using combination of open source and commercial products to look at the patterns of all ransomware across your observation space. Is that right? >> Exactly. I showed you like a very simple demo. It's not only open source and commercial, but a lot of it is our own custom developed products as well. And when we find something that works, that logic, that technique, we make sure it's built into our own products as well. So our own customers have the ability to detect the same type of threats that we're detecting as well. At FortiGuard Labs, the intelligence that we acquire, that product, that product of intelligence it's consumed directly by our prospects. >> So take me through what what's actually going on, what it means for the customer. So FortiGuard Labs, you're looking at all the ransomware, you seeing the patterns, are you guys proactively looking? Is it, you guys are researching, you look at something pops in the radar. I mean, take us through what goes on and then how does that translate into a customer notification or impact? >> So, yeah, John, if you look at a typical life cycle of these attacks, there's always proactive and reactive. That's just the way it is in the industry, right? So of course we try to be (indistinct) as we look for some of the solutions we talked about before, and if you look at an incoming threat, first of all, you need visibility. You can't protect or analyze anything that you can see. So you got to get your hands on visibility. We call these IOC indicators of compromise. So this is usually something like an actual executable file, like the virus or the malware itself. It could be other things that are related to it, like websites that could be hosting the malware as an example. So once we have that SEED, we call it a SEED. We can do threat hunting from there. So we can analyze that, right? If we have to, it's a piece of malware or a botnet, we can do analysis on that and discover more malicious things that this is doing. Then we go investigate those malicious things. And we really, it's similar to the world of CSI, right? These different dots that they're connecting, we're doing that at hyper-scale. And we use that through these tools that Aamir was talking about. So it's really a lifecycle of getting the malware incoming, seeing it first, analyzing it, and then doing action on that. So it's sort of a three step process. And the action comes down to what Aamir was saying, waterfall and that to our customers, so that they're protected. But then in tandem with that, we're also going further and I'm sharing it if applicable to say law enforcement partners, other threat Intel sharing partners too. And it's not just humans doing that. So the proactive piece, again, this is where it comes to artificial intelligence, machine learning. There's a lot of cases where we're automatically doing that analysis without humans. So we have AI systems that are analyzing and actually creating protection on its own too. So it's quite interesting that way. >> It say's at the end of the day, you want to protect your customers. And so this renders out, if I'm a Fortinet customer across the portfolio, the goal here is protect them from ransomware, right? That's the end game. >> Yeah. And that's a very important thing. When you start talking to these big dollar amounts that were talking earlier, it comes to the damages that are done from that- >> Yeah, I mean, not only is it good insurance, it's just good to have that fortification. So Derek, I going to ask you about the term the last mile, because, we were, before we came on camera, I'm a band with junkie always want more bandwidth. So the last mile, it used to be a term for last mile to the home where there was telephone lines. Now it's fiber and wifi, but what does that mean to you guys in security? Does that mean something specific? >> Yeah, absolutely. The easiest way to describe that is actionable. So one of the challenges in the industry is we live in a very noisy industry when it comes to cybersecurity. What I mean by that is that because of that growing attacks for FIS and you have these different attack factors, you have attacks not only coming in from email, but websites from DoS attacks, there's a lot of volume that's just going to continue to grow is the world that 5G and OT. So what ends up happening is when you look at a lot of security operations centers for customers, as an example, there are, it's very noisy. It's you can guarantee almost every day, you're going to see some sort of probe, some sort of attack activity that's happening. And so what that means is you get a lot of protection events, a lot of logs. And when you have this worldwide shortage of security professionals, you don't have enough people to process those logs and actually start to say, "Hey, this looks like an attack." I'm going to go investigate it and block it. So this is where the last mile comes in, because a lot of the times that, these logs, they light up like Christmas. And I mean, there's a lot of events that are happening. How do you prioritize that? How do you automatically add action? Because the reality is if it's just humans doing it, that last mile is often going back to your bandwidth terms. There's too much latency. So how do you reduce that latency? That's where the automation, the AI machine learning comes in to solve that last mile problem to automatically add that protection. It's especially important 'cause you have to be quicker than the attacker. It's an arms race, like you said earlier. >> I think what you guys do with FortiGuard Labs is super important, not only for the industry, but for society at large, as you have kind of all this, shadow, cloak and dagger kind of attack systems, whether it's national security international, or just for, mafias and racketeering, and the bad guys. Can you guys take a minute and explain the role of FortiGuards specifically and why you guys exist? I mean, obviously there's a commercial reason you built on the Fortinet that trickles down into the products. That's all good for the customers, I get that. But there's more at the FortiGuards. And just that, could you guys talk about this trend and the security business, because it's very clear that there's a collective sharing culture developing rapidly for societal benefit. Can you take a minute to explain that? >> Yeah, sure. I'll give you my thoughts, Aamir will add some to that too. So, from my point of view, I mean, there's various functions. So we've just talked about that last mile problem. That's the commercial aspect. We created a through FortiGuard Labs, FortiGuard services that are dynamic and updated to security products because you need intelligence products to be able to protect against intelligent attacks. That's just a defense again, going back to, how can we take that further? I mean, we're not law enforcement ourselves. We know a lot about the bad guys and the actors because of the intelligence work that we do, but we can't go in and prosecute. We can share knowledge and we can train prosecutors, right? This is a big challenge in the industry. A lot of prosecutors don't know how to take cybersecurity courses to court. And because of that, a lot of these cyber criminals reign free, and that's been a big challenge in the industry. So this has been close my heart over 10 years, I've been building a lot of these key relationships between private public sector, as an example, but also private sector, things like Cyber Threat Alliance. We're a founding member of the Cyber Threat Alliance. We have over 28 members in that Alliance, and it's about sharing intelligence to level that playing field because attackers roam freely. What I mean by that is there's no jurisdictions for them. Cyber crime has no borders. They can do a million things wrong and they don't care. We do a million things right, one thing wrong and it's a challenge. So there's this big collaboration. That's a big part of FortiGuard. Why exists too, as to make the industry better, to work on protocols and automation and really fight this together while remaining competitors. I mean, we have competitors out there, of course. And so it comes down to that last mile problems on is like, we can share intelligence within the industry, but it's only intelligence is just intelligence. How do you make it useful and actionable? That's where it comes down to technology integration. >> Aamir, what's your take on this societal benefit? Because, I would say instance, the Sony hack years ago that, when you have nation States, if they put troops on our soil, the government would respond, but yet virtually they're here and the private sector has to fend for themselves. There's no support. So I think this private public partnership thing is very relevant, I think is ground zero of the future build out of policy because we pay for freedom. Why don't we have cyber freedom if we're going to run a business, where is our help from the government? We pay taxes. So again, if a military showed up, you're not going to see companies fighting the foreign enemy, right? So again, this is a whole new changeover. What's your thought? >> It really is. You have to remember that cyber attacks puts everyone on an even playing field, right? I mean, now don't have to have a country that has invested a lot in weapons development or nuclear weapons or anything like that. Anyone can basically come up to speed on cyber weapons as long as an internet connection. So it evens the playing field, which makes it dangerous, I guess, for our enemies. But absolutely I think a lot of us, from a personal standpoint, a lot of us have seen research does I've seen organizations fail through cyber attacks. We've seen the frustration, we've seen, like besides organization, we've seen people like, just like grandma's lose their pictures of their other loved ones because they kind of, they've been attacked by ransomware. I think we take it very personally when people like innocent people get attacked and we make it our mission to make sure we can do everything we can to protect them. But I will add that at least here in the U.S. the federal government actually has a lot of partnerships and a lot of programs to help organizations with cyber attacks. The US-CERT is always continuously updating, organizations about the latest attacks and regard is another organization run by the FBI and a lot of companies like Fortinet. And even a lot of other security companies participate in these organizations. So everyone can come up to speed and everyone can share information. So we all have a fighting chance. >> It's a whole new wave of paradigm. You guys are on the cutting edge. Derek always great to see you, Aamir great to meet you remotely, looking forward to meeting in person when the world comes back to normal as usual. Thanks for the great insights. Appreciate it. >> Pleasure as always. >> Okay. Keep conversation here. I'm John Furrier, host of theCUBE. Great insightful conversation around security ransomware with a great demo. Check it out from Derek and Aamir from FortiGuard Labs. I'm John Furrier. Thanks for watching.

>> Announcer: From theCUBE Studios in Palo Alto and Boston, connecting with thought leaders all around the world, this is theCUBE Conversation. >> Hi I'm John Furrier with theCUBE, we're here for a special CUBE Conversation. Obviously we're remote, we're in the studio most of the time but on the weekends I get an opportunity to talk to friends and experts. And here I wanted to really dig in with an awesome case study around AWS Cloud in a use case that I think is game changing for local communities, especially in this time of COVID. You have local communities where local journalism is suffering, but also connectedness. And connected experience is what's going to make the difference as we come out of this pandemic as a societal impact. But there's a real tech story here I want to dig into. We're here with Dan Drew who is the vice president of engineering for Clinical Didja, they make an app called Local BTV which basically takes over the air television and streams it to an app in your local area, enabling access to linear TV and on demand as well for local communities. It's a phenomenal project and it's unique. Somewhat misunderstood right now, but I think it's going to be something that's going to be very important. Dan, thank you for coming on and chatting with me. >> Thanks for having me, appreciate it. >> Okay so I'm a big fan, I've been using the app in San Francisco. I know New York's on the docket, it might even be deployed. You guys have a unique infrastructure capability that's powering this new app location, and this is the focus of this conversation in this CUBE Talk. Amazon is a big part of this. Talk about your local BTV that you are protecting, this platform for broadcast television, it has a unique hybrid cloud architecture. Can you tell us about that? >> Yeah certainly, I mean, one of our challenges, as you know, is that we are local television. So unlike a lot of products on the market, you know like your Hulus or other VMPV products, which primarily service sort of national feeds and things like that. We have to be able to receive over-the-air signals in each market. Many channels that serve local content are still over the air. And that is why you don't see a lot of them on those types of services. They tend to get ignored and unavailable to many users. So that's part of our value proposition is to not only allow more people to get access to these stations, but allow the stations themselves to reach more people. So that means that we have to have a local presence in each market in order to receive those signals. So that sort of forces us to have this hybrid model where we have local data centers, but then we also want to be able to effectively manage those in a central way, and we do that in our cloud platform which is hosted on Amazon and using Amazon services. >> All right let me take a breath here. You have a hybrid architecture on Amazon so since you're using a lot of the plumbing, take us through what the architecture of this ram is on using a variety of their services. Can you unpack that? >> Yeah, so obviously it starts with some of the core services like EC2, S3, RDS, which everybody on the planet uses. We're also very focused on using ECS; we're completely containerized which allows us to more effectively deploy our services and scale them. And one of the benefits on that front that Amazon provides is that because their container service is wired into all the other services like cloudwatch metrics, auto-scaling policies, IM policies, things like that. It means it allows us to manage those things in a much more effective way, and use those services to much more effectively make those things reliable and scalable. We also use a lot of their technologies, for example, for collecting metrics. So we use Kinesis and Redshift to collect realtime metrics from all of our markets across the U.S. That allows us to do that reliably and at scale without having to manage complex ETL systems like Kafka and other things. As well as store it in a large data lake like Redshift and Corid for analytics and things like that. We also use technologies like Media Tailor, so for example, one of the big features that most stations do not have access to is realtime targeted advertising. In the broadcast space, many ads are sold and placed weeks in advance, and not personalized obviously for that reason. Whereas one of the big features we can bring to the table using our system and technologies like Media Tailor is we can provide realtime targeted advertising which is a huge win for these stations. >> What are some of the unique capabilities that you guys can offer broadcast station partners 'cause you're basically going in and partnering with broadcast stations as well. But also you're enabling new broadcasters to jump in as well. What are some of the unique capabilities that you're delivering, what is Amazon bringing to the table there and what are you doing that's unique? >> Well again, it allows us, because we can do things centrally as well as the local reception, it allows us to do some interesting things like if we have channels that are allowed to broadcast even outside their market, then we can easily put them in other markets and get them even more viewers that way. We have the ability to even do hyper local or community channels that are not necessarily broadcasting all of the standard antennas, but can get us a feed from whatever zip code in whatever market, and we can give them a way to reach viewers in the entire market, in other markets, or even just in their local area. So consider the case where maybe a high school or a college wants to show games or local content, we provide a platform where they can now do that, and reach more people using our app and our platform very very easily. So that's another area that we want to help expand is not just your typical view of local of what's available in Phoenix, but what's available in a particular city in that area or a local community where they want to reach their community more effectively or even have content that might be interesting to other communities in Phoenix or one of the other markets. >> Now I think, just going on a side tangent here, I talked with your partner, Jim Long, who's the CEO, you guys have an amazing business opportunity. Again, I think it's kind of misunderstood, but it's very clear to me that someone who follows and has huge passion about local journalism, you know you see awesome efforts out there like Charlie Sennott from the Ground Truth Project Report for America, they take a journalism kind of print view, but if you add that Didja business model onto this local journalism, you can enable more video locally. I mean, that's really the killer app, video. And now COVID more than ever, I really want to know things like there's a mural in downtown Palo Alto, Black lives matter, I want to know what's going on with the local summer restaurants, putting people out on the sidewalks. Right now I'm limited to like next door or very laggy media, whether it's the website, so again, I think this is an opportunity for that, plus education. I mean, Amazon educate for instance, you can get a degree on computing by sitting on the couch. So again, this is a paradigm shift from an application standpoint that you're providing essentially linear TV to that. >> Exactly. >> In the local economy. So I just want to give you a shout-out for that because I think it's super important. I think people should get behind this, so congratulations. Okay I'm off on my little rant there. Let's get back down to some of that cloud stuff 'cause I think what's super interesting to me is you guys can stand up infrastructure very quickly, and what you've done here, you've leveraged the benefits of Amazon and the goodness of cloud, you essentially can stand up a metro region pretty quickly and pretty impressive. So I got to ask you, what Amazon services are most important for your business? >> Well like I said, I think for us, it's managing the central services so we sort of talked about managing the software, the APIs, and those are kind of the glue, so for us standing up a new metro is obviously getting the data center contracts and all the other messy stuff you have to deal with, just to have a footprint. But essentially once we have that in place, we can spin up the software in the data center and have it hooked into our central service within hours. And we can be starting channels literally within half a day. So that's the real win for us is having all that central glue and that central management system and the scalability where we can just add another 10, 20, 50, 100 markets and the system is set up to scale centrally where we can start collecting metrics through Cloud watch from those data centers, we're collecting logs and diagnostic information so we can detect health and everything else centrally and monitor and operate all of these things centrally in a way that is sane and not crazy. We don't need a 24/7 knock of a thousand people to do this, you know, and do that in a way that we, as a relatively small company, can still scale and do that in a sensible way, and a cost-effective way, which is obviously very important for us at our size, but at any size, you want to make sure if you're going to go into 200 plus markets that you have a really good cost model and that's one of the things where Amazon has really really helped us is allow us to do some really complex things, and in an efficient, scalable, reliable, and cost-effective way. The cost for us to go into a new metro now is so small relatively speaking that that's really what allows us to do as a business and now we just opened up New York and we're going to keep expanding on that model so that's been a huge win for us is evaluating what Amazon can bring to the table versus other third parties or building our own obviously-- >> So Amazon gives you the knock basically leverage and scale. The data center you're referring to, that's pretty much just to get an origination point in the territory. >> Dan: Exactly, that's right. >> So it's not like it's a super complex data center. You can just go in, making sure that they got all the normal path to recovery and the normal stuff, it's not like a heavy duty buildup. Can you explain that? >> Yeah, so one thing we do do in our data centers is because we are local, we have sort of primary data centers where we do do transcoding and origination of the video so we receive the video locally and then we want to transcode and deliver it locally and that way we're not sending video across the country and back type of thing. So that is sort of the hybrid part of our model. So we stand that up, but then that is all managed by the central service. So we essentially have another container cluster using Kubernetes in this case. But that Kubernetes cluster is essentially told what to do by everything that's running in Amazon. So we essentially stand up the Kubernetes cluster, we wire it up to the central service, and then from then on, we just go into the central service and say stand up these channels and it all pops up. >> Well my final question on the Amazon piece is really about the future capability besides having a CUBE channel which we'd love to have on there, I told my guys we'll get there. But we're just too busy working around the clock as you guys are with COVID-19. (overlapping chatter) I could almost see a slew of new services coming out, just on the Amazon side. If I'm on the Amazon side I'm thinking, okay I'll post this as an opportunity for me. I can see sage making and machine learning coming in and adding value for the user experience. And also enabling their own stuff. They've got a ton of stuff with Prime and moving people around and delivering things. I mean the headroom for Amazon in this thing is off the charts. But that being said, that's Amazon, I could see them winning with this. I know certainly I know you're using Elemental as well, but for you guys on the consumer side, what features and what new things do you see on the roadmap or what you might envision the future looking like? >> Well, I think part of it I think there's two parts. One of it is what are we going to deliver ourselves so we talked about adding community content and continuing to evolve the local BTV product. But we also see ourselves primarily as a local TV platform. For example, you mentioned Prime and a lot of people are now realizing, especially with COVID and what's going on, the importance of local television and so we're in discussions on a lot of fronts with people to see how we can be the provider of that local TV content. And that's really a lot of stations are super excited about that too 'cause you know, again, looking to expand their own footprint and their own reach, we're basically the way that we can join those two things together between the stations, the other video platforms, and distribution mechanisms, and the viewers obviously at the end of the day, we want to make sure local viewers can get more local content and stuff that's interesting to them. Like you said with the news, it is not uncommon that you may have your Bay area stations but the news is still maybe very focused on LA or San Francisco or whatever. And so being able to enable the smaller regional outlets to reach people in that area in a more local fashion is definitely a big way that we can facilitate that from the platform and viewer perspective. So we're hoping to do that in any way we can. Our main focus is make local great and get the broadcast world out there and that's not going anywhere especially with things like HSE3 on the front, and we just want to make sure those people are successful and enrich people and make revenue. >> Yeah, you got a lot of (mumbles) but I think one of the things that's interesting about your project that I find is a classic case of people who focus in on just current market value investing, versus kind of the game-changing shifts is that you guys are horizontally enabling in the sense that there's so many different use cases I was pointing out from my perspective, journalism, and I look at that and I'm like, okay that's a huge opportunity just there, changing the game on societal impact on journalism, huge education opportunity for court cutters. You're talking about a whole nother thing around TV so I got to ask ya, pretend I'm an idiot for a minute. Pretend, let's make it, I am an idiot. I don't understand, isn't this just TV? What are you doing different because it's only local. I can't watch San Francisco if I'm in Chicago and I can't watch Chicago if I'm in San Francisco, I get that. But why is this important? Isn't this just TV? Can't I just get it on YouTube, TikTok, what is this? >> Yes and no. There's TV and then there's TV as you know. If you look at the TV landscape, it's pretty fractured but typically when you're talking about YouTube or Hulu, you're talking about sort of cable TV channels. You know, you're going to get your A&E, you're going to get some of your local through ABC and whatnot, but you're not really getting local content. So for example, in our Los Angeles market, there are about 100 and something over-the-air channels. If you look at the cross section of which of those channels you can get on your other big name products like your Hulus or your YouTube TV, you're talking about maybe half a dozen or a dozen. So we're talking about 90 plus channels that are local to LA that you can only get through an antenna. And those are hitting the type of demographics that, quite frankly, some of these other players just don't see as important. >> Under different minorities or immigrants, the each entrepreneurs of our country. >> Yes exactly, so we might see a lot of Korean channels or Spanish channels or other minority channels that you just won't get over your cable channels or your typical online video providers. So that's, again, why we feel like we've got something that is really unique and that is really under-served as far as on a television standpoint. The other side that we bring to the table is that a lot of these broadcast channels are under served themselves in terms of technology. If you look at ad insertion and a lot of the technical discussions about how to do live TV and how to get live TV out there, it's very focused on the OTT market, so again, going back to the Hulus and the YouTubes. >> OTT, over-the-top you mean. >> Over the top, yeah. And so this broadcast market basically had no real evolution on that front in a while and I sort of mentioned the way ad buying works. It's still sort of the traditional ad buying that happens a couple weeks in front, not a lot of targeted or anything ability. And even when we get to HSE3, you're now relying on having an HES3 TV and you're still tied to an antenna, etc, etc, which is, again, a good move forward, but still not covering the spectrum of what these guys really want to reach and do. So that's where we kind of fill in the gaps using technology and filling in the gap of receiving a signal and bringing these technologies to not only the ad insertion and the stuff we can do for the livestream, but providing analytics and other tools to the stations that they really don't have right now unless you're willing to shell out a lot of money for Nielsen, which a lot of local small stations don't do. So we can provide a lot of analytics on viewership and targeting and things like that that they're really looking forward to and really excited about. >> All right, I got to ask you, put you on the spot here, 'cause I always see Andy Jassy at (mumbles) hopefully I'll see him this year if they do an in-person event. He's really dynamic and you should send him an email; he tends to read his emails a lot, and if you're a customer and I know you are, but I've got to ask you, if you bumped into Andy Jassy on the elevator and he's like, hey why should I pay attention to Didja? Why is it important for Amazon and why is it important for the world? How does it raise the bar on society? >> Well I think part of what Amazon's goal, especially if you get into their work in public sector and education, that's really where we see we're focusing with the community and local television and enabling new types of local television. So I think there's a lot of advantage and I hate the word synergy, but I'm going to use the word synergy. As far as our goals in those areas around really helping, one of the terms flying around now is the double bottom line where it's not just about revenue, it's about how do we help people in communities be better as well? So there's a bottom line in terms of people, benefit, and revenue in that way, not just financial revenue. And that's very important to us as a business as well is that's why we're focused on local TV and we're not just doing another Fubo where it's really easy to get an IP national fee. It's really important to us to enable the local community and the local broadcasters and the local channels and the local viewers to get the content that they're missing out on right now. So I think there's a, I hate it but I'm going to use it, synergy on that front as far as-- >> Synergy and the new normal. >> Synergy and the new normal? I think COVID and some of the other things that have been happening in the news with the Black Lives Matter and a lot of the things going around where local and community has been in the spotlight and getting the word out and having really local things versus I'm just seeing this thing from three counties away which I don't really care about and it's not telling me what's happening down the street like you said. And that's really what we want to help improve and support. >> Yeah it's a great mission, and it's one we care a lot about theCUBE. We've seen the data: content drives community engagement, and community's where the truth is. So in an era when we need more transparency and more truth, you get more cameras on the street, you're going to start to see things. That's what we're seeing a lot of things. And as more data's exposed, as you turn the lights on, so to speak, that kind of data will only help communities grow, heal, and thrive. So to me, big believer in what you guys are doing. Local BTV has a great mission. I wish you guys well and thanks for explaining the infrastructure on Amazon. I think you guys have a really killer use case technically. I mean to me, I think the technical superiority of what you've done give ability to stand up to these kinds of network with massive number of potential reach out of the gate, that's pretty impressive, congratulations. >> Great, thank you very much and thanks for taking the time. (upbeat music)

>>from the Cube Studios in Palo Alto and Boston connecting with thought leaders all around the world. This is a cube conversation. Hi, I'm John Furrier with the Cube. We're here for a special cube conversation about seeing with remote where Studio most of the time. But on the weekends we get an opportunity to talk to friends and experts, and he I wanted to really dig in with an awesome case study around AWS Cloud in a use case that I think is game changing for local community, especially this time of Cove. It you have local community work, local journalism suffering, but also connectedness and connected experiences was going to make. The difference is we come out of this pandemic a societal impact. But there's a real tech story here I want to dig into. We're here with Dan. True is the vice president of engineering for chemical Didja. They make an app called local Be TV, which basically takes over the air television and stream it to an app in your local area, enabling access to linear TV and on demand as well. For local communities. It's a phenomenal project, and it's unique, somewhat misunderstood right now, but I think it's going to be something that's going to really put Dan, thank you for coming on and chatting with >>Thanks for having me appreciate it. >>Okay, so I'm a big fan. I've been using the APP in San Francisco. I know New York's on the docket might be deployed. You guys have a unique infrastructure capability that's powering this new application, and this is the focus of the conversations. Q. Talk Amazon is a big part of this talk about your local BTV that you architect with this platform for broadcast television as a unique hybrid cloud architecture. Can you tell us about that? >>Certainly. I mean, one of our challenges, as you know, is that we are local television eso. Unlike a lot of products on the markets, you know, like your Hulu's or other VM PV products, which primarily service sort of national feeds and things like that, we have to be able to receive, um, over the air signals in each market. Um, many channels that serve local content are still over the air, and that is why you don't see a lot of them on those types of services. They tend to get ignored and available to many users. So that's part of our value. Proposition is to not only allow more people to get access to these stations, but, uh, allow the stations themselves to reach more people. So that means that we have to have a local presence in each market in order to receive those signals. Uh, so that's sort of forces us to have this hybrid model where we have local data centers. But then we also want to be able to effectively manage those in a central way. Uh, and we do that in our cloud platform, which is hosted on Amazon and using Amazon services. >>Let me take take a breath. Here. You have a hybrid architecture on Amazon so that you're using a lot of the plumbing, take us through what the architecture is. RAM is on using a variety of their services. Can you unpack that? >>Yeah. So, um, obviously it starts with some of the core services, like easy to s three RDS, which everybody on planet uses. Um, we're also very focused on using e CS. We're completely containerized, which allows us to more effectively deploy our services and scale them. Um, and one of the benefits on that front that Amazon provides is that because they're container services wired into all the other services, like cloud watch metrics, auto scaling policies, I am policies, things like that. It means it allows us to manage those things in a much more effective way. Um, and use those services too much more effectively make those things reliable and scalable. Um, we also use a lot of their technologies, for example, for collecting metrics. So we use kinesis and red shift to collect real time metrics from all of our markets across the US that allows us to do that reliably and at scale without having to manage complex detail systems like Kafka and other things. Um, as well, it's stored in a large data lake like red shift in Korea for analytics. And you know, things like that. Um, we also use, um, technologies like media Taylor s. So, for example, one of the big features that most stations do not have access to Israel. Time targeted advertising in the broadcast space. Many ads are sold and placed weeks in advance. Um, and not personalized, obviously. You know, for that reason, where is one of the big features we can bring to the table using our system and technologies like Media Taylor is we can provide real time targeted advertising, which is a huge win for these stations. >>What are some of the unique capabilities that you guys offer? Broadcast station partners? Because you're basically going in and partnering with broadcast ages as well. But also you're enabling new broadcasters to jump in, and it's well, what are some of the unique capabilities that you're delivering? What is Amazon brings to the table there. What are you doing that >>well again, it allows us because we can do things centrally. You know as well as the local reception. It allows us to do some interesting things. Like if we have channels that, um, are allowed to broadcast even outside their market, Um, then we could easily put them in other markets and get them even more of years. That way we have the ability to even do, like hyper local or community channels, you know that are not necessarily broadcasting over the standard antennas, um, but can get us a feed from, you know, whatever zip code and whatever market and we can give them a way to reach viewers in the entire market and other markets, or even just in their local area. So, you know, consider the case where maybe a high school or college you know, wants to show games or local content. Um, we provide a platform where they can now do that and reach more people, Um, using our app in our platform very, very easily. So that's another area that we want help Expand is not just your typical view of local of what's available in Phoenix, Um, but what's available in a particular city in that area or a local community where they want to reach their community more effectively or even have content that might be interesting to other communities in Phoenix or one of the other markets. >>You know, I think just is not going to side tangent here. I talked with your partner, Jim Long, who's the CEO? You guys have an amazing business opportunity again. I think it's kind of misunderstood, but it's very clear to me that follows in. It has huge passion of local journalism. You see awesome efforts out there by Charlie Senate from the Ground Truth Project report for America. They take a journalism kind of friend view. But if you add like that digital business model onto this local journalism, you can enable more video locally. I mean, that's really the killer app of video. And now it Koven. More than ever. I really want to know things like this. A mural downtown Palo Alto. Black lives, matters. I want to know what's going on. Local summer restaurants, putting people out of sidewalks. Right now I'm limited to, like, next door or very Laghi media, whether it's the website. So again, I think this is an opportunity to that plus education. I mean, Amazon education, for instance. You can get a degree cloud computing by sitting on the couch. So you know, this is again. This is a paradigm shift from an application standpoint, but you're providing essentially linear TV to app because in the local economy, So I just want to give you a shout out for that because I think it's super important. I think you know, people should get behind this, so congratulations, Okay, I'm often my little rant there. Let's get back down to some of that cloud stuff. So I think it's super interesting to me is you guys can stand up infrastructure very quickly. And what you've done here, you can leverage the benefits of Amazon. Goodness of cloud. You essentially can stand up a metro region pretty quickly. Try it. And it pretty impressive. So I gotta ask you what? Amazon services are most important for your business. >>Um, well, like I said, I think for us it's matching the central services. So we sort of talked about, uh, managing the software, the ap eyes, Um, and those are kind of the glue. So, you know, for us standing up a new metro is obviously, you know, getting the data center contracts and all the other you know, >>and >>ask yourself, you have to deal with just have a footprint. But essentially, once we have that in place, we can spin up the software in the data center and have it hooked into our central service within hours. Right? And we could be starting channels literally, literally within half a day. Um, so that's the really win for us is, um, having all that central blue and that central management system and the scalability where, you know, we can just add another 10 20 5100 markets. And the system is set up to scale centrally, um, where we can start collecting metrics the cloudwatch from those data centers. We're collecting logs and diagnostic information s so we can detect health and everything else centrally and monitor and operate all of these things centrally in a way that is saying and not crazy. We don't need a 24 7 knock of 1000 people to do this. Um, you know, and do that in a way that, you know, we as a relatively small company can still scale and do that in a sensible way in a cost effective way, which is obviously very important for us at our size. But at any size, um, you want to make sure if you're gonna go into 200 plus markets, that you have a really good cost model. Um and that's one of the things that where Amazon has really really helped us is allow us to do some really complex things in an efficient, scalable, reliable and cost effective way. You know, the cost for us to go into the new metro now is so small, you know, relatively speaking, but that's really allows. What allows us to do is the business of now. We just opened up New York, you know, and we're going to keep expanding on that model. So that's been a huge win for us. Is evaluating what Amazon can bring to the table versus other third parties, and we're building our own, you know, obviously which >>So Amazon gives you the knock, basically leverage and scale the data center you're referring to. That's pretty much just to get an origination point in the Derek. Exactly. That's right. So it's not like it's a super complex data center. You can just go in making sure they got all the normal backup recovery in the normal stuff. It's not like a heavy duty build up. Can you explain that? >>Yeah. So one thing we do do in our data centers is because we are local. Um, we have sort of primary data centers where we do do trans coding and origination of the video. So we receive the video locally, and then we want to transport and deliver it locally. And that way we're not sending video across the country and back try to things so that That is sort of the hybrid part of our model. Right? So we stand that up, but then that is all managed by the central service. Right? So we essentially have another container cluster using kubernetes in this case. But that kubernetes cluster is essentially told what to do by everything that's running in Amazon. So we essentially stand up the kubernetes cluster, we wire it up to the Central Service, and then from then on, it just we just go into the Central Service and say, Stand up these channels. Um and it all pops up >>with my final question on the Amazon piece is really about future capabilities Besides having a Cube channel, which I would love to have gone there. And I told my guys, We'll get there, but it's just too busy working around the clock is You guys are with Kobe tonight? Yeah, sand. I can almost see a slew of new services coming out just on the Amazon site. If I'm on the Amazon site, I'm thinking, okay, Outpost is the opportunity for me. I got stage maker machine learning coming in and value for user experience and also, you know, enabling their own stuff. They've got a ton of stuff with prime moving people around and delivering the head room for Amazon. This thing is off the charts. But that being said, that's Amazon could see them winning with this and certainly, you know, using elemental as well. But for you guys on the consumer side, what features and what new things do you see on the road map or what? You might envision the future looking like, >>Well, I think part of it. I think there's two parts. One is what are we gonna deliver ourselves, you know. So we talked about adding community content and continuing to evolve the local beauty product. Um, but we also see ourselves primarily as a local TV platform. Um, and you know, for example, you mentioned prime. And a lot of people are now realizing, especially with Cove, it and what's going on the importance of local television. Uh, and so we're in discussions on a lot of fronts with people to see how how we can be the provider of that local TV content. You know, um and that's really a lot of stationed. Are super excited about that, too, because, you know, again looking to expand their own footprint and their own reach. You know, we're basically the way that we can join those two things together between the stations, the other video platforms and distribution mechanisms and the viewers. Obviously, at the end of the day, um, you know, we want to make sure local viewers can get more local content and stuff that's interesting to them. You know, Like you said with the news, it is not uncommon that you may have your Bay Area stations, but the news is still may be very focused on L. A or San Francisco or whatever, Um and so being able to enable, uh, you know, the smaller regional outlets to reach people in that area in a more local fashion. It is definitely a big way that we can facilitate that from the platform. And you were perspective. So we're hoping to do that in any way we can. You know, our main focus is make local great, you know, get the broadcast world out there, and that's not going anywhere, especially with things like HSC tree. Uh, you know, on that front, um, and you know, we just want to make sure that those people are successful, um, and can reach people and revenue and, you know, >>you got a lot of uncertainty, But I think one of the things that's just think about your project that I find is a classic case of people who focus in on that just the current market value, investing versus kind of game changing shifts is that you guys are horizontally enabling in the sense that there's so many different use cases. I was pointing out from my perspective, journalism. I'm like, I look at that and I'm like, Okay, that's a huge opportunity. Just they're changing the game on Societal impact on journalism, Huge education, opportunity for cord cutters. You're talking about a whole nother thing around TV. So I gotta ask you, you know, pretend I'm an idiot for a minute. Why are pretending that this person from this making I am entity after I don't understand it? Isn't this just TV? What are you doing Different? Because it's only local. I can't watch San Francisco. I'm in Chicago and I can't watch Chicago. I'm in San Francisco. I get that. You know why? Why is this important? Isn't this just TV can I just get on YouTube? I mean, tech talk. Well, talk about the yes >>or no. I mean, there's a TV, and then there's TV, You know, as you know, um and, you know, if you look at the TV landscape just pretty fracture. But typically, when you're talking about YouTube or who you're talking about, sort of cable TV channels, you know you're going to get your Andy, you're gonna get some of your local to ABC and what not? Um, but you're not really getting local contact. And So, for example, in our Los Angeles market, um, we there are There are about 100 something over the air channels. If you look at the cross section of which of those channels you can get on your other big name products like you lose your YouTube TV, you're talking about maybe half a dozen or a dozen, right? So there's like 90 plus channels that are local to L. A. That you can only get through an antenna, right? And those were hitting the type of demographics. You know, quite frankly, some of these other players or just, you know, don't see is important >>under other minorities exact with immigrants. You know, the entrepreneurs of our country? Yes, >>exactly. You know, So, you know, we see a lot of Korean channels or Spanish channels or other. You know, um, minority channels that you just won't get over your cable channels or your typical online video providers. So that's again Why, You know, we feel like we've got something that is really unique. Um, and that is really underserved, you know, as far as on a television sampling, Um, the other side that we bring to the table is that a lot of these broadcast channels, our underserved themselves in terms of technology, Right, if you look at, you know, ad insertion, um and you know a lot of the technical discussions about how to do live TV and how to get live TV out there. It's very focused on the OT market. So again, going back to who lose, and >>then you take a little over the top with the >>over the top. Yeah. Um and so this broadcast market basically had no real evolution on that front in a while. You know, I sort of mentioned like the way ad buying works, you know, it's still sort of the traditional and buying that happens a couple weeks in front, Not a lot of targeted or anything ability. Um, And even when we get to the HSC three, we're now relying on having an h A street TV and you're still tied to an antenna, etcetera, etcetera, which is again, a good move forward, but still not covering the spectrum of what these guys really want to reach and do. So that's where we kind of fill in the gaps, you know, using technology and filling in the gap of receiving a signal and bringing these technologies. So not only the ad insertion and stuff we can do for the live stream, Um, but providing analytics and other tools to the stations, uh, that they really don't have right now, unless you're willing to shell out a lot of money for Neilson, which a lot of local small stations don't do. Uh, so we can provide a lot of analytics on viewership and targeting and things like that that really looking forward to and really excited >>about. I gotta ask you put you on the spot here because I don't see Andy Jassy at reinvent might Hopefully I'll see in this year. They do a person event. He's really dynamic. And you just said, I mean, I think he tends to read his emails a lot. And if you're a customer and you are. But if you bumped into Andy Jassy on the elevators like okay, why should I pay attention to digital? What's why is it important for Amazon? And why is it important for the world? How do you raise the bar on society? >>Well, I think part of what Amazon's goal. And you know, especially if you get into, you know, their work in public sector on education. Um, you know, that's really where we see we're focusing with the community on local television and enabling new types of local television. So I think there's a lot of advantage, and, um, I hate the word synergy, but I'm gonna use the word synergies, you know, um, this for us, You know, our goals in those areas around really helping, you know, uh, you know, one of the terms flying around now is the double bottom line where it's not just about revenue. It's about how do we help people in communities be better as well. Um, so there's a bottom line in terms of uh huh. People benefit and revenue in that way, not just financial revenue. Right. And you know, that's very important to us as a business as well is, you know, that's why we're focused on local TV. And we're not just doing another food. Go where it's really easy to get a nightie national feed. You know, it's really important to us to enable the local community and the local broadcasters and local channels and the local viewers to get the content, um that they're missing out on right now. Um, so I think there's a your energy on that front. Um, as >>far synergy and the new normal to have energy in the new normal. You know, I think I think >>of it. And, you know, um, and some of the other things that have been happening in the news of the black lives matter And, um, you know, a lot of things going around where you know, local and community has been in the spotlight, right? And getting the word out and having really local things versus hundreds. Seeing this thing from you know, three counties away which I don't really care about. It's not telling me what's happening down the street, like you said, Um, and that's really what we want to help improve and support. >>Yeah, no, it's a great mission is one. We care a lot about the Cube. We've seen the data content drives, community engagement and communities where the truth is so in an era where we need more transparency and more truth, you get more cameras on the street, you're going to start to see things, and that's what we're seeing. A lot of things. And as more data is exposed as you turn the lights on, so this week that kind of data will only help communities grow, heal and thrive. So to me, a big believer in what you guys are doing local BTV is a great mission. I wish you guys well, and thanks for explaining the infrastructure on Amazon. I think you guys have a really killer use case. Technically, I mean to me, I think the technical superiority, what you've done, the ability to stand up these kinds of networks with massive number potential reach out of the gate. It's just pretty impressive. Congratulations, >>right? Thank you very much. And thanks for taking the time. >>Okay. Dan Drew, vice president of Jennifer. Did you start up That a lot of potential will. See. Let's go check out the comments on YouTube while we're here. Since we got you, let's see what's going on in the YouTube front year. Yeah, The one question was from someone asked me Was from TV serious that Dan, Great to see you. Thanks for taking the time on Sunday and testing out this new zoom home recording my home studio. But you got to get cleaned up. Thanks for taking the time Problem. Okay, Take care. Yeah. Yeah, yeah, yeah.

>> Narrator: From around the globe, it's theCUBE with digital coverage of AWS Public Sector Online. Brought to you by Amazon Web Services. >> Welcome back to the coverage of AWS Public Sector Summit virtual. I'm John for host of theCUBE. We're here in theCUBE studios, quarantine crew here talking to all the guests remotely as part of our virtual coverage of AWS Public Sector. So I've got a great guest here talking about data science, weather predictions, accurate climate modeling, really digging into how cloud is helping science. Dr. Chelle Gentemann, who is a senior scientist at Farallon Institute is my guest. Chelle, thank you for joining me. >> Thank you. >> So tell us a little about your research. It's fascinating how, I've always joked in a lot of my interviews, 10, 15, 20 years ago, you need super computers to do all these calculations. But now with cloud computing, it opens up so much more on the research side and the impact is significant. You're at an awesome Institute, the Farallon Institute, doing a lot of stuff in the sea and the ocean and a lot of your things. What's your focus? >> I study the ocean from space, and about 71% was covered by ocean. 40% of our population in the globe actually lives within 100 kilometers of the coast. The ocean influences our weather, it influences climate, but it also provides fisheries and recreational opportunities for people. So it's a really important part of the earth system. And I've been focused on using satellites. So from space, trying to understand how the ocean influences weather and climate >> And how new is this in terms of just state of the art? Fairly new, been around for a while? What's some of the progress for the state of the art we're involved in. >> I started working on satellite data in the 90s during school, and I liked the satellite data cause it's the interface of sort of applied math, computer science and physics. The state of the art is that we've really had remote sensing around for about 20, 30 years. But things are changing because right now we're having more sensors and different types of instruments up there and trying to combine that data is really challenging. To use it, our brain is really good in two and three dimensions, but once you get past that, it's really difficult for the human brain to try and interpret the data. And that's what scientists do. Is they try and take all these multidimensional data sets and try to build some understanding of the physics of what's going on. And what's really interesting is how cloud computing is impacting that. >> It sounds so exciting. The confluence of multiple disciplines kind of all right there, kind of geek out big time. So I've got to ask you, in the past you had the public data set program. Are you involved in that? Do you take advantage that research? How is some of the things that AWS is doing help you and is that public data set part of it? >> It's a big part of it now. I've helped to deploy some of the ocean temperature data sets on the cloud. And the way that AWS public data sets as sort of has potential to transform science is the way that we've been doing science, the way that I was trained in science was that you would go and download the data. And most of these big institutions that do research, you start to create these dark repositories where the institutions or someone in your group has downloaded data sets. And then you're trying to do science with these data, but you're not sure if it's the most recent version. It makes it really hard to do reproducible science, because if you want to share your code, somebody also has to access that data and download it. And these are really big data sets. So downloading it could take quite a long time. It's not very transparent, it's not very open. So when you move to a public data set program like AWS, you just take all of that download out of the equation. And instantly when I share my code now, people can run the code and just build on it and go right from there, or they can add to it or suggest changes. That's a really big advantage for trying to do open science. >> I had a dinner with Teresa Carlson who is awesome. She runs the Public Sector Summit for AWS. And I remember this was years ago and we were dreaming about a future where we would have national parks in the cloud or this concept of a Yosemite-like beautiful treasure. Physical place you could go there. And we were kind of dreaming that, wouldn't it be great to have like these data sets or supercomputer public commons. It sounds like that's kind of the vibe here where it's shareable and it's almost like a digital national park or something. Is that it's a shared resource. Is that kind of happening? First of all, what do you react to that? And what's your thoughts around that dream? And does this kind of tie to that? >> Yeah, I think it ties directly to that. When I think about how science is still being done and has been done for the past sort of 20 years, we had a real change about 20 years ago when a lot of the government agencies started requiring their data to be public. And that was a big change. So then we got, we actually had public data sets to work with. So more people started getting involved in science. Now I see it as sort of this fortress of data that in some ways have prevented scientists from really moving rapidly forward. But with moving onto the cloud and bringing your ideas and your compute to the data set, it opens up this entire Pandora's box, this beautiful world of how you can do science. You're no longer restricted to what you have downloaded or what you're able to do because you have this unlimited compute. You don't have to be at a big institution with massive supercomputers. I've been running hundreds of workers analyzing in my realm. Over two or 300 gigabytes of data on a $36 Raspberry Pi that I was playing around with my kids. That's transformative. That allows anyone to access data. >> And if you think about what it would have to do to do that in the old days, stack and spike servers. Call, first of all, you'll get the cash, buy servers, rack them and stack them, connect to a download of nightmare. So I got to ask you now with all this capability, first of all, you're talking to someone who loves the cloud. So I'm pretty biased. What are you doing now with the cloud that you couldn't do before? So certainly the old way from a provisioning standpoint, check, done. Innovation, bars raised. Now you're creative, you're looking at solutions, you're building enabling device like a Raspberry Pi, almost like a switch or an initiation point. How has the creativity changed? What can you do now? What are some of the things that are possible that you're doing? >> I think that you can point to within some of the data sets that have already gone on the cloud are being used in these really new, different ways. Again, it points to this, when you don't have access to the data, just simply because you have to download it. So that downloading the data and figuring out how to use it and figuring out how to store it is a big barrier for people. But when things like the HF Radar data set went online. Within a couple of months, there was a paper where people were using it to monitor bird migration in ways that they'd never been able to do before, because they simply hadn't been able to get the data. There's other research being done, where they've put whale recordings on the cloud and they're using AI to actually identify different whales. It's using one data set, but it's also the ability to combine all these different data sets and have access to them at the same time and not be limited by your computer anymore. Which for a lot of science, we've been limited by our access to compute. And that when you take away that, it opens all these new doors into doing different types of research with new types of data, >> You could probably correlate the whale sounds with the temperature and probably say, hey, it's cold. >> Chelle: Exactly. >> I'm making that up. But that's the kind of thing that wouldn't be possible before because you'd have to get the data set, do some math. I mean, this is cool stuff with the ocean. I mean, can you just take a minute to share some, give people an insight in some of the cool projects that are being either thought up or dreamed up or initiated or done or in process or in flight, because actually there's so much data in the ocean. So much things to do, it's very dynamic. There's a lot of data obviously. Share, for the folks that might not have a knowledge of what goes on. What are you guys thinking about? >> A lot of what we're thinking about is how to have societal impact. So as a scientist, you want your work to be relevant. And one of the things that we found is that the ocean really impacts weather at scales that we simply can't measure right now. So we're really trying to push forward with space instrumentation so that we can monitor the ocean in new ways at new resolutions. And the reason that we want to do that is because the ocean impacts longterm predictability in the weather forecast. So a lot of weather forecasts now, if you look out, you can go on to Weather Underground or whatever weather site you want. And you'll see the forecast goes out 10 days and that's because there's not a lot of accuracy after that. So a lot of research is going into how do we extend into seasonal forecast? I'm from Santa Rosa, California. We've been massively impacted by wildfires. And being able to understand how to prepare for the coming season is incredibly important. And surprisingly, I think to a lot of people, the ocean plays a big role in that. The ocean can impact how much storm systems, how they grow, how they evolve, how much water they actually got. Moisture they pick up from the ocean and then transport over land. So if you want to talk about, it's really interesting to talk about how the ocean impacts our weather and our seasonal weather. So that's an area where people are doing a lot of research. And again, you're talking about different data sets and being able to work together in a collaborative environment on the cloud is really what's starting to transform how people are working together, how they're communicating and how they're sharing their science. >> I just hope it opens up someone's possibilities. I want to get your vision of what you think the breakthroughs might be possible with cloud for research and computing. Because you have kind of old school and new school. Amazon CEO, Andy Jassy calls it old guard, new guard. The new guard is really more looking for self provisioning, auto-scaling, all that. Super computer on demand, all that stuff at your fingertips. Great, love that. But is there any opportunity for institutional change within the scientific community? What's your vision around the impact? It's not just scientific. It also can go to government for societal impact. So you start to see this modernization trend. What's your vision on the impact of the scientific community with cloud? >> I think that the way the scientific community has been organized for a long time is that scientists that are at an institute. And a lot of the research has been siloed. And it's siloed in part because of the way the funding mechanism works. But that inhibits creativity and inhibits collaboration. And it inhibits the advancement of science. Because if you hold onto data, you hold on to code. You're not allowing other people to work on it and to build on what you do. The traditional way that scientists have moved forward is you make a discovery, you write up a paper, you describe it in a journal article, and then you publish that. Then if someone wants to build on your research, they get your journal article, they read it. Then they try to understand what you did. They maybe recode all of your analysis. So they're redoing the work that you did, which is simply not efficient. Then they have to download the data sets that you access. This slows down all of science. And it also inhibits bringing in new data sets again because you don't have access to them. So one of the things I'm really excited about with cloud computing is that by bringing our scientific ideas and our compute to the data, it allows us to break out of these silos and collaborate with people outside of our institution, outside of our country, and bring new ideas and new voices and elevate everyone's ideas to another level. >> It brings the talent and the ideas together. And now you have digital and virtual worlds, cause we've been virtualized with COVID-19. You can create content as a community building capability or your work can create a network effect with other peers. And is a flash mobbing effect of potential collaboration. So work, work forces, workplaces, work loads, work flows, kind of are interesting or kind of being changed in real time. You were just talking about speed, agility. These are technical concepts being applied to kind of real world scenarios. I mean your thoughts on that. >> I now work with people like right now, I'm working with students in Denmark, Oman, India, France, and the US. That just wasn't possible 10 years ago. And we're able to bring all these different voices together, which it really frees up science and it frees up who can participate in science, which is really fun. I mean, I'm a scientist. I do it because it's really, really fun. And I love working with other people. So this new ability that I've gained in the last couple of years by moving onto the cloud has really accelerated all the different types of collaborations I'm involved with. And hopefully accelerating science as a whole. >> I love this topic. It's one of my passion areas where it's an issue I've been scratching for over a decade too. Is that content and your work is an enabler for community engagement because you don't need to publish it to a journal. It's like waterfall mentality. It's like you do it. But if you can publish something or create something and show it, demo it or illustrate it, that's better than a paper. If you're on video, you can talk about it. It's going to attract other people, like-minded peers can come together. That's going to create more collaboration data. That's going to create more solidarity around topics and accelerate the breakthroughs. >> For our last paper, we actually published all the software with it. We got a digital firewall for the software, published the software and then containerized it so that when you read our paper, at the bottom of the paper, you get a link. You go to that link, you click on a button and you're instantly in our compute environment, you can reproduce all of our results. Do the error propagation analysis that we did. And then if you don't like something, go ahead and change it or add onto it or ask us some questions. That's just magical. >> Yeah, it really is. And Amazon has been a real investor and I got to give props to Teresa Carlson and her team and Andy Jassy, the CEO, because they've been investing in credits and collaborating with groups like Jet Propulsion Lab, you guys, everyone else. Just space has been a big part of that. I see Bezos love space. So they've been investing in that and bringing that resource to the table. So you've got to give Amazon some props for that. But great work that you're doing. I'm fascinated. I think it's one of those examples where it's a moonshot, but it's doable. It's like you can get there. >> Yeah, and it's just so exciting. I'm the lead on a proposal for a new science mission to NASA. And we are going all in with the cloud computing. So we're going to do all the processing on the cloud. We want to do the entire science team on the cloud and create a science data platform where we're all working together. That's just never happened before. And I think that by doing this, we multiply the benefits of all of our analysis. We make it faster and we make it better and we make it more collaborative. So everyone wins. >> Sure, you're an inspiration to many. I'm so excited to do this interview with you. I love what you said earlier at the beginning about your focus of being in computer science, physics, space. That confluence is multiple disciplines. Not everyone can have that. Some people just get a computer science degree. Some people get, I'm premed, or I'm going to do biology. I'm going to do this. This notion of multiple disciplines coming together is really what society needs now. Is we're converging or virtualizing or becoming a global society. And that brings up my final question. Is something I know that you're passionate about creating a more inclusive scientific community because you don't have to be the, just the computer science major. Now, if you have all three, it's a multi-tool when you're a multiple skill player. But you don't have to be something to get into this new world. Because if you have certain disciplines, whether it's math, maybe you don't have computer science but it's quick to learn. There's frameworks out there, no code, low code. So cloud computing supports this. What's your vision and what's your opinion of how more inclusivity can come into the scientific community? >> I think that, when you're at an institution or at a commercial company or a nonprofit, if you're at some sort of organized institution, you have access to things that not everyone has access to. And in a lot of the world, there's trouble with internet connectivity. There is trouble downloading data. They simply don't have the ability to download large data sets. So I'm passionate about inclusivity because I think that, until we include global voices in science, we're not going to see these global results that we need to. We need to be more interdisciplinary. And that means working with different scientists in different fields. And if we can all work together on the same platform that really helps explode interdisciplinary science and what can be done. A lot of science has been quite siloed because you work at an institution. So you talked to the people one door down, or two doors down or on the same floor. But when you start working in this international community and people don't have to be online all the time, they can write code and then just jump on and upload it. You don't need to have these big, powerful resources or institutions behind you. And that gives a platform for all types of scientists, that all types of levels to start working with everyone. >> This is why I love the idea of the content and the community being horizontally scalable. Because if you're stuck around a physical institution or space, you kind of like have group think, or maybe you have the same kind of ideas being talked about. But here, when you pull back the remote work with COVID-19, as an example, it highlights it. The remote scientist could be anywhere. So that's going to increase access. What can we do to accept those voices? Is there a way or an idea or formula you see that people could, assuming there's access, which I would say, yes. What do we do? What do you do? >> I think you have to be open and you have to listen. Because, if I ask a question into the room where my colleagues work, we're going to come up with an answer. But we're going to come up with an answer that's informed by how we were trained in science and what fields we know. So when you open up this box and you allow other voices to participate in science, you're going to get new and different answers. And as a scientist, you need to be open to allowing those voices to be heard and to acting on them and including them in your research results and thinking about how they may change what you think and bring you to new conclusions. >> Machine learning has been a part. I know your work in the past, obviously cloud you're a big fan, obviously can tell. Proponent of it. Machine learning and AI can be a big part of this too, both on not only sourcing new voices and identifying what's contextually relevant at any given time, but also on the science-side machine learning. Because if we can take a minute to give your thoughts on the and relevance of machine learning and AI, because you still got the humans and you got machines augmenting each other, that relationship is going to be a constant conversation point going forward. Is there data about the data and what's the machines doing? What's your thoughts on all of these? Machine learning and AI as an impact. >> It's funny you say impact. So I work with this NASA IMPACT project, which is this interdisciplinary team that tries to advance science, and it's really into machine learning and AI. One of the difficulties when you start to do science is you have an idea like, okay, I want to study tropical storms. And then you have to go and wade through all these different types of data to identify when events happened and then gather all the data from those different events and start to try and do some analysis. They're working and they've been really successful in using AI to actually do this sort of event identification. So what's interesting and how can we use AI and machine learning to identify those interesting events and gathering everything together for scientists to then try and bring for analysis? So AI is being used in a lot of different ways in science. It's being used to look at these multi-dimensional problems that are just a little bit too big for our brains to try and understand. But if we can use AI and machine learning to gather insights into certain aspects of them, it starts to lead to new conclusions and it starts to allow us to see new connections. AI and machine learning has this potential to transform how we do science. Cloud computing is part of that because we have access to so much more data now. >> It's a real enabling technology. And when you have enabling technology, the power is in the hands of the creative minds. And it's really what you can think up and what you can dream up and that's going to come from people. Phenomenal. Final question for you, to kind of end on a light note. Dr. Chelle Gentemann here, senior scientist at the Farallon Institute. You're doing a lot of work on the ocean, space, ocean interaction. What's the coolest thing you're working on right now? Or you you've worked on that you think would be worth sharing. >> There's a couple of things. I have to think about what's the most fun. Right now, I'm working on doing some analysis with data. We had a big, huge international field campaign this winter off of Barbados, there were research festival, rustles and aircraft. There were sail drones involved, which are these autonomous robotic vehicles that go along the ocean surface and measure air-sea interactions. Right now we're working on analyzing that data. So we have all of this ground truth data. We're bringing in all the satellite observations to see how we can better understand the earth system in that region with a specific focus on air-sea interactions over the ocean where when it rains, you get the salinity stratification. When there's strong solar, you get diurnal stratification. So you have upper ocean stratification and heat and salinity. And how those impact the fluxes and how the ocean impacts the heat and moisture transport into the atmosphere, which then affects weather. So again, this is this multidimensional data set with all these different types of both ground truth data, satellite data that we're trying to bring together and it's really exciting. >> It could shape policy, it could shape society. Maybe have a real input into global warming. Our behaviors in the world, sounds awesome. Plus, I love the ground truth and the observational data. It sounds like our media business algorithm, we got to get the observation, get the truth, report it. Sounds like there's something in there that we could learn from. (both giggling) >> Yeah, it's very interesting cause you often find what you see from a distance is not quite true up close. >> I can tell you that we as in media as we do a lot of investigative journalism. So we appreciate that. Dr. Chelle Gentemann, senior scientist at the Farallon Institute, here as part of AWS Public Sector Summit. Thank you so much for time. What a great story. We'll keep in touch. Love the sails drone. Great innovation. And continue the good work, I'm looking forward to checking in later. Thanks for joining. >> Thanks so much. It was nice talking to you. >> I'm John Furrier with theCUBE. We're here in our studios covering the Amazon Web Services Public Sector Summit virtual. This is theCUBE virtual bringing you all the coverage with Amazon and theCUBE. Thanks for watching. (upbeat music)

>> Narrator: From around the globe, it's theCUBE with digital coverage of PegaWorld iNspire, brought to you by Pegasystems. >> Hi everybody, this is Dave Vellante and welcome to theCUBE's coverage of PegaWorld iNspire 2020. And now that the dust has settled on the event, we wanted to have a little postmortem power panel, and I'm really excited to have three great guests here today. Adrian Swinscoe is a customer service and experience advisor and the best-selling author of a couple of books: "How to Wow" and "Punk CX." Adrian great to see you, thanks for coming on. >> Hey Dave. >> And Shelly Kramer's a principal, analyst, and a founding partner at Futurum Research, CUBE alum. Shelly, good to see you. >> Hi, great to see you too. >> And finally, Don Schuerman who is the CTO of Pegasystems and one of the people that was really highlighting the keynotes. Don, thanks for your time, appreciate you coming on. >> Great to be here. >> Guys, let's start with some of the takeaways from the event, and if you don't mind I'm going to set it up. I had some, I had many many notes. But I'll take a cue from Alan's keynote, where he talked about three things: rethinking the customer engagement, that whole experience, that as a service, I'm going to say that certainly the second part of last decade came to the front and center and we think is going to continue in spades. And then new tech, we heard about that. Don we're going to ask you to chime in on that. Modern software, microservices, we've got machine intelligence now. And then I thought there were some really good customer examples. We heard from Siemens, we heard from the CIO and head of digital at Aflac, the Bank of Australia. So, some really good customer examples. But Shelly, let me start with you. What were your big takeaways of PegaWorld iNspire 2020, the virtual edition? >> You know, what I love is a focus, and we have talked a lot about that here at Futurum Research, but what I love is the thinking that what really is important now is to think about rethinking and kind of tearing things apart. Especially when we're in a time, we're in difficult economic times, and so instead of focusing on rebuilding and relaunching as quickly as possible, I think that now's the time to really focus on reexamining what is it that our customers want? How is it that we can best serve them? And really sort of start from ground zero and examine our thinking. And I think that's really at the heart of digital transformation, and I think that both in this virtual event and in some interviews I was lucky enough to do in advance with some of the Pega senior team, that was really a key focus, is really thinking about how we can re-architect things, how we can do things in ways that are more efficient, that impact people more effectively, that impact the bottom line more effectively. And to me that's really exciting. >> So Adrian, CX is obviously your wheelhouse. A lot of the conversation at PegaWorld iNspire was of course about customer experience, customer service. How do you think the content went? What were some of the highlights for you? And maybe, what would you have liked to hear more of? >> Well I think, thanks Dave, I actually really enjoyed it. I actually kind of thought was, first of all I should say that I've been to a bunch of virtual summits and I thought this was one of the best ones I've done in terms of its pace and its interactivity. I love the fact that Don was bouncing around the screen, kind of showing us around the menu and things. I thought that was great. But the things that I thought really stood out for me was this idea of the context around accelerating digital transformation. And that's very contextual, it's almost being forced upon us. But then this idea of also the center-out thinking and the Process Fabric. Because it really reminded me of, and Don you can maybe correct me if I'm wrong here, is taking a systems-thinking approach to delivering the right outcomes for customers. Because it's always struck me that there's a contradiction at the heart of the rhetoric around customer-centricity where people say they want to do the right things by customers but then they force them down this channel-centric or process-centric way of thinking. And so actually I thought it was really refreshing to hear about this center-out and Process Fabric platform that Pega's building. And I thought it's really exciting because it felt like actually we're going to start to take a more systemic look and take to delivering great service and great experience. So I thought that was really great. Those were my big headlines out of the summit. >> So Don, one of the-- >> Adrian I think-- >> Go ahead, please. >> Yeah, I think the whole idea, you know, and Alan referred to center-out as a business architecture, and I think that's really an important concept because this is really about the intersection of that business goal. How do I truly become customer-centric? And then how do I actually make my technology do it? And it's really important for that to work where you put your business logic in the technology. If you continue to do it in the sort of channel-centric way or really data-centric, system-centric way that historically has been the approach, I don't think you can build a sustainable platform for great customer engagement. So I think that idea of a business architecture that you clued in on a little bit is really central to how we've been thinking about this. >> Let's stay on that for a second. But first of all, I just want to mention, you guys did a good job of not just trying to take a physical event and plug in into virtual. So congratulations on that. The virtual clicker toss, and you know, you were having some fun eating your eggs. I mean that was, that's great. And the Dropkick Murphys couldn't be live, but you guys still leveraged that, so well done. One of the better ones that I've seen. But I want to stay on your point there. Alan talked about some of the mistakes that are made, and one of the questions I have for you guys is, what is the state of customer experience today, and why the divergence between great, and good, and pretty crappy? And Alan talked about, well, people try to impose business process top-down, or they try to infuse logic in the database bottom-up. You really got to do that middle-out. So, Don I want to come back to you. Let's explore that a little bit. What do you really mean by middle-out? Where am I putting the actual business logic? >> Yeah, I think this is important, right. And I think that a lot of time we have experiences as customers. And I had one of these recently with a cable provider, where I spent a bunch of time on their website chatting with a chatbot of some kind, that then flipped me over to a human. When the chatbot flipped me to the human, the human didn't know what I was doing with the chatbot. And that human eventually told me I had to call somebody. So I picked up the phone, I made the phone call. And that person didn't know what I was doing on chat with the human or with the chatbot. So every time there's a customer, I'm restarting. I'm reexplaining where I am. And that to me is a direct result of that kind of channel-centric thinking, where all of my business logic ends up embedded in, "Well hey, we're going to build a cool chatbot. "And now we're going to build a cool chat system. "And by the way, "we're going to keep our contact centers running." But I'm not thinking holistically about the customer experience. And that's why we think this center-out approach is so important, because I want to go below the channel. And I want to think about that customer journey. What's the outcome I'm trying to get to? In the case of my interaction, I was just trying to increase my bandwidth so that I could do events like this, right? What's that outcome that I'm trying to get to and how do I get the customer to that outcome in a way that's as efficient for the business and as easy for the customer as possible regardless of what channel they're on. And I think that's a little bit of a new way of thinking. And again, it means thinking not just about the customer goal, but having an opinion, whether you are a business leader or an IT person, about where that logic belongs in your architecture. >> So, Adrian. Don just described the sort of bot and human experience, which mimics a lot of the human experience that we've all touched in the past. So, but the customer journey that Don talked about isn't necessarily one journey. There's multiple journeys. So what's your take on how organizations can do better with that kind of service. >> Well I think you're absolutely right, Dave. I mean, actually during the summer I was talking, I was listening to Paul Greenberg talk about the future of customer service. And Paul said something that I think was really straightforward but really insightful. He said, "Look, organizations think about customer journeys "but customers don't think about journeys "in the way that organizations do. "They think discontinuously." So it's like, "I'm going to go to channel one, "and then channel three, and then channel four, "and then channel five, and then back to channel two. "And then back to channel five again." And they expect those conversations to be picked up across those different channels. And so I think what we've got to do is develop, as Don said, build an architecture that is, that works around trying to support the different journeys but allows that flexibility and that adaptability for customers to jump around and to have one of those continuous but disconnected conversations. But it's up to us to try and connect them all, to deliver the service and experience that the customers actually want. >> Now Shelly, a lot of the customer experience actually starts with the employees, and employees don't like when the customer is yelling at them saying, "I just answered all those questions. "Why do I have to answer them again?" So you've, at your firm, you guys have written a lot about this, you've thought a lot about it, you have some data I know you shared on theCUBE one time that 80% of employees are disengaged. And so, that affects the customer experience, doesn't it? >> Yeah it does, you know. And I think that when I'm listening to Don's explanation about his cable company, I'm having flashbacks to what feels like hundreds of my own experiences. And you're just thinking, "This does not have to be this complicated!" You know, ten years ago that same thing that Don just described happened with phone calls. You know, you called one person and they passed you off to somebody else, and they passed you off to somebody else, and you were equally as frustrated as a customer. Now what's happening a lot of times is that we're plugging technology in, like a chat bot, that's supposed to make things better but we're not developing a system and processes throughout our organization, and also change management, what do I want to say, programs within the organization and so we're kind of forgetting all of those things. So what's happening is that we're still having customers having those same experiences that are a decade old, and technology is part of the mix. And it really shouldn't be that way. And so, one thing that I really enjoyed, speaking about employees, was listening to Rich Gilbert from Aflac. And he was talking about when you're moving from legacy processes to new ones, you have to plan for and invest in change management. And we talk about this all the time here at Futurum, you know technology alone is never the answer. It's technology plus people. And so you have to invest in people, you have to invest in their training in order to be able to support and manage change and to drive change. And I think one really important part of that equation is also listening to your employees and getting their feedback, and making them part of the process. Because when they are truly on your front lines, dealing with customers, many times dealing with stressed, upset, frustrated customers, you know, they have a lot of insights. And sometimes we don't bring them into those conversations, certainly early enough in the process to help, to let them help guide us in terms of the solutions and the processes that we put in place. I think that's really important. >> Yeah, a lot of-- >> Shelly, I think-- >> If I may, a lot of the frustration with some employees sometimes is those processes change, and they're unknown going into it. We saw that with COVID, Don. And so, your thoughts on this? >> Yeah, I mean, I think the environment employees are working in is changing rapidly. We've got a customer, a large telecommunications company in the UK where their customer service requests are now being handled by about 4,000 employees pulled from their marketing department working distributed because that's the world that we're in. And the thing I was going to say in response to Shelly is, Alan mentioned in his keynote this idea of design thinking. And one of the reasons why I think that's so important is that it's actually about giving the people on the front lines a voice. It's a format for engaging the employees who actually know the day-to-day experiences of the customers, the day-to-day experiences of a customer service agent, and pulling them into the solution. How do we develop the systems, how do we rethink our processing, how does that need to plug into the various channels that we have? And that's why a lot of our focus is not just on the customer service technology, but the underlying low code platform that allows us to build those processes and those chunks of the customer journey. We often refer to them as "microjourneys" that lead to a specific outcome. And if you're using a low code based platform, something that allows anybody to come in and define that process, you can actually pull employees from the front lines and put them directly on your project teams. And all of a sudden you get better engagement but you also get this incredible insight flowing into what you're doing because you're talking to the people who live this day in and day out. >> Well and when you have-- >> So let's stay on this for a second, if we can. Shelly, go ahead please. >> Sure. When you have a chance to talk with those people, to talk with those front line employees who are having an opportunity to work with low code, no code, they get so excited about it and their jobs are completely, the way they think about their jobs and their contribution to the company, and their contribution to the customer, and the customer experience, is just so wonderful to see. And it's such an easy thing to do, so I think that that's really a critical part of the equation as it relates to success with these programs. >> Yeah, staying close to the customer-- >> Can I jump in? >> Yeah, please Adrian. >> Can I jump in on that a little, a second. I think Shelly, you're absolutely right. I think that it's a really simple thing. You talk about engagement. And one of the key parts of engagement, it seems to me, is that, is giving people a voice and making them feel important and feel heard. And so to go and ask for their opinion and to help them get involved and make a difference to the work that they do, the outcomes that their customers receive, and the overall productivity and efficiency, can only have a positive impact. And it's almost like, it feels self-evident that you'd do that but unfortunately it's not very common. >> Right. It does feel self-evident. But we miss on that front a lot. >> So I want to ask, I'm going to come back to, we talked about people process, we'll come back to that. But I want to talk about the tech. You guys announced, the big announcement was the Pega Process Fabric. You talked about that, Don, as a platform for digital platforms. You've got all these cool microservices and dynamic APIs and being able to compose on the fly, so some pretty cool stuff there. I wonder, with the virtual event, you know, with the physical event you've got the hallway traffic, you talk to people and you get face-to-face reactions. Were you able to get your kind of real-time reactions to the announcement? What was that like? Share with us please. >> Yeah, so, we got well over 1,000 questions in during the event and a lot of them were either about Process Fabric or comments about it. So I think people are definitely excited about this. And when you strip away all of the buzzwords around microservices and cloud, et cetera, I think what we're really getting at here is that work is going to be increasingly more distributed. We are living proof of that right now, the four of us all coming here from different studios. But work is going to be distributed for a bunch of reasons. Because people are more distributed, because organizations increasingly are building customer journeys that aren't just inside their walls, but are connected to the partners and their ecosystem. I'm a bank but I may, as part of my mortgage process, connect somebody up to a home insurer. And all of a sudden the home buying process goes beyond my four walls. And then finally, as you get all of these employees engaged with building their low code apps and being citizen developers, you want to let the 1,000 flowers to bloom but you also need a way to connect that all back together. And Process Fabric is about putting the technology in place to allow us to take these distributed bits of work that we need to do and weave them together into experiences that are coherent for a customer and easy for an employee to navigate. Because I think it's going to be really really important that we do that. And even as we take our systems and break them up into microservices, well customers don't interact with microservices. Customers interact with journeys, with experiences, with the processes you lay out, and making sure we can connect that up together into something that feels easy for the customer and the employee, and gets them to that result they want quickly, that's what the vision of Process Fabric is all about. >> You know, it strikes me, I'm checking my notes here. You guys talked about a couple of examples. One was, I think you talked about the car as sort of a mobility experience, maybe, you know, it makes me wonder with all this AI and autonomous vehicle stuff going on, at what point is owning and driving your own vehicle really going to be not the norm anymore? But you talked about this totally transformed, sorry to use that word, but experience around autos. And certainly financial services is maybe a little bit more near-term. But I wonder Shelly, Futurum, you know, you guys look ahead, how far can we actually go with AI in this realm? >> Well, I think we can go pretty far and I think it'll happen pretty fast. And I think that we're seeing that already in terms of what happened when we had the Coronavirus COVID-19, and of course we're still navigating through that, is that all of a sudden things that we talked about doing, or thought about doing, or planned doing, you know later on in this year or 2021, we had to do all of those things immediately. And so again, it is kind of like ripping the Bandaid off. And we're finding that AI plays a tremendously important role in relieving the workload on the frontline workers, and being able to integrate empathy into decision making. And you know, I go back to, I remember when you all first rolled out the empathy part of your platform, Don, and just watching a demo on that of how you can slide this empathy meter to be warmer, and see in true dollars and cents over time the impact of treating your customers with more empathy, what that delivers to a company. And I think that AI that continues to build and learn and again, what we're having right now, is we're having this gigantic volume of needs, of conversation, of all these transactions that need to happen at once, and great volumes make for better outcomes as it relates to artificial intelligence and how learning can happen more quickly over time. So I think that it's, we're definitely going to see more use of AI more rapidly than we might've seen it before, and I don't think that's going to slow down, at all. Certainly, I mean there's no reason for it to slow down. The benefits are tremendous. The benefits are tremendous, and let me step back and say, following a conversation with Rob Walker on responsible AI, that's a whole different ball of wax. And I think that's something that Pega has really embraced and planted a flag in. So I think that we'll see great things ahead with AI, and I think that we'll see the Pega team really leading as it relates to ethical AI. And I think that's tremendously important as well. >> Well that's the other side of the coin, you know. I asked how far can we go and I guess you're alluding to how far should we go. But Adrian, we also heard about agility and empathy. I mean, I want an empathic service provider. Are agility and empathy related to customer service, and how so? >> Well, David, I think that's a great question. I think that, you talk about agility and talk about empathy, and I think the thing is, what we probably know from our own experience is that being empathetic is sometimes going to be really hard. And it takes time, and it takes practice to actually get better at it. It's almost like a new habit. Some people are naturally better at it than others. But you know, organizationally, I talk about that we need to almost build, almost like an empathetic musculature at an organizational level if we're going to achieve this. And it can be aided by technology, but we, when we develop new muscles it takes time. And sometimes you go through a bit of pain in doing that. So I think that's where the agility comes in, is that we have to test and learn and try new things, be willing to get things wrong and then correct, and then kind of move on. And then learn from these kind of things. And so I think the agility and empathy, it does go hand in hand and it's something that will drive growth and increasing empathetic interactions as we go forward. But I think it's also, just to build on Shelly's point, I think you're absolutely right that Pega has been leading the way in this sort of dimension, in terms of its T-switch and its empathetic advisor. But now the ethical AI testing or the ethical bias testing adds a dimension to that to make sure it's not just about all horsepower, but being able to make sure that you can steer your car. To use your analogy. >> So AI's coming whether we like it or not. Right, Shelly? Go ahead. >> It is. One real quick real world example here is, you know, okay so we have this time when a lot of consumers are furloughed. Out of work. Stressed about finances. And we have a lot of Pega's customers are in the financial services space. Some of the systems that they've established, they've developed over time, the processes they've developed over time is, "Oh, I'm talking with Shelly Kramer and she has a "blah-blah-blah account here. "And this would be a great time to sell her on "this additional service," or whatever. And when you can, so that was our process yesterday. But when you're working with an empathic mindset and you are also needing to be incredibly agile because of current circumstances and situations, your technology, the platform that you're using, can allow you to go, "Okay I'm dealing "with a really stressed customer. "This is not the best time "to offer any additional services." Instead what we need to ask is this series of questions: "How can we help?" Or, "Here are some options." Or whatever. And I think that it's little tweaks like that that can help you in the customer service realm be more agile, be more empathetic, and really deliver an amazing customer experience as a result. And that's the technology. >> If I could just add to that. Alan mentioned in his keynote a specific example, which is Commonwealth Bank of Australia. And they were able, multiple times this year, once during the Australian wildfires and then again in response to the COVID crisis, to completely shift and turn on a dime how they interacted with their customer, and to move from a prioritization of maybe selling things to a prioritization of responding to a customer need. And maybe offering payment deferrals or assistance to a customer. But back to what we were talking about earlier, that agility only happened because they didn't have the logic for that embedded in all their channels. They had it centralized. They had it in a common brain that allowed them to make that change in one place and instantly propagate it to all of the 18 different channels in which they touch their customer. And so, being able to have agility and that empathy, to my mind, is explicitly tied to that concept of a center-out business architecture that Alan was talking about. >> Oh, absolutely. >> And, you know, this leads to discussion about automation, and again, how far can we go, how far should we go? Don, you've been interviewed many many times, like any tech executive, about the impact of AI on jobs. And, you know, the typical response of course is, "No, we want augmentation." But the reality is, machines have always replaced humans it's just, now it's the first time in terms of cognitive function. So it's a little different for us this time around. But it's clear, as I said, AI is coming whether we like it or not. Automation is very clearly on the top of people's minds. So how do you guys see the evolution of automation, the injection of automation into applications, the ubiquity of automations coming in this next decade? Shelly, let's start with you. >> You know, I was thinking you were going to ask Don that question so I'm just listening and listening. (laughing) >> Okay, well we can go with Don, that's-- >> No I'm happy to answer it. It's fine, it just wasn't what I expected. You know, we are really immersed in the automation space. So I very much see the concerns that people on the front line have, that automation is going to replace them. And the reality of it is, if a job that someone does can be automated, it will be automated. It makes sense. It makes good business sense to do that. And I think that what we are looking at from a business agility standpoint, from a business resilience standpoint, from a business survival standpoint, is really how can we deliver most effectively to serve the needs of our customers. Period. And how we can do that quickly and efficiently and without frustration and in a way that is cost effective. All of those things play into what makes a successful business today, as well as what keeps employees, I'm sorry, as well as what keeps customers served, loyal, staying around. I think that we live in a time where customer loyalty is fleeting. And so I think that smart businesses have to look at how do we deepen the relationships that we have with customers? How can we use automation to do that? And the thing about it, you know, I'll go back to the example that Don gave about his cable company that all of us have lived through. It's just like, "Oh my gosh. "There's got to be a better way." So compare that to, and I'm sure all of us can think of an experience where you had to deal with a customer service situation in some way or another, and it was the most awesome thing ever. And you walked away from it and you just went, "Oh my gosh. I know I was talking to a bot here or there." Or, "I know I was doing this, but that solved my problem. "I can't believe it was so easy! "I can't believe it was so easy! "I can't wait to buy something from this company again!" You know what I'm saying? And that's really, I think, the role that automation can play. Is that it can really help deepen existing relationships with our customers, and help us serve them better. And it can also help our employees do things that are more interesting and that are more relevant to the business. And I think that that's important too. So, yes, jobs will go. Yes, automation will slide into places where we've done things manually and repetitive processes before, but I think that's a good thing. >> So, we've got to end it shortly here but I'll give you guys each a last opportunity to chime in. And Adrian, I want to start with you. I invoked the T-word before, transformation, a kind of tongue-in-cheek joking because I know it's not your favorite word. But it is the industry's favorite word. Thinking ahead for the future, we've talked about AI, we've talked about automation, people, process and tech. What do you see as the future state of customer experience, this mix of human and machine? What do we have to look forward to? >> So I think that, first of all, let me tackle the transformation thing. I mean, I remember talking about this with Duncan Macdonald who is the CIO across at UPC, which is one of Pega's customers, on my podcast there the other week. And he talked about, he's the cosponsor of a three year digital transformation program. But then he appended the description of that by saying it's a transformation program that will never end. That's the thing that I think about, because actually, if you think about what we're talking about here, we're not transforming to anything in particular, you know. It's not like going from here to there. And actually, the thing that I think we need to start thinking about is, rather than transformation we actually need to think about an evolution. And adopting an evolutionary state. And we talked about being responsive. We talked about being adaptable. We talked about being agile. We talk about testing and learning and all these different sort of things, that's evolutionary, right? It's not transformational, it's evolutionary. If you think about Charles Darwin and the theory of the species, that's an evolutionary process. And there's a quote, as you've mentioned I authored this book called "Punk CX," there's a quote that I use in the book which is taken from a Bad Religion song called "No Control" and it's called, "There is no vestige of a beginning, "and no prospect of an end." And that quote comes from a 1788 book by James Hutton, which was one of the first treaties on geology, and what he found through all these studies was actually, the formation of the earth and its continuous formation, there is no vestige of a beginning, no prospect of an end. It's a continuous process. And I think that's what we've got to embrace is that actually change is constant. And as Alan says, you have to build for change and be ready for change. And have the right sort of culture, the right sort of business architecture, the right sort of technology to enable that. Because the world is getting faster and it is getting more competitive. This is probably not the last crisis that we will face. And so, like in most evolutionary things, it wasn't the fittest and the strongest that survived, it was the ones that were most adaptable that survived. And I think that's the kind of thing I want to land on, is actually how, it's the ones that kind of grasp that, grasp that whole concept are the ones that are going to succeed out of this. And, what they will do will be... We can't even imagine what they're going to do right now. >> And, thank you. And Shelly, it's not only responding to, as Adrian was saying, to crisis, but it's also being in a position to very rapidly take advantage of opportunities and that capability is going to be important. You guys are futurists, it's in the name. Your thoughts? >> Well I think that, you know, Adrian's comments were incredibly salient, as always. And I think that-- >> Thank you. >> The thing that this particular crisis that we are navigating through today has in many ways been bad, but in other ways, I think it's been incredibly good. Because it has forced us, in a way that we really haven't had to deal with before, to act quickly, to think quickly, to rethink and to embrace change. Oh, we've got to work from home! Oh, we've got 20 people that need to work from home, we have 20,000 people that need to work from home. What technology do we need? How do we take care of our customers? All of these things we've had to figure out in overdrive. And humans, generally speaking, aren't great at change. But what we are forced to do as a result of this pandemic is change. And rethink everything. And I think that, you know, the point about transformation not being a beginning and an end, we are never, ever, ever done. It is evolutionary and I think that as we look to the future and to one of your comments, we are going faster with more exciting technology solutions out there, with people who are incredibly smart, and so I think that it's exciting and I think that all we are going to see is more and more and more change, and I think it will be a time of great resilience, and we'll see some businesses survive and thrive, and we'll see other businesses not survive. But that's been our norm as well, so I think it's really, I think we have some things to thank this pandemic for. Which is kind of weird, but I also try to be fairly optimistic. But I do, I think we've learned a lot and I think we've seen some really amazing exciting things from businesses who have done this. >> Well thanks for sharing that silver lining, Shelly. And then, Don, I'm going to ask you to bring us to the finish line. And I'm going to close my final question to you, or pose it. You guys had the wrecking ball, and I've certainly observed, when it comes to things like digital transformations, or whatever you want to call it, that there was real complacency, and you showed that cartoon with the wrecking ball saying, "Ehh not in my life, not on my watch. "We're doing fine." Well, this pandemic has clearly changed people's thinking, automation is really top of mind now at executive. So you guys are in a good spot from that standpoint. But your final thoughts, please? >> Yeah, I mean, I want to concur with what Adrian and Shelly said and if I can drop another rock quote in there. This one is from Bob Dylan. And Dylan famously said, "The times they are a changing." But the quote that I keep on my wall is one that he tossed off during an interview where he said, "I accept chaos. "I'm not sure if it accepts me." But I think digital transformation looks a lot less like that butterfly emerging from a cocoon to go off happy to smell the flowers, and looks much more like accepting that we are in a world of constant and unpredictable change. And I think one of the things that the COVID crisis has done is sort of snapped us awake to that world. I was talking to the CIO of a large media company who is one of our customers, and he brought up the fact, you know, like Croom said, "We're all agile now. "I've been talking about five years, "trying to get this company to operate in an agile way, "and all of a sudden we had to do it. "We had no choice, we had to respond, "we had to try new things, we had to fail fast." And my hope is, as we think about what customer engagement and automation and business efficiency looks like in the future, we keep that mindset of trying new things and continuously adapting. Evolving. At the end of the day, our company's brand promise is, "Build for change." And we chose that because we think that that's what organizations, the one thing they can design for. They can design for a future that will continue to change. And if you put the right architecture in place, if you take that center-out mindset, you can support those immediate needs, but set yourself up for a future of continuous change and continuous evolution and adaptation. >> Well guys, I'll quote somebody less famous. Jeff Frick, who said, "The answer to every question "lives somewhere in a CUBE interview." and you guys have given us a lot of answers. I really appreciate your time. I hope that next year at PegaWorld iNspire we can see each other face-to-face and do some live interviews. But really appreciate the insights and all your good work. Thank you. >> Thank you. >> Absolutely. >> And thank you for watching everybody, this is Dave Vellante and our coverage of PegaWorld iNspire 2020. Be right back, right after this short break. (lighthearted music)

>> Narrator: Live from Seattle, Washington it's theCUBE covering Smartsheet ENGAGE 2019. Brought to you by Smartsheet. >> Welcome back, everyone, to theCUBE's live coverage of Smartsheet ENGAGE here in Seattle. I'm your host, Rebecca Knight, along with my co-host, Jeff Frick. We're joined by Kristin Komassa. She is the VP Process Improvement at Colliers International Wisconsin. Thanks so much for coming on the show. >> Thanks for having me, I'm excited to be here. >> So you're here direct from Milwaukee. Tell our viewers a little bit about Colliers International Wisconsin. >> Yeah, so Colliers International Wisconsin, we are recognized as the largest full-service commercial real estate company in the state of Wisconsin. And when I say full-service it means we have everything from brokerage to property management to facilities, architecture, development. We cover the gamut on both the commercial and we've actually started a residential program, as well. So, we've got you covered. >> Excellent, so tell us now about your Smartsheet story. There was a movie that played during the keynote address where we heard a lot about your Smartsheet experience. But you tell our viewers now. >> Yeah, so I started using Smartsheet in 2012 when I came to Colliers and really it was a one specific project that we needed to really wrap our arms around and other methods weren't doing it at all. So I discovered Smartsheet. And ironically if you took Smartsheet from 2012 and put it next to Smartsheet 2019, you wouldn't think they're the same product at all. But it solved our issues at that time. We were able to really elevate what we were doing with that client. We were recognized, and the company ownership saw that if you can do this with one client, what could you do with the whole company? And over the past years we have really rolled it out both internally through the operational side, from how we just manage our day-to-day business to also how do we get in with those clients and how do we manage their real estate with this software program? So that's kind of been my journey and it's been fun and it's been amazing and I'm looking forward to the next phase. >> So what was the killer app in 2012 that you couldn't do with any other tool that was so breakthrough? >> We were starting with Excel and it was just an extremely large portfolio. We tried to do Google Sheets, that didn't work. And Smartsheet was the app of choice, that we could collaboratively work on this entire portfolio but manage it with a security level, because it was a banking institution, that they were concerned. And Smartsheet, even at that time, they knew that security was a big issue with their clients. >> So was it the ability to cross-company collaborate with the banking client as well as your own team? That was-- >> It was. It was a large team, we had 15 people, so you can imagine version control was huge. >> Nightmare. >> Yeah, a nightmare. Nobody wants to see an Excel document sent to 15 people asking for revisions. And, again, we had to be able to report to this banking customer in their own format and we had again really aggregate that data in a consistent and repeatable way, but yet still maintain that control. And Smartsheet allowed us to do that in a very flexible and customizable way. So we didn't buy something off the shelf that we'll maybe use 50% of it, we used 100% of what we purchased. >> So 2012, that's a while ago. >> A little bit. >> Can you talk about the cultural change from your company now that you use Smartsheet on a regular basis and how that has helped you collaborate and helped you be more creative with each other, helped you understand the big picture? >> Yeah, so really in 2012 we were a slightly smaller company. It was coming right out of the recession and when there was a lot of REO properties and just there was some issues in real estate in general. And we were able to really ride that wave and come back a lot stronger than we were because we were able to cross-collaborate between all of our different company divisions, and really show our clients, one of our taglines is Better Together, and that's what we were. And it's easy to be better together when you have a platform that helps you build that up. And our company has since kind of shed some of those maybe less desirable properties or product type and really moved into the class-A downtown markets because we're able to now work with some of those more sophisticated owners of real estate and those sophisticated clients that are, they're really looking for not just a real estate expert, but an advisor for them. How do you help me take my real estate and make it work for my business? And Smartsheet was a big part of that. >> It really has evolved your role. As you said, it's much more of a, you're much more of an advisor now. >> Yes, we are definitely much more of an advisor, of a consultant, of a trusted partner, is what we are. And it's not always just about real estate anymore, it's about building those relationships. But showing them as well as to, how can we put all those pieces together and then still have full transparency with you? And with our other vendors and our clients and bringing everybody together. >> So I love that you, looking at the big picture and big changes in the big picture, but you've also talked about it's a combination of lots of little things that add up to the big thing. I think one of your videos you talked about a push notice for an accept/decline was a game changer. And then today we heard in the keynote, a copy/paste from one to the other got a standing ovation. So what was your favorite feature for today? And I'm just curious, is that approach something that you've adopted also in the way that you use the tool to engage with your clients? >> Every ENGAGE that I've been to I leave and I'm just so excited to get back and start implementing everything because, again, Smartsheet really listens to their clients. But really from what the things that were announced today, it seems like a simple thing but I'm really excited about Move Row. Because when you're done with a project, it doesn't take a lot of time to actually grab it and move it down, but if somebody forgot to do it and it's rolling up to your aggregate data and all that, it's just such a little thing but it makes such a big difference. Show me only my active in-flight projects. I don't want to see my completed ones or my closed, or my on-hold, if I change the status. Give me what I care about, front and center. So Move Row wass my big thing. >> Love it. >> But that is what we've been talking about, frankly, all day, is how these little things can add up to be the big aggravations of work. And so when you are slowly chipping away at all of the annoyances, that leads to a much more pleasant work day. >> Kristin: It definitely does. >> And a much more satisfying work life. >> Yep, I'll take any second I can gain back in a day. >> Right, so we talked about how Colliers International Wisconsin has really evolved from sort of, not a small-time real estate, but now you are this trusted partner of so many wealthier clients. Talk about the internal culture, though, in terms of how you all work together. >> Yeah, so some of our key features are like we like Warrior-Spirit, and this Better Together, and being innovators. And that's really what Smartsheet has encouraged us to be, is more of these innovators and working together and really being a champion internally. You'd be amazed, a lot of real estate companies, they have a lot of brokers and then employees and maybe not everybody, there are different personality types and all that, but our company has been able to figure out a way to pull everybody together and aggregate that data for a real big picture from both sides. Instead of looking at employees versus consultants, but just everybody. What is Colliers? And it's been amazing because Smartsheet has been that platform that we've utilized to do that and to bring everybody up. The collaboration that it has encouraged between different departments. Everybody knowing what is going on with a project or knowing that if you're talking to the same client that I'm talking to and how do we now work together, versus you make a phone call and you just called my client. I don't want that happening and it makes you sound kind of silly. How do we work together for a common purpose, basically, is what's happened. >> So is it the primary work tool that's open on people's desks? >> Yes, it is. It's open on my desk 100% of the time and we have actually created individualized dashboards for every single one of our brokers and it is their ground zero where they go to for all of their information. For if they have a new listing, if they have to submit commission information, if they want to submit a referral to another one of our lines. That is where they go. Our property managers, we're working right now to create their individual dashboards where, again, they're going to be living in there, and how they're communicating with their landlords and their owners and, how do you aggregate that tenant data in there so that everybody on your team is all on the same page? But again, it's living in Smartsheet is what the entire company is doing these days. >> So you talked about how this was 2012 when you first adopted it. The real estate business particularly, and commercial real estate not in a great position, in a much better, more solid position today. What are you thinking about for the future in terms of how your industry evolves and how you're going to need tools to help you evolve? >> Yeah, our clients, it's a tech world, everything. Your fridge can order milk for you these days. If you have a real estate and they're not an advisor, they're just a real estate broker and they're not accessing the technology that is out there to help you get market intel at the touch of your fingertips. They almost want you to anticipate what their question is going to be before they ask it. And they want that data available at night, on the weekends, in the morning, at their own schedule. If you're not able to provide that but you have to send them an email and they have to wait on it, I think that you're going to fall behind. You have to be able to keep up with the world of technology and becoming less of a one, I'm just going to help you on this single transaction to I'm helping you on this one, but what's the next one? And how does it affect your business? And how do I become your partner and your advisor and just that trusted partner? And that's where it's going, I think. >> And have you been able to, are you able to do those things because it has freed up your time? Because that's another thing we hear about this technology, is that because it is automating so many of the manual, repetitive tasks, you do have more time to be creative, to think more holistically and more about the future. >> Yeah and that's really what we're pushing is, if it's an administrative task, if it's something that you can automate it, do it. Don't take another day sending a repetitive email or you checking your calendar, did somebody finish something? Have the system do it for you. Did somebody, if you assigned a task, did they do it? You shouldn't have to babysit them for it. And yes, it should free you up to, how do I look strategically? How do I look forward into something? Instead of constantly trying to look backwards as to what did we do? Has it been completed? It should be done and we should be on to the next step at this point. >> So you said that you always come away from ENGAGEs so excited, so happy to come back to your office and talk about what you've learned. What do you think it's going to be from this one? Besides Move Row? Which I know is going to change your life, Kristin. >> Move Row will change my life, but there's a lot of things. You know what, so many things. Again, Smartsheet, I can't reiterate enough, they listen to their customers. And going back and figuring out how do I optimize something that I already thought was the apex thing that I was going to create, how do I now make it better? How do I make it so that it frees up somebody else's time? So that maybe them moving a row down, they no longer have to do that. How do I now make the next one even better? So I'm just, I'm excited, again, about that continuous process improvement. >> Excellent. Well, thank you so much for coming on the show. It was a pleasure having you. >> Thank you, I'm excited to be here. >> And now you're a CUBE veteran. >> Now I'm a CUBE veteran, thank you. >> I'm Rebecca Knight for Jeff Frick, stay tuned for more of theCUBE's live coverage of ENGAGE 2019. (upbeat electronic music)

>> from the Cosmopolitan Hotel in Las Vegas, Nevada. It's the Cube covering Cooper inspired 2019. Brought to You by Cooper. >> Welcome to the Q. But Lisa Martin on the ground in Las Vegas for Cooper Inspire. 19 Hot Vegas. Fresh Insight. I'm pleased to welcome Max Ground, the managing director from Deloitte to the program. Hey, Max. >> Good morning. Good afternoon. >> Good afternoon. Whatever time it is, Vegas Right here is this. It's a time warp. They don't like you see outside It's >> only place the world. The 25th hour. >> Right? So here we are. It inspired 19 kick Everything kicked off this morning with the general session. I was teasing Rob Bernstein a couple hours ago and I had him on that. I learned three things in the general session. He likes pizza, he likes kittens. And Cuba's platform now has 1.2 trillion dollars of spending data going through it. And I thought, man procurement is not what I thought. It wa ce and you have a really >> interesting story about procurement. I'd love for you to share with our audience >> because you said in your session earlier today you said people in this standing your morning session. How many of you wanted to be on procurement? Anybody that raises their hands of line tell me about the procurement of yesterday, the >> opportunities that it's given you and what it is now. >> So I think >> in the past, >> security has been something that had to happen. It was a must have not a place that people saw value. But was the rule enforcers right? So trying to do that and really adding value by discipline, where today, if you think about it, the value that they can add by driving savings authorization drops right to the bomb line. So all the savings that are out there, all >> the negotiations that are doing, it's really unique skill set >> and something that people really should move into finance folks when they're looking for a new opportunity. It's a great skill set to have. Lately I've come across a former attorneys are practicing law but now doing strategic sourcing, doing procurement, work, people from finance because the talent that you have to have is field work with people within their companies, understand their needs, negotiate with suppliers, do hard core analytics and, oh, by the way, we're talking about Cooper has helped in change and implemented technology like that. It's really fascinating. >> It's so much more than >> being a buyer or being somebody that's controlling a particular business unit's ability to buy and spend. >> One of the interesting things about Cooper is this platform that allows what started, I >> think, initially as more procurement corner invoicing is now expanded to also include payments and expenses and travel management and contingent workhorse management. So what the CPO now has the opportunity to do is get this visibility right across an entire business of all of the spending, to your point, make massive impacts to the bottom line. >> Yeah, I >> mean, data is so important, right? In the past, the vendors had all the information. Why? Because the sales people how to get commissions. They knew exactly what was being bought of that company. Today, you can reverse engineer saying, selling cells. I say it's reverse sales. I can't go in there and I tell them now I have the full picture. So if it's divided up that category by three or four different vendors, they're making assumptions about how much market share they have. I know it all. I can create a model, a pricing model on the reverse. Engineer it. It's really for sales. I'm telling them now why they should give me a great discount for the organization and >> I >> have the ability to actually enforce that and drive the savings that we have for the organization. It also helped them drive their numbers on sales. So it's a mutually beneficial relationship. They have more market share. I drive better value for the organization. It really works well, >> Well, one of the destructor is that you're kind of alluded to Is this consumer ization? You know, when you go to buy >> a car these days, you just walk in there. You have as a as a buyer of the consumer oven automobile. You have access to every piece of information possible, the whole transaction process. The sales process is different. So as consumers in our regular lives, we have so much expectation that weaken, find anything good Amazon, find anything that we want, get it delivered tomorrow and have all these information on what? Where's the best place I could get it? Who's selling it for what? How is this person that you know, more trustworthy supplier So this consumer ization element and how it's changing the role of the CPO in the CFO is >> really revolutionary. >> It really isn't so you think about it. Most of us go out to Amazon by something, and really the only control there for me, for example, is my wife has to approve it, right, so that's the only veto authority. So that's really the only difference between the two platforms. If you think about it is, there's controls in place, so you're doing the right thing. But from an end user perspective, if I go out there and find the right item and again in Amazon, I don't to go find the supplier. I don't know if that be on contract. Why don't you do that work? We shouldn't have to. I should just go out there and say, I need this And in the background, Cooper is working all those things, presenting the right products on the right contracts, driving right value and almost is important, minimizing the risk. So across all those different lenses, you see why the value of Cooper is for the end user. They're getting what they need for the organization, for the company we're reducing risk and we're increasing value, and then you have rich reporting on the back end. So it's just it's a great way of doing business. It really is taking what you used to do or what you do. It's Sunday afternoon like Rob, you say Monday at work, and I think that's really powerful thing of perspective. >> It is. And it can be so impactful if applied in the right way with an organization, whether it's a manufacturer or hospital or retailer that has a culture that is willing to embrace change, right? I mean, there's that right, Especially >> get him to get your >> perspective on when you're implementing Cooper at a large organization. Maybe have been around for many, many years versus maybe a more modern that we think might be more nimble organization. Culturally, Do you see massive differences in how they're leading procurement, and are you able to sort of level the playing field and show them doesn't matter what your culture is? Here's how your business, your body. >> So from a change perspective, I think there's a different perception. The newer, nimbler organization believes that they changed easy, but it still may have people the older organisation again still made people most people don't like to change. What I have learned is if you help them understand the value of it, how they're doing it, how their jobs are going to change and give them the tools to do it. Some people are gonna be early adopters. But finding that one person, the organization, no matter what level they are in that business unit or in that department that has that informal voice that people look to naturally, that the Nazi leader who's in a leadership position with leader from a personality perspective get them on board. And sometimes that's the hardest thing to do. They might be the most changed resistant, but was that person flips, They become your greatest greatest advocate out there. So it's a personal thing. This is hard work. That's why I talk about in our sessions, is going through. This requires a lot of work, but it's worth it. You can measure the value on the end that you got help. People understand why you're going on this journey and have have resource is there for help. >> So what were some of that? You said you did good Q and a session during your break out this afternoon. >> Tell me some of >> the things that that some of the audience said that you thought was really like they're getting it, >> Yes. So the whole point of our session was going live is not really the goal, right? That's just >> a guess, the exact right. >> And so most people focus on going live, and the answer is congratulations. You purchased the product, Kuba, and now it's working. So what? You don't have any real data? What do you do in the future? Some questions were as they're going through Supplier Neighborhood. The shift between procurement now taking a larger role in the relationships with the vendors. Well, that's great. It should be a balanced relationship. You know, there's a procurement role in that. And then there's the end. Users are the people in the organization from the business. You have to relate with those suppliers, so work together. If you were together in the past now it's a great time to do that. There's some other questions about if something is not working correctly. Post go live how quick It's not broken, but it could be optimized or you're getting complaints about. How quick should you change it? The answer is, I don't know, measuring yourself. I mean, obviously it's broken. Fix it. But it might be something around change. And maybe you have to help people understand why they're doing this new process. If people are giving feedback positive, negative, mostly native, was positive. We just go off our way. Welcome to Yelp. But if it's negative feedback, listen, don't get offended, understand that perspective and then measure it. Say, Is this something that we did is saying the platform, or is it just changed and work with it? What I tell our clients to is in Cooper, Just cause you can doesn't mean you should. I mean, that's really easy to build a field custom field, really easy to build, custom approval chance, really hard to maintain that stuff. So try to do it out of the not out of the box, but configured without as much customization as possible, and they can always improve it, understand it better. >> I think the key to adoption is the more customization that you have. I imagine the adoption funnel gets narrower and narrower. It's got >> interesting, so you customize because you think that's the way the process should go, because that's how we do it today. So if your goal is to take how you do your process today and put into Cooper, also tell clients congratulations. If you had a bad process now you're bad process that works faster. So take the time to say, Let's step back. Companies evolve, right? And so as they're evolving, if you haven't taken a really a view purposeful of you backwards and measure organization, where you're out from a charity model assessment, then you probably don't know where your gaps are. Take the opportunity when you're implying Cooper to use kind of leading practice that Cooper has start with that and said, Going back to what you're doing today, you know what a great example. That's improvers, right? So people like to have 10 approve er's because they think it reduces risk. So if I go back and look and I asked the audience, say, how many purchase order requests rejected? Very few. And how long do people actually have it open when they re prove it? So that's three seconds when they open it up and looked at it, do they really assess it from a risk perspective? Probably not. But if four people ahead of them approved it, that person's just gotta prove it, because I think it's okay because they're assuming someone else is looking at it, as opposed to in Cooper. Now I have the rich data to understand it. I could minimize risk that way instead of trying to do it. And what is a false sense of security? >> So getting people on board with bringing in automation and leveraging like I was saying in the beginning, the 1.2 trillion of spend that's going through the Cooper platform toe leverage that intelligence to not only have Cooper create the prescriptions for companies to be able to go. Okay, we don't we shouldn't your point. We shouldn't take a process that was clunky before and just do it faster. Still clunky, being able to have the automation thing. Analytics. Really, Those core enabling technologies can also be quite revolutionary. >> Absolutely. Yeah, absolutely. So the coop insights now, and you're seeing that measured against others and its mass, but you see how you're doing it, So this is really powerful sitting your goals out there and seeing how you're doing. Adjusting those really question yourself is, if we're not getting is approved in the speed that we thought, How do we do it differently? Right, So and that's nice about Cuba. It is really sounds right, and they really do come out with three releases a year, which is powerful. And so it's always changing, which means you have to be nimble. Understand your organization, adopting the new technologies to come out. They're also looking at their acquisitions and seeing that fits into what you're doing. >> Exactly. Last question for you is the announcement of the expansion of their in the AWS marketplace today and thinking, Wow, the I t person is probably gonna finally all these Shadow I T units that are popping up in finance and marketing and engineering and whatnot. They now have the ability to see and manage the entire software from search to deployment and management through AWS. What advantage is that going to give Deloitte when you're working with Cooper customers on implementation? >> That's probably too soon to say on that one. All the expansions they're having really help us with another tool. Tell clients I would say that there's always measuring the benefit for that client in the risk. So even if you take Amazon, for example, just opened by for Cooper is managing that So Amazon. When they first came out with Amazon for business open by, you couldn't control the categories that were exposed to the client. Now you can, but you can't control the items. So having a process in place, having a category strategy and then maximizing it if Amazon works that client fantastic, AWS is gonna get them or visibility across their platforms to manage those better. Fantastic. I think it just gives another opportunity to bring clients back into Cooper. Have a look at the value for Cooper from an end and solution, and all these wraparound acquisitions are making our expansions with their clients, people pay and all those other pieces out there. It's just another thing for them to have a goal and understand make a decision from their business, whether they're going to use it or not. But there's there's value across the board. Every every client is different, >> Absolutely. But it's also that that consumer ization approach that if you can take a process that somebody does on their own time, whether they're buying soccer balls or pool and bring that to their business life, that consumer ization following them. You think with potential there to transform every industry, every function, every line of business. It's just infinite. So >> truly dot, >> dot dot to me. Continue. Absolutely Wish we had more time. But Max, thank you so much for joining me on the Cube today and talk doing talking to me about what's going on at Deloitte and congrats on having us standing. You're only sessions. That's good, right? Take for Max Ground like I'm Lisa Martin. You're watching the Cube from Cooper Inspire 19. Thanks for watching.

>> Announcer: Live from Washington D.C. it's The Cube covering AWS Public Sector Summit, brought to you by Amazon Web Services. >> Welcome back everyone to The Cube's live coverage of the AWS Public Sector summit here in our nation's capitol, I'm your host Rebecca Knight. Co-hosting alongside analyst John Furrier. We are welcoming today Troy Bertram. He is the GM Public Business Development Worldwide Public Sector at AWS. Thanks so much for coming on The Cube, Troy >> Thanks for having me Rebecca >> Rebecca: A first timer. >> It is the first time. >> Rebecca: Welcome. >> Yes, thank you John, thank you Rebecca. >> Let's talk about your partner organization. Why don't you let our viewers know how it's structured, what its mission is, how it works. >> Yes, certainly. Our public sector partner teams work with our partners around the world that really support the mission requirements of government, education, and non-profits. Our partners are part of the large Amazon partner network, so 35,000 plus partners, but really our customers choose, Whether it's technology partners that have really focused their SaaS, PaaS, ISV solutions on government customers and worked through accreditations and certifications, or it's the consulting partners that go to market and own the prime contract vehicles. Contracts are how our customers buy in public sector. What we've done is really focused our teams from start-ups, and venture capitalists, and incubators, through technology, ISVs, PaaS and SaaS partners to our large consulting partners; global consulting partners, but also really helping curate those consulting partners that meet socioeconomic requirements. Often times governments have laws, regulations to buy small woman owned 8(a), service disabled veteran, as veteran, one of my near and dear partner subset to me, and we work with them to help navigate through and develop programs to work through the APN, and often times it's a partner to partner activity of a consulting partner working with a specialized ISV technology solution that can meet a customer's mission requirements. >> What's interesting about the cloud, we've been talking about our intro this morning is the agility and government's now seeing it benefits, and it's not just and aha moment anymore cloud is really, it's driving a lot of change. That's been lifting up a lot of your partner profiles. You have start-ups to large entities all playing together because the requirements my change based upon either the agency or the public sector entity. >> Yes. >> Have unique needs, so you have a broad range of partners. How do you guys nurture that? That's good diversity. You have nice solution set from tech to business. How do you guys nurture that? What's some of the challenges and opportunities you guys are seeing with the growth. >> Cloud is really allowed a reset for many of our partners. Whether you are born in the cloud company, that doesn't necessarily have a long legacy, and haven't built an entire infrastructure, and you don't have an infrastructure of people, but also don't have technology debt that you've been burdened with because of your prior operating models. It's nurturing that born in the cloud company that maybe a services oriented migration partner that's focused on moving our customers applications and workloads, or it's nurturing the technology and helping them build, or it's a refactor and a legacy on premise solution or those solution providers that have traditionally operated in an on-prem environment. Helping them train, certify, and really build a new practice. >> And it's exciting too. You got the ecosystem kind of approach where, you know a thousand flowers can bloom. I've got to ask you, what do you see sprouting up? What's growing most? What is some of the trends that you see in the partner ecosystem? What's growing fast? What's the demand? What's the hot area? >> The real demand is for people with skill sets. In our business, skill sets also often include security clearances, and a knowledge of the working environment that they're migrating from. We're spending an inordinate amount training and educating. Also, our partner selling community of understanding the dynamics of how to go to market, and the contract vehicles, and how to navigate. The opportunities are really immense. It's nurturing those thousand flowers, and it is a challenge for many of us. How do we nurture those thousand flowers simultaneously? >> Are you finding the right people? A big theme on The Cube here is the skills gap. I just saw a Deloitte survey. 60% of executives, and these are executives, they're not in the public sector, said a skills gap hindered their AI initiatives and hindering their cloud computing initiatives. What are you seeing? What are you hearing from the people you're talking to? >> There's a thirst for both knowledge and training, but there's also, from the executive side, we have a need to fill. There's an abundance of roles, and all of us working together. One of our initiatives is even the job boards that we're working with our educate team and Ken Eisner a peer that leads that is, we're helping our partners promote their open roles. Allowing our partners to look for and curate the same talent that Amazon is helping train and develop because when our partners can find amazing talent, our customers win. It benefits AWS and the partner ecosystem. >> Education's huge. You got to have the ongoing digital course ware. Is that a top priority for you? What are some of your top goals for this year in your plan? >> When it comes to education, top goal is training many of our new partners through our emerging partner team. Many of the new partners have a commercial practice. We're also looking at those partners and actively recruiting those partners that have built a commercial practice that are looking to enter government. Whether it's our distributors or our resellers that own the prime contract vehicles, we're doing partner to partner activities. We call it partner speed dating. It's contract vehicles that exist across state and local government, US federal, or in the international community for those ISVs that want to enter new market regions is pairing with those existing local companies that have contract vehicles and then helping train and educate on the nuances of public sector. >> We were talking with General Keith Alexander and retired General Yesthidae came on and I asked them directly, if you could a magic wand, I think I said, something along the lines of if you had a magic wand, what would you do to change the government? It could go faster. He said the technology check we're doing very well, it's moving along great, it's the procurement process. It's just too long. He mentioned contracts. This is really the key point we keep hearing. The red tape. What's the update there? I'm sure partners aren't wanting more red tape. They want to cut through it, to your point. >> No. It's really an education process. When I started at Amazon over six and a half years ago, my first role was to stand up, and it still is the core of my role, I have individuals in 22 different countries around the world, and we're helping governments and VR partners through the procurement process. We did this past week in my home state of Minnesota, our 10,000th RFX, so we consider an FRP, FRI, an RFQ a tender, I need to buy, I want to buy something. We responded to 10,000 of those in six years and two months. That's an abundance of contract that ultimately, many of them are task orders and IDIQs and GWAX. There's an abundance of pathways as General Alexander stated for customers to buy the technology. Now it's educating the contracting officers, the COs, the KOs, around the world on the existing pathways and how to leverage them. We still see old procurement methodologies being applied to the cloud, and it does slow down the end customer's mission requirements. >> And the path to value. >> Yes, the path to value. Exactly. They want to move and move fast and contracts is how we buy, but it's also what slows us down. >> You know, you're with Amazon six years plus, so you know this, so the speeds of value's been the key thing for the cloud. As you look at success now with Amazon public sector, not only in the US, but abroad and internationally, you got massive tailwinds on the success. The growth is phenomenal. How does that feel? What's some observations? What's some learnings that you can take away from the past few years and where's it going? >> It feels like it's day one. It does feel like it's day one. There are tailwinds, but there's still an abundance of customer requirements, and they're evolving, and they're more complex. I personally really like my career's been public sector. Solving the mission requirements, whether it's helping a forward deployed airman, soldier, really keeping them at the cutting edge of technology, and out of harms way, or our first responders; some of the new product demonstrations that we've seen of evolving technology that's helping a firefighter see from an aerial drone vehicle. What does it look like on the other side of this building, and how can I now communicate across different agencies? Is phenomenal. In my home state, where Army Futures Command, I live in Austin, Texas. Army Futures Command is working with the state of Texas as well as the University of Texas to really collaborate as we've never seen before. The barriers of emerging technology to legacy government, to ministries, and health defenses around the world, ministries of defense, and health agencies around the world. >> The data, the scale of Amazon cloud is going to to make that possible. Ground Station's a great example of how that's growing like a weed. The DOD has got a great charter around using agility and AI. >> Collaboration, which is so critical too, as you said. >> It is, and our VM Ware partnership with VM Ware on AWS can really help, and that's a partner play. That's partners helping migrate using the co-developed technology to really move and move faster. Use those existing apps and vacate those data centers. >> Well, thanks for coming on The Cube. Got to be a quick plug, plug the organization, share with the audience, what you're looking for, and update on the partner network. Give a quick plug for your group. >> What we're really looking for is, we've got 105 different competency partners that have really invested in their government, their education, their non-profit competency, and we want to help. I personally want to help them promote their business, and what the opportunity is to connect to either other partners or to government mission requirements. Really welcome the opportunity, John, to come on and look forward to seeing my partners on The Cube in the future. Thank you. >> Well, Troy Bertram, you are now a Cube alum, >> A Cube alum >> Thank you. (panel laughing) >> Thank you. >> I'm Rebecca Knight for John Furrier, you are watching The Cube, stay tuned for more AWS Public Sector Summit.