>>Partnerships in the technology business, they take many forms. For example, technology engineering partnerships, they drive value in terms of things like integration and simplification for customers. There are product partnerships. They fill gaps to create more comprehensive portfolios and more fluid relationships. Partner ecosystems offer high touch services. They offer managed services, specialty services, and other types of value based off of strong customer knowledge and years of built up trust partner. Ecosystems have evolved quite dramatically over the last decade with the explosion of data and the popularity of cloud models. Public, private, hybrid cross clouds. You know, yes it's true. Partnerships are about selling solutions, but they're also about building long term sustainable trust, where a seller learns the ins and outs of a customer's organization and can anticipate needs that are gonna drive bottom line profits for both sides of the equation, the buyer and the seller. >>Hello and welcome to our program. My name is Dave Ante and along with Lisa Martin, we're going to explore how Hitachi Van Tara drives customer success with its partners. First up, Lisa speaks with Kim King. She's the senior vice president of Strategic Partners and Alliances at Hitachi Van. And they'll set the table for us with an overview of how Hitachi is working with partners and where their priorities are focused. Then Russell Kingsley, he's the CTO and global VP of Technical sales at Hitachi Van Tara. He joins Lisa for a discussion of the tech and they're gonna get into cloud generally and hybrid cloud specifically in the role that partners play in the growing as a service movement. Now, after that I'll talk with Tom Christensen, he's the global technology advisor and executive analyst at Hitachi Vitara. And we're gonna talk about a really important topic, sustainability. We're gonna discuss where it came from, why it matters, and how it can drive bottom line profitability for both customers and partners. Let's get right to it. >>Where for the data driven, for those who understand clarity is currency. Believe progress requires precision and no neutral is not an option. We're for the data driven. The ones who can't tolerate failure, who won't put up with downtime or allow access to just anyone. We're for the data driven who act on insight instead of instinct. Bank on privacy instead of probabilities and rely on resilience instead of reaction. We see ourselves in the obsessive, the incessant, progressive, and the meticulously engineered. We enable the incredible identify with the analytical and are synonymous with the mission critical. We know what it means to be data driven because data is in our dna. We were born industrial and and we breathe digital. We speak predictive analytics so you can keep supply chains moving. We bleed in store and online insights so you can accurately predict customer preferences. We sweat security and digital privacy so you can turn complex regulations into competitive advantage. We break down barriers and eliminate silos. So you can go from data rich to data driven because it's clear the future belongs to the data driven. >>Hey everyone, welcome to this conversation. Lisa Martin here with Kim King, the SVP of Strategic Partners and Alliances at Hitachi Ventera. Kim, it's great to have you on the program. Thank you so much for joining me today. >>Thanks Lisa. It's great to be here. >>Let's talk about, so as we know, we talk about cloud all the time, the landscape, the cloud infrastructure landscape increasingly getting more and more complex. What are some of the biggest challenges and pain points that you're hearing from customers today? >>Yeah, so lot. There are lots, but I would say the, the few that we hear consistently are cost the complexity, right? Really the complexity of where do they go, how do they do it, and then availability. They have a lot of available options, but again, going back to complexity and cost, where do they think that they should move and how, how do they make that a successful move to the cloud? >>So talk to me, Hitachi Ventura has a great partner ecosystem. Where do partners play a role in helping customers to address some of the challenges with respect to the cloud landscape? >>Yeah, so part, our partners are really leading the way in the area of cloud in terms of helping customers understand the complexities of the cloud. As we talked about, they're truly the trusted advisor. So when they look at a customer's complete infrastructure, what are the workloads, what are the CRI critical applications that they work with? What's the unique architecture that they have to drive with that customer for a successful outcome and help them architect that? And so partners are truly leading the way across the board, understanding the complexities of each individual customer and then helping them make the right decisions with and for them. And then bringing us along as part of that, >>Talk to me a little bit about the partner landscape, the partner ecosystem at Hitachi Ventura. How does this fit into the overall strategy for the company? >>So we really look at our ecosystem as an extension of our sales organization and and really extension across the board, I would say our goal is to marry the right customer with the right partner and help them achieve their goals, ensure that they keep costs in check, that they ensure they don't have any security concerns, and that they have availability for the solutions and applications that they're trying to move to the cloud, which is most important. So we really, we really look at our ecosystem as a specialty ecosystem that adds high value for the right customers. >>So Kim, talk to me about how partners fit into Hitachi van's overall strategy. >>So I think our biggest differentiators with partners is that they're not just another number. Our partner organization is that valued extension of our overall sales pre-sales services organization. And we treat them like an extension of our organization. It's funny because I was just on a call with an analyst earlier this week and they said that AWS has increased their number of partners to 150,000 partners from, it was just under a hundred thousand. And I'm really not sure how you provide quality engagement to partners, right? And is how is that really a sustainable strategy? So for us, we look at trusted engagement across the ecosystem as a def differentiation. Really our goal is to make their life simple and profitable and really become their primary trusted partner when we go to market with them. And we see that paying dividends with our partners as they engage with us and as they expand and grow across the segments and then grow globally with us as well. >>And that's key, right? That synergistic approach when you're in customer conversations, what do you articulate as the key competitive differentiators where it relates to your partners? >>So really the, that they're the trusted advisor for that partner, right? That they understand our solutions better than any solution out there. And because we're not trying to be all things to our customers and our partners that we being bring best breaths of breed, best of breed solutions to our customers through our partner community, they can truly provide that end user experience and the successful outcome that's needed without, you know, sort of all kinds of, you know, crazy cha challenges, right? When you look at it, they really wanna make sure that they're driving that co-developed solution and the successful outcome for that customer. >>So then how do you feel that Hitachi Ventura helps partners really to grow and expand their own business? >>Wow, so that's, there's tons of ways, but we've, we've created a very simplified, what we call digital selling platform. And in that digital selling platform, we have allowed our partners to choose their own price and pre-approve their pricing and their promotions. They've actually, we've expanded the way we go to market with our partners from a sort of a technical capabilities. We give them online what we call Hitachi online labs that allow them to really leverage all of the solutions and demo systems out there today. And they have complete access to any one of our resources, product management. And so we really have, like I said, we actually provide our partners with better tools and resources sometimes than we do our own sales and pre-sales organization. So we, we look at them as, because they have so many other solutions out there that we have to be one step ahead of everybody else to give them that solution capability and the expertise that they need for their customers. >>So if you dig in, where is it that Hiti is helping partners succeed with your portfolio? >>Wow. So I think just across the board, I think we're really driving that profitable, trusted, and simplified engagement with our partner community because it's a value base and ease of doing business. I say that we allow them to scale and drive that sort of double digit growth through all of the solutions and and offerings that we have today. And because we've taken the approach of a very complex technical sort of infrastructure from a high end perspective and scale it all the way through to our mid-size enterprise, that allows them to really enter any customer at any vertical and provide them a really quality solution with that 100% data availability guarantee that we provide all of our customers. >>So then if we look at the overall sales cycle and the engagement, where is it that you're helping cus your partners rather succeed with the portfolio? >>Say that again? Sorry, my brain broke. No, >>No worries. So if we look at the overall sales cycle, where is it specifically where you're helping customers to succeed with the portfolio? >>So from the sales cycle, I think because we have the, a solution that is simple, easy, and really scaled for the type of customer that we have out there, it allows them to basically right size their infrastructure based on the application, the workload, the quality or the need that application may have and ensure that we provide them with that best solution. >>So then from a partner's perspective, how is it that Hitachi van is helping them to actually close deals faster? >>Yeah, so lots of great ways I think between our pre-sales organization that's on call and available a hundred percent of the time, I think that we've seen, again, the trusted engagement with them from a pricing and packaging perspective. You know, we, you know, two years ago it would take them two to three weeks to get a pre-approved quote where today they preapproved their own quotes in less than an hour and can have that in the hands of a customer. So we've seen that the ability for our partners to create and close orders in very short periods of time and actually get to the customer's needs very quickly, >>So dramatically faster. Yes. Talk about overall, so the partner relationship's quite strong, very synergistic that, that Hitachi Ventura has with its customers. Let's kind of step back out and look at the cloud infrastructure. How do you see it evolving the market evolving overall in say the next six months, 12 months? >>Yeah, so we see it significantly, we've been doing a lot of studies around this specifically. So we have a couple of different teams. We have our sort of our standard partner team that's out there and now we have a specialty cloud service provider team that really focuses on partners that are building and their own infrastructure or leveraging the infrastructure of a large hyperscaler or another GSI and selling that out. And then what we found is when we dig down deeper into our standard sort of partner reseller or value added reseller market, what we're seeing is that they are want to have the capability to resell the solution, but they don't necessarily wanna have to own and manage the infrastructure themselves. So we're helping both of them through that transition. We see that it's gonna, so it's funny cuz you're seeing a combination of many customers move to really the hyperscale or public cloud and many of them want to repatriate their infrastructure back because they see costs and they see challenges around all of that. And so our partners are helping them understand, again, what is the best solution for them as opposed to let's just throw everything in the public cloud and hope that it works. We're we're really helping them make the right choices and decisions and we're putting the right partners together to make that happen. >>And how was that feedback, that data helping you to really grow and expand the partner program as a whole? >>Yeah, so it's been fantastic. We have a whole methodology that we, we created, which is called PDM plan, develop monetize with partners. And so we went specifically to market with cloud service providers that'll, and we really tested this out with them. We didn't just take a solution and say, here, go sell it, good luck and have, you know, have a nice day. Many vendors are doing that to their partners and the partners are struggling to monetize those solutions. So we spend a lot of time upfront planning with them what is not only the storage infrastructure but your potentially your data resiliency and, and everything else that you're looking at your security solutions. How do we package those all together? How do we help you monetize them? And then who do you target from a customer perspective so that they've built up a pipeline of opportunities that they can go and work with us on and we really sit side by side with them in a co-development environment. >>In terms of that side by side relationship, how does the partner ecosystem play a role in Hitachi Venturas as a service business? >>So our primary go to market with our, as a service business is with and through partners. So our goal is to drive all, almost all of of our as a service. Unless it's super highly complex and something that a partner cannot support, we will make sure that they really, we leverage that with them with all of our partners. >>So strong partner relationships, very strong partner ecosystem. What would you say, Kim, are the priorities for the partner ecosystem going forward? The next say year? >>Yeah, so we have tons of priorities, right? I think really it's double digit growth for them and for us and understanding how a simpler approach that's customized for the specific vertical or customer base or go to market that they have that helps them quickly navigate to be successful. Our goal is always to facilitate trusted engagements with our partners, right? And then really, as I said, directionally our goal is to be 95 to a hundred percent of all of our business through partners, which helps customers and then really use that trusted advisor status they have to provide that value base to the customer. And then going back on our core tenants, which are, you know, really a trusted, simplified, profitable engagement with our partner community that allows them to really drive successful outcomes and go to market with us. And the end users >>Trust is such an important word, we can't underutilize it in these conversations. Last question. Sure. From a channel business perspective, what are some of the priorities coming down the pi? >>Oh, again, my biggest priority right, is always to increase the number of partner success stories that we have and increase the value to our partners. So we really dig in, we, we right now sit about number one or number two in, in our space with our partners in ease of doing business and value to our channel community. We wanna be number one across the board, right? Our goal is to make sure that our partner community is successful and that they really have those profitable engagements and that we're globally working with them to drive that engagement and, and help them build more profitable businesses. And so we just take tons of feedback from our partners regularly to help them understand, but we, we act on it very quickly so that we can make sure we incorporate that into our new program and our go to markets as we roll out every year. >>It sounds like a great flywheel of communications from the partners. Kim, thank you so much for joining me today talking about what Hitachi Vanta is doing with its partner ecosystem, the value in IT for customers. We appreciate your insights. >>Thank you very much. >>Up next, Russell Kingsley joins me, TTO and global VP of technical sales at Hitachi van you watch in the cube, the leader in live tech coverage. Hey everyone, welcome back to our conversation with Hitachi van Tara, Lisa Martin here with Russell Skillings Lee, the CTO and global VP of technical sales at Hitachi Van Russell. Welcome to the program. >>Hi Lisa, nice to be here. >>Yeah, great to have you. So here we are, the end of calendar year 2022. What are some of the things that you're hearing out in the field in terms of customers priorities for 2023? >>Yeah, good one. Just to, to set the scene here, we tend to deal with enterprises that have mission critical IT environments and this has been been our heritage and continues to be our major strength. So just to set the scene here, that's the type of customers predominantly I'd be hearing from. And so that's what you're gonna hear about here. Now, in terms of 20 23, 1 of the, the macro concerns that's hitting almost all of our customers right now, as you can probably appreciate is power consumption. And closely related to that is the whole area of ESG and decarbonization and all of that sort of thing. And I'm not gonna spend a lot of time on that one because that would be a whole session in itself really, but sufficient to say it is a priority for us and we, we are very active in, in that area. >>So aside from from that one that that big one, there's also a couple that are pretty much in common for most of our customers and, and we're in areas that we can help. One of those is in an exponential growth of the amount of data. It's, it's predicted that the world's data is going to triple by 2025 as opposed to where it was in 2020. And I think everyone's contributing to that, including a lot of our customers. So just the, the act of managing that amount of data is, is a challenge in itself. And I think closely related to that, a desire to use that data better to be able to gain more business insights and potentially create new business outcomes and business ideas are, is another one of those big challenges in, in that sense, I think a lot of our customers are in what I would kind of call, I affectionately call the, the post Facebook awakening era. >>And that, and what I mean by that is our traditional businesses, you know, when Facebook came along, they kind of illustrated, hey, I can actually make some use out of what is seemingly an enormous amount of useless data, which is exactly what Facebook did. They took a whole lot of people's Yeah. The minutia of people's lives and turned it into, you know, advertising revenue by gaining insights from, from those, you know, sort of seemingly useless bits of data and, you know, right. And I think this actually gave rise to a lot of digital business at that time. You know, the, this whole idea of what all you really need to be successful and disrupt the business is, you know, a great idea, you know, an app and a whole bunch of data to, to power it. And I think that a lot of our traditional customers are looking at this and wondering how do they get into the act? Because they've been collecting data for decades, an enormous amount of data, right? >>Yes. I mean, every company these days has to be a data company, but to your point, they've gotta be able to extract those insights, monetize it, and create real value new opportunities for the business at record speed. >>Yes, that's exactly right. And so being able to, to wield that data somehow turn it, it kind of turns out our customer's attentions to the type of infrastructure they've got as well. I mean, if you think about those, those companies that have been really successful in leveraging that data, a lot of them have, especially in the early days, leverage the cloud to be able to build out their capabilities. And, and the reason why the cloud became such a pivotal part of that is because it offered self-service. IT and, you know, easy development platforms to those people that had these great ideas. All they needed was access to, to, you know, the provider's website and a credit card. And now all of a sudden they could start to build a business from that. And I think a lot of our traditional IT customers are looking at this and thinking, now how do I build a similar sort of infrastructure? How do I, how do I provide that kind of self-service capability to the owners of business inside my company rather than the IT company sort of being a gatekeeper to a selected set of software packages. How now do I provide this development platform for those internal users? And I think this, this is why really hybrid cloud has become the defacto IT sort of architectural standard, even even for quite traditional, you know, IT companies. >>So when it comes to hybrid cloud, what are some of the challenges the customers are facing? And then I know Hitachi has a great partner ecosystem. How are partners helping Hitachi Ventura and its customers to eliminate or solve some of those hybrid cloud challenges? >>Yeah, it's, it, it's a great question and you know, it's, it's not 1975 anymore. It's not, it's not like you're going to get all of your IT needs from, from one, from one vendor hybrid by sort of, it's, you know, by definition is going to involve multiple pieces. And so there basically is no hybrid at all without a partner ecosystem. You really can't get everything at, at a one stop shop like you used to. But even if you think about the biggest public cloud provider on the planet, aws even, it has a marketplace for partner solutions. So, so even they see, even for customers that might consider themselves to be all in on public cloud, they are still going to need other pieces, which is where their marketplace come comes in. Now for, for us, you know, we are, we're a company that, we've been in the IT business for over 60 years, one of one of the few that could claim that sort of heritage. >>And you know, we've seen a lot of this type of change ourselves, this change of attitude from being able to provide everything yourself to being someone who contributes to an overall ecosystem. So partners are absolutely essential. And so now we kind of have a, a partner first philosophy when it comes to our routes to market on, you know, not just our own products in terms of, you know, a resale channel or whatever, but also making sure that we are working with some of the biggest players in hybrid infrastructure and determining where we can add value to that in our, in our own solutions. And so, you know, when it comes to those, those partner ecosystems, we're always looking for the spaces where we can best add our own capability to those prevailing IT architectures that are successful in the marketplace. And, you know, I think that it's probably fair to say, you know, for us, first and foremost, we, we have a reputation for having the biggest, most reliable storage infrastructure available on the planet. >>And, and we make no apologies for the fact that we tout our speeds and feeds and uptime supremacy. You know, a lot of our, a lot of our competitors would suggest that, hey, speeds and feeds don't matter. But you know, that's kind of what you say when, when you're not the fastest or not the most reliable, you know, of course they matter. And for us, what we, the way that we look at this is we say, let's look at who's providing the best possible hybrid solutions and let's partner with them to make those solutions even better. That's the way we look at it. >>Can you peel the, the onion a little bit on the technology underpinning the solutions, give a glimpse into that and then maybe add some color in terms of how partners are enhancing that? >>Yeah, let me, let me do that with a few examples here, and maybe what I can do is I can sort of share some insight about the way we think with partnering with, with particular people and why it's a good blend or why we see that technologically it's a good blend. So for example, the work we do with VMware, which we consider to be one of our most important hybrid cloud partners and in, and in fact it's, it's my belief, they have one of the strongest hybrid cloud stories in the industry. It resonates really strongly with, with our customers as well. But you know, we think it's made so much better with the robust underpinnings that we provide. We're one of the, one of the few storage vendors that provides a 100% data availability guarantee. So we, we take that sort of level of reliability and we add other aspects like life cycle management of the underpinning infrastructure. >>We combine that with what VMware's doing, and then when you look at our converged or hyper-converged solutions with them, it's a better together story where you now have what is one of the best hybrid cloud stories in the industry with VMware. But now for the on premise part, especially, you've now added a hundred percent data, data availability guarantee, and you've made managing the underlying infrastructure so much easier through the tools that we provide that go down to that level A level underneath where VMware are. And so that's, that's VMware. I've got a couple, couple more examples just to sort of fill, fill that out a bit. Sure. Cisco is another part, very strong partner of ours, a key partner. And I mean, you look at Cisco, they're a 50 billion IT provider and they don't have a dedicated storage infrastructure of their own. So they're going to partner with someone. >>From our perspective, we look at Cisco's, Cisco's customers and we look at them and think they're very similar to our own in terms of they're known to appreciate performance and reliability and a bit of premium in quality, and we think we match them them quite well. They're already buying what we believe are the best converge platforms in the industry from Cisco. So it makes sense that those customers would want to compliment that investment with the best array, best storage array they can get. And so we think we are helping Cisco's customers make the most of their decision to be ucs customers. Final one for, for you, Lisa, by way of example, we have a relationship with, with Equinix and you know, Equinix is the world's sort of leading colo provider. And the way I think they like to think of themselves, and I too tend to agree with them, is their, they're one of the most compelling high-speed interconnect networks in the world. >>They're connected to all of the, the, the significant cloud providers in most of the locations around the world. We have a, a relationship with them where we find we have customers in common who really love the idea of compute from the cloud. Compute from the cloud is great because compute is something that you are doing for a set period of time and then it's over you. Like you have a task, you do some compute, it's done. Cloud is beautiful for that. Storage on the other hand is very long lived storage doesn't tend to operate in that same sort of way. It sort of just becomes a bigger and bigger blob over time. And so the cost model around public cloud and storage is not as compelling as it is for compute. And so our, with our relationship with Equinix, we help our customers to be able to create, let's call it a, a data anchor point where they put our arrays into, into an Equinix location, and then they utilize Equinix as high speeding interconnects to the, to the cloud providers, okay. To take the compute from them. So they take the compute from the cloud providers and they own their own storage, and in this way they feel like we've now got the best of all worlds. Right. What I hope that illustrates Lisa is with those three examples is we are always looking for ways to find our key advantages with any given, you know, alliance partners advantages, >>Right? What are, when you're in customer conversations, and our final few minutes here, I wanna get, what are some of the key differentiators that you talk about when you're in customer conversations, and then how does the partner ecosystem fit into Hitachi vans as a service business? We'll start with differentiators and then let's move into the as service business so we can round out with that. >>Okay. Let's start with the differentiators. Yeah. Firstly and I, and hopefully I've kind of, I've hit this point hard, hard enough. We do believe that we have the fastest and most reliable storage infrastructure on the planet. This is kind of what we are known for, and customers that are working with us already sort of have an appreciation for that. And so they're looking for, okay, you've got that now, how can you make my hybrid cloud aspirations better? So we do have that as a fundamental, right? So, but secondly I'd say, I think it's also because we go beyond just storage management and, and into the areas of data management. You know, we've got, we've got solutions that are not just about storing the bits. We do think that we do that very well, but we also have solutions that move into the areas of enrichment, of the data, cataloging of the data, classification of the data, and most importantly, analytics. >>So, you know, we, we think it's, some of our competitors just stop at storing stuff and some of our competitors are in the analytics space, but we feel that we can bridge that. And we think that that's a, that's a competitive advantage for us. One of the other areas that I think is key for us as well is, as I said, we're one of the few vendors who've been in the marketplace for 60 years and we think this, this, this gives us a more nuanced perspective about things. There are many things in the industry, trends that have happened over time where we feel we've seen this kind of thing before and I think we will see it again. But you only really get that perspective if you are, if you are long lived in the industry. And so we believe that our conversations with our customers bear a little bit more sophistication. It's not just, it's not just about what's the latest and greatest trends. >>Right. We've got about one minute left. Can you, can you round us out with how the partner ecosystem is playing a role in the as service business? >>They're absolutely pivotal in that, you know, we, we ourselves don't own data centers, right? So we don't provide our own cloud services out. So we are 100% partner focused when it comes to that aspect. Our formula is to help partners build their cloud services with our solutions and then onsell them to their customers as as as a service. You know, and by what quick way of example, VMware for example, they've got nearly 5,000 partners selling VMware cloud services. 5,000 blows me away. And many of them are our partners too. So we kind of see this as a virtuous cycle. We've got product, we've got an an alliance with VMware and we work together with partners in common for the delivery of an as a service business. >>Got it. So the, as you said, the partner ecosystem is absolutely pivotal. Russell, it's been a pleasure having you on the program talking about all things hybrid cloud challenges, how Hitachi van is working with its partner ecosystems to really help customers across industries solve those big problems. We really appreciate your insights and your time. >>Thank you very much, Lisa. It's been great. >>Yeah, yeah. For Russell Stingley, I'm Lisa Martin. In a moment we're gonna continue our conversation with Tom Christensen. Stay tuned. >>Sulfur Royal has always embraced digital technology. We were amongst the first hospitals in the UK to install a full electronic patient record system. Unfortunately, as a result of being a pioneer, we often find that there's gaps in the digital solutions. My involvement has been from the very start of this program, a group of us got together to discuss what the problems actually were in the hospital and how we could solve this. >>The digital control center is an innovation that's been designed in partnership between ourselves, anti touch, and it's designed to bring all of the information that is really critical for delivering effective and high quality patient care. Together the DCC is designed not only to improve the lives of patients, but also of our staff giving us information that our demand is going to increase in the number of patients needing support. The technology that we're building can be replicated across sulfur, the NCA, and the wider nhs, including social care and community services. Because it brings all of that information that is essential for delivering high quality efficient care. >>The DCC will save time for both staff and more importantly our patients. It will leave clinicians to care for patients rather than administrate systems and it will allow the system that I work with within the patient flow team to effectively and safely place patients in clinically appropriate environments. >>But we chose to partner with Hitachi to deliver the DCC here at Sulfur. They were willing to work with us to co-produce and design a product that really would work within the environment that we find ourselves in a hospital, in a community setting, in a social care setting. >>My hopes for the DCC is that ultimately we will provide more efficient and reliable care for our patients. >>I do believe the digital control center will improve the lives of staff and also the patients so that we can then start to deliver the real change that's needed for patient care. >>Okay, we're back with Tom Christensen, who's the global technology advisor and executive analyst at Hitachi Van Tara. And we're exploring how Hitachi Van Tower drives customer success specifically with partners. You know Tom, it's funny, back in the early part of the last decade, there was this big push around, remember it was called green it and then the oh 7 0 8 financial crisis sort of put that on the back burner. But sustainability is back and it seems to be emerging as a mega trend in in it is, are you seeing this, is it same wine new label? How real is this trend and where's the pressure coming from? >>Well, we clearly see that sustainability is a mega trend in the IT sector. And when we talk to CIOs or senior IT leaders or simply just invite them in for a round table on this topic, they all tell us that they get the pressure from three different angles. The first one is really end consumers and end consumers. Nowaday are beginning to ask questions about the green profile and what are the company doing for the environment. And this one here is both private and public companies as well. The second pressure that we see is coming from the government. The government thinks that companies are not moving fast enough so they want to put laws in that are forcing companies to move faster. And we see that in Germany as an example, where they are giving a law into enterprise companies to following human rights and sustainability tree levels back in the supply chain. >>But we also see that in EU they are talking about a new law that they want to put into action and that one will replicate to 27 countries in Europe. But this one is not only Europe, it's the rest of the world where governments are talking about forcing companies to move faster than we have done in the past. So we see two types of pressure coming in and at the same time, this one here starts off at the CEO at a company because they want to have the competitive edge and be able to be relevant in the market. And for that reason they're beginning to put KPIs on themself as the ceo, but they're also hiring sustainability officers with sustainability KPIs. And when that happens it replicates down in the organization and we can now see that some CIOs, they have a kpi, others are indirectly measured. >>So we see direct and indirect. The same with CFOs and other C levels. They all get measured on it. And for that reason it replicates down to IT people. And that's what they tell us on these round table. I get that pressure every day, every week, every quarter. But where is the pressure coming from? Well the pressure is coming from in consumers and new laws that are put into action that force companies to think differently and have focus on their green profile and doing something good for the environment. So those are the tree pressures that we see. But when we talk to CFOs as an example, we are beginning to see that they have a new store system where they put out request for proposal and this one is in about 58% of all request for proposal that we receive that they are asking for our sustainability take, what are you doing as a vendor? >>And in their score system cost has the highest priority and number two is sustainability. It waits about 15, 20 to 25% when they look at your proposal that you submit to a cfo. But in some cases the CFO say, I don't even know where the pressure is coming from. I'm asked to do it. Or they're asked to do it because end consumers laws and so on are forcing them to do it. But I would answer, yeah, sustainability has become a make trend this year and it's even growing faster and faster every month we move forward. >>Yeah, Tom, it feels like it's here to stay this time. And your point about public policy is right on, we saw the EU leading with privacy and GDPR and it looks like it's gonna lead again here. You know, just shifting gears, I've been to a number of Hitachi facilities in my day. OWA is my favorite because on a clear day you can see Mount Fuji, but other plants I've been to as well. What does Hitachi do in the production facility to reduce CO2 emissions? >>Yeah, I think you're hitting a good point here. So what we have, we have a, a facility in Japan and we have one in Europe and we have one in America as well to keep our production close to our customers and reduced transportation for the factory out to our customers. But you know, in the, in the, in the May region back in 2020 13, we created a new factory. And when we did that we were asked to do it in an energy, energy neutral way, which means that we are moving from being powered by black energy to green energy in that factory. And we build a factory with concrete walls that were extremely thick to make it cold in the summertime and hot in the winter time with minimum energy consumption. But we also put 17,000 square meters of solar panel on the roof to power that factory. >>We were collecting rain waters to flush it in the toilet. We were removing light bulbs with L E D and when we sent out our equipment to our customers, we put it in a, instead of sending out 25 packages to a customer, we want to reduce the waste as much as possible. And you know, this one was pretty new back in 2013. It was actually the biggest project in EA at that time. I will say if you want to build a factory today, that's the way you are going to do it. But it has a huge impact for us when electricity is going up and price and oil and gas prices are coming up. We are running with energy neutral in our facility, which is a big benefit for us going forward. But it is also a competitive advantage to be able to explain what we have been doing the last eight, nine years in that factory. We are actually walking to talk and we make that decision even though it was a really hard decision to do back in 2013, when you do decisions like this one here, the return of investment is not coming the first couple of years. It's something that comes far out in the future. But right now we are beginning to see the benefit of the decision we made back in 2013. >>I wanna come back to the economics, but before I do, I wanna pick up on something you just said because you know, you hear the slogan sustainability by design. A lot of people might think okay, that's just a marketing slogan, slogan to vector in into this mega trend, but it sounds like it's something that you've been working on for quite some time. Based on your last comments, can you add some color to that? >>Yeah, so you know, the factory is just one example of what you need to do to reduce the CO2 emission and that part of the life of a a product. The other one is really innovating new technology to drive down the CO2 emission. And here we are laser focused on what we call decarbonization by design. And this one is something that we have done the last eight years, so this is far from you for us. So between each generation of products that we have put out over the last eight years, we've been able to reduce the CO2 emission by up to 30 to 60% between each generation of products that we have put into the market. So we are laser focused on driving that one down, but we are far from done, we still got eight years before we hit our first target net zero in 2030. So we got a roadmap where we want to achieve even more with new technology. At its core, it is a technology innovator and our answers to reduce the CO2 emission and the decarbonization of a data center is going to be through innovating new technology because it has the speed, the scale, and the impact to make it possible to reach your sustainability objectives going forward. >>How about recycling? You know, where does that fit? I mean, the other day it was, you know, a lot of times at a hotel, you know, you used to get bottled water, now you get, you know, plant based, you know, waters in a box and, and so we are seeing it all around us. But for a manufacturer of your size, recycling and circular economy, how does that fit into your plans? >>Yeah, let me try to explain what we are doing here. Cause one thing is how you produce it. Another thing is how you innovate all that new technology, but you also need to combine that with service and software, otherwise you won't get the full benefit. So what we are doing here, when it comes to exploring circular economics, it's kind of where we have an eternity mindset. We want to see if it is possible to get nothing out to the landfill. This is the aim that we are looking at. So when you buy a product today, you get an option to keep it in your data center for up to 10 years. But what we wanna do when you keep it for 10 years is to upgrade only parts of the system. So let's say that you need more CBU power, use your switch the controller to next generation controller and you get more CPU power in your storage system to keep it those 10 years. >>But you can also expand with new this media flash media, even media that doesn't exist today will be supported over those 10 years. You can change your protocol in the, in the front end of your system to have new protocols and connect to your server environment with the latest and greatest technology. See, the benefit here is that you don't have to put your system into a truck and a recycle process after three years, four years, five years, you can actually postpone that one for 10 years. And this one is reducing the emission again. But once we take it back, you put it on the truck and we take it into our recycling facility. And here we take our own equipment like compute network and switches, but we also take competitor equipment in and we recycle as much as we can. In many cases, it's only 1% that goes to the landfill or 2% that goes to the landfill. >>The remaining material will go into new products either in our cycle or in other parts of the electronic industry. So it will be reused for other products. So when we look at what we've been doing for many years, that has been linear economics where you buy material, you make your product, you put it into production, and it goes into land feed afterwards. The recycling economics, it's really, you buy material, you make your product, you put it into production, and you recycle as much as possible. The remaining part will go into the landfill. But where we are right now is exploring circle economics where you actually buy material, make it, put it into production, and you reuse as much as you can. And only one 2% is going into the landfill right now. So we have come along and we honestly believe that the circular economics is the new economics going forward for many industries in the world. >>Yeah. And that addresses some of the things that we were talking about earlier about sustainability by design, you have to design that so that you can take advantage of that circular economy. I, I do wanna come back to the economics because, you know, in the early days of so-called green, it, there was a lot of talk about, well, I, I, I'll never be able to lower the power bill. And the facilities people don't talk to the IT people. And that's changed. So explain why sustainability is good business, not just an expense item, but can really drive bottom line profitability. I, I understand it's gonna take some time, but, but help us understand your experience there, Tom. >>Yeah, let me try to explain that one. You know, you often get the question about sustainability. Isn't that a cost? I mean, how much does it cost to get that green profile? But you know, in reality when you do a deep dive into the data center, you realize that sustainability is a cost saving activity. And this one is quite interesting. And we have now done more than 1,200 data center assessment around the world where we have looked at data centers. And let me give you just an average number from a global bank that we work with. And this one is, it is not different from all the other cases that we are doing. So when we look at the storage area, what we can do on the electricity by moving an old legacy data center into a new modernized infrastructure is to reduce the electricity by 96%. >>This is a very high number and a lot of money that you save, but the CO2 mission is reduced by 96% as well. The floor space can go up to 35% reduction as well. When we move down to the compute part, we are talking about 61% reduction in electricity on the compute part just by moving from legacy to new modern infrastructure and 61% on the CO2 emission as well. And see this one here is quite interesting because you save electricity and you and you do something really good for the environment. At the same time, in this case I'm talking about here, the customer was paying 2.5 million US dollar annually and by just modernizing that infrastructure, we could bring it down to 1.1 million. This is 1.4 million savings straight into your pocket and you can start the next activity here looking at moving from virtual machine to containers. Containers only use 10% of the CPU resources compared to a virtual machine. Move up to the application layer. If you have that kind of capability in your organization, modernizing your application with sustainability by design and you can reduce the C, the CO2 emission by up to 50%. There's so much we can do in that data center, but we often start at the infrastructure first and then we move up in the chain and we give customers benefit in all these different layers. >>Yeah, A big theme of this program today is what you guys are doing with partners do, are partners aware of this in your view? Are they in tune with it? Are they demanding it? What message would you like to give the channel partners, resellers and, and distributors who may be watching? >>So the way to look at it is that we offer a platform with product, service and software and that platform can elevate the conversation much higher up in the organization. And partners get the opportunity here to go up and talk to sustainability officers about what we are doing. They can even take it up to the CEO and talk about how can you reach your sustainability KPI in the data center. What we've seen this round table when we have sustainability officers in the room is that they're very focused on the green profile and what is going out of the company. They rarely have a deep understanding of what is going on at the data center. Why? Because it's really technical and they don't have that background. So just by elevating the conversation to these sustainability officers, you can tell them what they should measure and how they should measure that. And you can be sure that that will replicate down to the CIO and the CFO and that immediately your request for proposal going forward. So this one here is really a golden opportunity to take that story, go out and talk to different people in the organization to be relevant and have an impact and make it more easy for you to win that proposal when it gets out. >>Well really solid story on a super important topic. Thanks Tom. Really appreciate your time and taking us through your perspectives. >>Thank you Dave, for the invitation. >>Yeah, you bet. Okay, in a moment we'll be back. To summarize our final thoughts, keep it right there. >>Click by click. The world is changing. We make sense of our world by making sense of data. You can draw more meaning from more data than was ever possible before, so that every thought and every action can build your path to intelligent innovation to change the way the world works. Hitachi Van Tara. >>Okay, thanks for watching the program. We hope you gained a better understanding of how Hitachi Ventura drives customer success with its partners. If you wanna learn more about how you can partner for profit, check out the partner togetherPage@hitachiventera.com and there's a link on the webpage here that will take you right to that page. Okay, that's a wrap for Lisa Martin. This is Dave Valante with the Cube. You a leader in enterprise and emerging tech coverage.

(upbeat music) >> Hello, and welcome to this startup showcase. It's great to be here and talk about some of the innovations we are doing at AWS, how we work with our partner community, especially our open source partners. My name is Deepak Singh. I run our compute services organization, which is a very vague way of saying that I run a number of things that are connected together through compute. Very specifically, I run a container services organization. So for those of you who are into containers, ECS, EKS, fargate, ECR, App Runner Those are all teams that are within my org. I also run the Amazon Linux and BottleRocketing. So anything AWS does with Linux, both externally and internally, as well as our high-performance computing team. And perhaps very relevant to this discussion, I run the Amazon open source program office. Serving at AWS for over 13 years, almost 14, involved with compute in various ways, including EC2. What that has done has given me a vantage point of seeing how our customers use the services that we build for them, how they leverage various partner solutions, and along the way, how AWS itself has gotten involved with opensource. And I'll try and talk to you about some of those factors and how they impact, how you consume our services. So why don't we get started? So for many of you, you know, one of the things, there's two ways to look at AWS and open-source and Amazon in general. One is the number of contributors you may have. And the number of repositories that contribute to. Those are just a couple of measures. There are people that I work with on a regular basis, who will remind you that, those are not perfect measures. Sometimes you could just contribute to one thing and have outsized impact because of the nature of that thing. But it address being what it is, increasingly we'll look at different ways in which we can help contribute and enhance open source 'cause we consume a lot of it as well. I'll talk about it very specifically from the space that I work in the container space in particular, where we've worked a lot with people in the Kubernetes community. We've worked a lot with people in the broader CNCF community, as well as, you know, small projects that our customers might have got started off with. For example, I want to like talking about is Argo CD from Intuit. We were very actively involved with helping them figure out what to do with it. And it was great to see how into it. And we worked, etc, came together to think about get-ups at the Kubernetes level. And while those are their projects, we've always been involved with them. So we try and figure out what's important to our customers, how we can help and then take because of that. Well, let's talk about a little bit more, here's some examples of the kinds of open source projects that Amazon and AWS contribute to. They arranged from the open JDK. I think we even now have our own implementation of Java, the Corretto open source project. We contribute to projects like rust, where we are very active in the rest foundation from a leadership role as well, the robot operating system, just to pick some, we collaborate with Facebook and actively involved with the pirates project. And there's many others. You can see all the logos in here where we participate either because they're important to us as AWS in the services that we run or they're important to our customers and the services that they consume or the open source projects they care about and how we get to those. How we get and make those decisions is often depends on the importance of that particular project. At that point in time, how much impact they're having to AWS customers, or sometimes very feel that us contributing to that project is super critical because it helps us build more robust services. I'll talk about it in a completely, you know, somewhat different basis. You may have heard of us talk about our new next generation of Amazon Linux 2022, which is based on fedora as its sub stream. One of the reasons we made this decision was it allows us to go and participate in the preneurial project and make sure that the upstream project is robust, stays robust. And that, that what that ends up being is that Amazon Linux 2022 will be a robust operating system with the kinds of capabilities that our customers are asking for. That's just one example of how we think about it. So for example, you know, the Python software foundation is something that we work with very closely because so many of our customers use Python. So we help run something like PyPy which is many, you know, if you're a Python developer, I happened to be a Ruby one, but lots of our customers use Python and helping the Python project be robust by making sure PyPy is available to everybody is something that we help provide credits for help support in other ways. So it's not just code. It can mean many different ways of contributing as well, but in the end code and operations is where we hang our happens. Good examples of this is projects that we will create an open source because it makes sense to make sure that we open source some of the core primitives or foundations that are part of our own services. A great example of that, whether this be things that we open source or things that we contribute to. And I'll talk about both and I'll talk about things near and dear to my heart. There's many examples I've picked the two that I like talking about. The first of these is firecracker. Many of you have heard about it, a firecracker for those of you who don't know is a very lightweight virtual machine manager, which allows you to run these micro VMs. And why was this important many years ago when we started Lambda and quite honestly, Fugate and foggy, it still runs quite a bit in that mode, we used to have to run on VMs like everything else and finding the right VM for the size of tasks that somebody asks for the size of function that somebody asks for is requires us to provision capacity ahead of time. And it also wastes a lot of capacity because Lambda function is small. You won't even if you find the smallest VM possible, those can be a little that can be challenging. And you know, there's a lot of resources that are being wasted. VM start at a particular speed because they have to do a whole bunch of things before the operating system spins up and the virtual machine spins up and we asked ourselves, can we do better? come up with something that allows us to create right size, very lightweight, very fast booting. What's your machines, micro virtual machine that we ended up calling them. That's what led to firecracker. And we open source the project. And today firecrackers use, not just by AWS Lambda or foggy, but by a number of other folks, there's companies like fly IO that are using it. We know people using firecracker to run Kubernetes on prem on bare metal as an example. So we've seen a lot of other folks embrace it and use it as the foundation for building their own serverless services, their own container services. And we think there's a lot of value and learnings that we can bring to the table because we get the experience of operating at scale, but other people can bring to the table cause they may have specific requirements that we may not find it as important from an AWS perspective. So that's firecracker an example of a project where we contribute because we feel it's fundamentally important to us as continually. We were found, you know, we've been involved with continuity from the beginning. Today, we are a whole team that does nothing else, but contribute to container D because container D underlies foggy. It underlies our Kubernetes offerings. And it's increasingly being used by customers directly by their placement. You know, where they're running container D instead of running a full on Docker or similar container engine, what it has allowed us to do is focus on what's important so that we can operate continuously at scale, keep it robust and secure, add capabilities to it that AWS customers need manifested often through foggy Kubernetes, but in the end, it's a win-win for everybody. It makes continuously better. If you want to use containers for yourself on AWS, that's a great way to you. You know, you still, you still benefit from all the work that we're doing. The decision we took was since it's so important to us and our customers, we wanted a team that lived in breathed container D and made sure a super robust and there's many, many examples like that. No, that we ended up participating in, either by taking a project that exists or open sourcing our own. Here's an example of some of the open source projects that we have done from an AWS on Amazon perspective. And there's quite a few when I was looking at this list, I was quite surprised, not quite surprised I've seen the reports before, but every time I do, I have to recount and say, that's a lot more than one would have thought, even though I'd been looking at it for such a long time, examples of this in my world alone are things like, you know, what work had to do with Amazon Linux BottleRocket, which is a container host operating system. That's been open-sourced from day one. Firecracker is something we talked about. We have a project called AWS peril cluster, which allows you to spin up high performance computing clusters on AWS using the kind of schedulers you may use to use like slum. And that's an open source project. We have plenty of source projects in the web development space, in the security space. And more recently things like the open 3d engine, which is something that we are very excited about and that'd be open sourced a few months ago. And so there's a number of these projects that cover everything from tooling to developer, application frameworks, all the way to database and analytics and machine learning. And you'll notice that in a few areas, containers, as an example, machine learning as an example, our default is to go with open source option is where we can open source. And it makes sense for us to do so where we feel the product community might benefit from it. That's our default stance. The CNCF, the cloud native computing foundation is something that we've been involved with quite a bit. You know, we contribute to Kubernetes, be contribute to Envoy. I talked about continuity a bit. We've also contributed projects like CDK 8, which marries the AWS cloud development kit with Kubernetes. It's now a sandbox project in Kubernetes, and those are some of the areas. CNCF is such a wide surface area. We don't contribute to everything, but we definitely participate actively in CNCF with projects like HCB that are critical to eat for us. We are very, very active in just how the project evolves, but also try and see which of the projects that are important to our customers who are running Kubernetes maybe by themselves or some other project on AWS. Envoy is a good example. Kubernetes itself is a good example because in the end, we want to make sure that people running Kubernetes on AWS, even if they are not using our services are successful and we can help them, or we can work on the projects that are important to them. That's kind of how we think about the world. And it's worked pretty well for us. We've done a bunch of work on the Kubernetes side to make sure that we can integrate and solve a customer problem. We've, you know, from everything from models to work that we have done with gravity on our arm processor to a virtual GPU plugin that allows you to share and media GPU resources to the elastic fabric adapter, which are the network device for high performance computing that it can use at Kubernetes on AWS, along with things that directly impact Kubernetes customers like the CDKs project. I talked about work that we do with the container networking interface to the Amazon control of a Kubernetes, which is an open source project that allows you to use other AWS services directly from Kubernetes clusters. Again, you notice success, Kubernetes, not EKS, which is a managed Kubernetes service, because if we want you to be successful with Kubernetes and AWS, whether using our managed service or running your own, or some third party service. Similarly, we worked with premetheus. We now have a managed premetheus service. And at reinvent last year, we announced the general availability of this thing called carpenter, which is a provisioning and auto-scaling engine for Kubernetes, which is also an open source project. But here's the beauty of carpenter. You don't have to be using EKS to use it. Anyone running Kubernetes on AWS can leverage it. We focus on the AWS provider, but we've built it in such a way that if you wanted to take carpenter and implemented on prem or another cloud provider, that'd be completely okay. That's how it's designed and what we anticipated people may want to do. I talked a little bit about BottleRocket it's our Linux-based open-source operating system. And the thing that we have done with BottleRocket is make sure that we focus on security and the needs of customers who want to run orchestrated container, very focused on that problem. So for example, BottleRocket only has essential software needed to run containers, se Linux. I just notice it says that's the lineups, but I'm sure that, you know, Lena Torvalds will be pretty happy. And seeing that SE linux is enabled by default, we use things like DM Verity, and it has a read only root file system, no shell, you can assess it. You can install it if you wanted to. We allowed it to create different bill types, variants as we call them, you can create a variant for a non AWS resource as well. If you have your own homegrown container orchestrator, you can create a variant for that. It's designed to be used in many different contexts and all of that is open sourced. And then we use the update framework to publish and secure repository and kind of how this transactional system way of updating the software. And it's something that we didn't invent, but we have embraced wholeheartedly. It's a bottle rockets, completely open source, you know, have partners like Aqua, where who develop security tools for containers. And for them, you know, something I bought in rocket is a natural partnership because people are running a container host operating system. You can use Aqua tooling to make sure that they have a secure Indiana environment. And we see many more examples like that. You may think so over us, it's all about AWS proprietary technology because Lambda is a proprietary service. But you know, if you look peek under the covers, that's not necessarily true. Lambda runs on top of firecracker, as we've talked about fact crackers and open-source projects. So the foundation of Lambda in many ways is open source. What it also allows people to do is because Lambda runs at such extreme scale. One of the things that firecracker is really good for is running at scale. So if you want to build your own firecracker base at scale service, you can have most of the confidence that as long as your workload fits the design parameters, a firecracker, the battle hardening the robustness is being proved out day-to-day by services at scale like Lambda and foggy. For those of you who don't know service support services, you know, in the end, our goal with serverless is to make sure that you don't think about all the infrastructure that your applications run on. We focus on business logic as much as you can. That's how we think about it. And serverless has become its own quote-unquote "Sort of environment." The number of partners and open-source frameworks and tools that are spun up around serverless. In which case mostly, I mean, Lambda, API gateway. So it says like that is pretty high. So, you know, number of open source projects like Zappa server serverless framework, there's so many that have come up that make it easier for our customers to consume AWS services like Lambda and API gateway. We've also done some of our own tooling and frameworks, a serverless application model, AWS jealous. If you're a Python developer, we have these open service runtimes for Lambda, rust dot other options. We have amount of number of tools that we opened source. So in general, you'll find that tooling that we do runtime will tend to be always be open-sourced. We will often take some of the guts of the things that we use to build our systems like firecracker and open-source them while the control plane, etc, AWS services may end up staying proprietary, which is the case in Lambda. Increasingly our customers build their applications and leverage the broader AWS partner network. The AWS partner network is a network of partnerships that we've built of trusted partners. when you go to the APN website and find a partner, they know that that partner meets a certain set of criteria that AWS has developed, and you can rely on those partners for your own business. So whether you're a little tiny business that wants some function fulfill that you don't have the resources for or large enterprise that wants all these applications that you've been using on prem for a long time, and want to keep leveraging them in the cloud, you can go to APN and find that partner and then bring their solution on as part of your cloud infrastructure and could even be a systems integrator, for example, to help you solve this specific development problem that you may have a need for. Increasingly, you know, one of the things we like to do is work with an apartment community that is full of open-source providers. So a great one, there's so many, and you have, we have a panel discussion with many other partners as well, who make it easier for you to build applications on AWS, all open source and built on open source. But I like to call it a couple of them. The first one of them is TIDELIFT. TIDELIFT, For those of you who don't know is a company that provides SAS based tools to curate track, manage open source catalogs. You know, they have a whole network of maintainers and providers. They help, if you're an independent open developer, or a smart team should probably get to know TIDELIFT. They provide you benefits and, you know, capabilities as a developer and maintainer that are pretty unique and really help. And I've seen a number of our open source community embraced TIDELIFT quite honestly, even before they were part of the APN. But as part of the partner network, they get to participate in things like ISP accelerate and they get to they're officially an advanced tier partner because they are, they migrated the SAS offering onto AWS. But in the end, if you're part of the open source supply chain, you're a maintainer, you are a developer. I would recommend working with TIDELIFT because their goal is making all of you who are developing open source solutions, especially on AWS, more successful. And that's why I enjoy this partnership with them. And I'm looking to do a lot more because I think as a company, we want to make sure that open source developers don't feel like they are not supported because all you have to do is read various forums. It's challenging often to be a maintainer, especially of a small project. So I think with helping with licensing license management, security identification remediation, helping these maintainers is a big part of what TIDELIFT to us and it was great to see them as part of a partner network. Another partner that I like to call sysdig. I actually got introduced to them many years ago when they first launched. And one of the things that happened where they were super interested in some of our serverless stuff. And we've been trying to figure out how we can work together because all of our customers are interested in the capabilities that cystic provides. And over the last few years, he found a number of areas where we can collaborate. So sysdig, I know them primarily in a security company. So people use cystic to secure the bills, detect, you know, do threat response, threat detection, completely continuously validate their posture, get this continuous analytics signal on how they're doing and monitor performance. At the end of it, it's a SAS platform. They have a very nice open source security stack. The one I'm most familiar with. And I think most of you are probably familiar with is Falco. You know, sysdig, a CNCF project has been super popular. It's just to go SSS what 3, 37, 40 million downloads by now. So that's pretty, pretty cool. And they have been a great partner because we've had to do make sure that their solution works at target, which is not a natural place for their software to run, but there was enough demand and interest from our customers that, you know, or both companies leaned in to make sure they can be successful. So last year sister got a security competency. We have a number of specific competencies that we for our partners, they have integration and security hub is great. partners are lean in the way cystic has onto making our customer successful. And working with us are the best partners that we have. And there's a number of open source companies out there built on open source where their entire portfolio is built on open source software or the active participants like we are that we love working with on a day to day basis. So, you know, I think the thing I would like to, as we wind this out in this presentation is, you know, AWS is constantly looking for partnerships because our partners enable our customers. They could be with companies like Redis with Mongo, confluent with Databricks customers. Your default reaction might be, "Hey, these are companies that maybe compete with AWS." but no, I mean, I think we are partners as well, like from somebody at the lower end of the spectrum where people run on top of the services that I own on Linux and containers are SE 2, For us, these partners are just as important customers as any AWS service or any third party, 20 external customer. And so it's not a zero sum game. We look forward to working with all these companies and open source projects from an AWS perspective, a big part of how, where my open source program spends its time is making it easy for our developers to contribute, to open source, making it easy for AWS teams to decide when to open source software or participate in open source projects. Over the last few years, we've made significant changes in how we reduce the friction. And I think you can see it in the results that I showed you earlier in this stock. And the last one is one of the most important things that I say and I'll keep saying that, that we do as AWS is carry the pager. There's a lot of open source projects out there, operationalizing them, running them at scale is not easy. It's not all for whatever reason. It may not have anything to do with the software itself. But our core competency is taking that and being really good at operating it and becoming experts at operating it. And then ideally taking that expertise and experience and operating that project, that software and contributing back upstream. Cause that makes it better for everybody. And I think you'll see us do a lot more of that going forward. We've been doing that for the last few years, you know, in the container space, we do it every day. And I'm excited about the possibilities. With that. Thank you very much. And I hope you enjoy the rest of the showcase. >> Okay. Welcome back. We have Deepak sing here. We just had the keynote closing keynote vice-president of compute services. Deepak. Great to a great keynote, great wisdom and insight from that session. A very notable highlights and cutting edge trends and product information. Thanks for sharing. >> No, anytime it's always good to be here. It's too bad that we still doing this virtually, but always good to talk to you, John. >> We'll get hopefully through this way pretty quickly, I want to jump right in. Cause we don't have a lot of time. I want to get some quick question. You've brought up a good things. Open source innovation. Okay. Going next level. You've seen the rise of super clouds and super apps developing at open source. You're seeing big companies contributing, you know, you mentioned Argo into it. You're seeing that dynamic where companies are forming around this. This is a rising tide. This is, this is actually real. It's not the old school of, okay, here's a project. And then someone manages support and commercialization of it. It's actually platform in cloud scale. This is next gen. >> Yeah. And actually I think it started a few years ago. We can talk about a company that, you know, you're very familiar with as part of this event, which is armory many years ago, Netflix spun off this project called Spinnaker. A Spinnaker is CISED you know, CSED system that was developed at Netflix for their own purposes, but they chose to open solicit. And since then, it's become very popular with customers who want to use it even on prem. And you have a company that spun up on it. I think what's making this world very unique is you have very large companies like Facebook that will build things for themselves like VITAS or Netflix with Spinnaker and open source them. And you can have a lot of discussion about why they chose to do so, etc. But increasingly that's becoming the default when Amazon or Netflix or Facebook or Mehta, I guess you call them these days, build something for themselves for their own needs. The first question we ask ourselves is, should it be opensource? And increasingly we are all saying yes. And here's what happens because of that. It gives an opportunity depending on how you open source it for innovation through commercial deployments, so that you get SaaS companies, you know, that are going to take that product and make it relevant and useful to a very broad number of customers. You build partnerships with cloud providers like AWS, because our customers love this open source project and they need help. And they may choose an AWS managed service, or they may end up working with this partner on a day-to-day basis. And we want to work with that partner because they're making our customers successful, which is one reason all of us are here. So you're having this set of innovation from large companies from, you know, whether they are just consumer companies like Metta infrastructure companies like us, or just random innovation that's happening in an open source project that which ends up in companies being spun up and that foster that innovative innovation and that flywheel that's happening right now. And I think you said that like, this is unique. I mean, you never saw this happen before from so many different directions. >> It really is a nice progression on the business model side as well. You mentioned Argo, which is a great organic thing that was Intuit developed. We just interviewed code fresh. They just presented here in the showcase as well. You seeing the formation around these projects develop now in the community at a different scale. I mean, look at code fresh. I mean, Intuit did it Argo and they're not just supporting it. They're building a platform. So you seeing the dynamics of tools and now emerging the platforms, you mentioned Lambda, okay. Which is proprietary for AWS and your talk powered by open source. So again, open source combined with cloud scale allows for new potential super applications or super clouds that are developing. This is a new phenomenon. This isn't just lift and shift and host on the cloud. This is actually a construction production developer workflow. >> Yeah. And you are seeing consumers, large companies, enterprises, startups, you know, it used to be that startups would be comfortable adopting some of these solutions, but now you see companies of all sizes doing so. And I said, it's not just software it's software, the services increasingly becoming the way these are given, delivered to customers. I actually think the innovation is just getting going, which is why we have this. We have so many partners here who are all in inventing and innovating on top of open source, whether it's developed by them or a broader community. >> Yeah. I liked, I liked the represent container. Do you guys have, did that drove that you've seen a lot of changes and again, with cloud scale and open source, you seeing the dynamics change, whether you're enabling that, and then you see kind of like real big change. So let's take snowflake, a big customer of AWS. They started out as a startup too, but they weren't a data warehouse. They were bringing data warehouse like functionality and then changing everything differently and making it consumable for the cloud. And hence they're huge. So that's a disruption into an incumbent leader or sector. Then you've got new capabilities emerging. What's your thoughts, Deepak? Can you share your vision on how you have the disruption to existing leaders, old guard, if you will, as you guys call them and then new capabilities as these new platforms emerge at a net new functionality, how do you see that emerging? >> Yeah. So I speak from my side of the world. I've lived in over the last few years, which has containers and serverless, right? There's a lot of, if you go to any enterprise and ask them, do you want to modernize the infrastructure? Do you want to take advantage of automated software delivery, continuous delivery infrastructure as code modern observability, all of them will say yes, but they also are still a large enterprise, which has these enterprise level requirements. I'm using the word enterprise a lot. And I usually it's a trigger word for me because so many customers have similar requirements, but I'm using it here as large company with a lot of existing software and existing practices. I think the innovation that's coming and I see a lot of companies doing that is saying, "Hey, we understand the problems you want to solve. We understand the world where you live in, which could be regulated." You want to use all these new modalities. How do we allow you to use all of them? Keep the advantages of switching to a Lambda or switching to, and a service running on far gate, but give you the same capabilities. And I think I'll bring up cystic here because we work so closely with them on Falco. As an example, I just talked about them in my keynote. They could have just said, "Oh no, we'll just support the SE2 and be done with it." They said, "No, we're going to make sure that serverless containers in particular are something that you're going to be really good at because our customers want to use them, but requires us to think differently. And then they ended up developing new things like Falco that are born in this new world, but understand the requirements of the old world. If you get what I'm saying. And I think that a real example. >> Yeah. Oh, well, I mean, first of all, they're smart. So that was pretty obvious for most people that know, sees that you can connect the dots on serverless, which is a great point, but not everyone can see that again, this is what's new and and systig was just found in his backyard. As I found out on my interview, a great, great founder, they would do a new thing. So it was a very easy to connect the dots there again, that's the trend. Well, I got to ask if they're doing that for serverless, you mentioned graviton in your speech and what came out of you mentioned graviton in your speech and what came out of re-invent this past year was all the innovation going on at the compute level with gravitron at many levels in the Silicon. How should companies and open source developers think about how to innovate with graviton? >> Yeah, I mean, you've seen examples from people blogging and tweeting about how fast their applications run and grab it on the price performance benefits that they get, whether it's on, you know, whether it's an observability or other places. something that AWS is going to embrace across a compute something that AWS is going to embrace across a compute portfolio. Obviously you can go find EC2 instances, the gravitron two instances and run on them and that'll be great. But we know that most of our customers, many of our customers are building new applications on serverless containers and serveless than even as containers increasingly with things like foggy, where they don't want to operate the underlying infrastructure. A big part of what we're doing is to make sure that graviton is available to you on every compute modality. You can run it on a C2 forever. You've been running, being able to use ECS and EKS and run and grab it on almost since launch. What do you want me to take it a step further? You elastic Beanstalk customers, elastic Beanstalk has been around for a decade, but you can now use it with graviton. people running ECS on for gate can now use graviton. Lambda customers can pick graviton as well. So we're taking this price performance benefits that you get So we're taking this price performance benefits that you get from graviton and basically putting it across the entire compute portfolio. What it means is every high level service that gets built on compute infrastructure. And you get the price performance benefits, you get the price performance benefits of the lower power consumption of arm processes. So I'm personally excited like crazy. And you know, this has graviton 2 graviton 3 is coming. >> That's incredible. It's an opportunity like serverless was it's pretty obvious. And I think hopefully everyone will jump on that final question as the time's ticking here. I want to get your thoughts quickly. If you look at what's happened with containers over the past say eight years since the original founding of the first Docker instance, if you will, to how that's evolved and then the introduction of Kubernetes and the cloud native wave we're seeing now, what is, how would you describe the relationship between the success Docker, seeing now with Kubernetes in the cloud native construct what's different and why is this combination so successful? >> Yeah. I often say that containers would have, let me rephrase that. what I say is that people would have adopted sort of the modern way of running applications, whether containers came around or not. But the fact that containers came around made that migration and that journey is so much more efficient for people. So right from, I still remember the first doc that Solomon gave Billy announced DACA and starting to use it on customers, starting to get interested all the way to the more sort of advanced orchestration that we have now for containers across the board. And there's so many examples of the way you can do that. Kubernetes being the most, most well-known one. Here's the thing that I think has changed. I think what Kubernetes or Docker, or the whole sort of modern way of building applications has done is it's taken people who would have taken years adopting these practices and by bringing it right to the fingertips and rebuilding it into the APIs. And in the case of Kubernetes building an entire sort of software world around it, the number of, I would say number of decisions people have to take has gone smaller in many ways. There's so many options, the number of decisions that become higher, but the com the speed at which they can get to a result and a production version of an application that works for them is way low. I have not seen anything like what I've seen in the last 6, 7, 8 years of how quickly the most you know, the most I would say is, you know, a company that you would think would never adopt modern technology has been able to go from, this is interesting to getting a production really quickly. And I think it's because the tooling makes it So, and the fact that you see the adoption that you see right and the fact that you see the adoption that you see right from the fact that you could do Docker run Docker, build Docker, you know, so easily back in the day, all the way to all the advanced orchestration you can do with container orchestrator is today. sort of taking all of that away as well. there's never been a better time to be a developer independent of whatever you're trying to build. And I think containers are a big central part of why that's happened. >> Like the recipe, the combination of cloud-scale, the timing of Kubernetes and the containerization concepts just explode as a beautiful thing. And it creates more opportunities and will challenges, which are opportunities that are net new, but it solves the automation piece that we're seeing this again, it's only makes things go faster. >> Yes. >> And that's the key trend. Deepak, thank you so much for coming on. We're seeing tons of open cloud innovations, thanks to the success of your team at AWS and being great participants in the community. We're seeing innovations from startups. You guys are helping enabling that. Of course, they want to live on their own and be successful and build their super clouds and super app. So thank you for spending the time with us. Appreciate. >> Yeah. Anytime. And thank you. And you know, this is a great event. So I look forward to people running software and building applications, using AWS services and all these wonderful partners that we have. >> Awesome, great stuff. Great startups, great next generation leaders emerging. When you see startups, when they get successful, they become the modern software applications platforms out there powering business and changing the world. This is the cube you're watching the AWS startup showcase. Season two episode one open cloud innovations on John Furrier your host, see you next time.

(upbeat music) >> Welcome back to the Quantcast Industry Summit on the demise of third-party cookies, The Cookie Conundrum, A Recipe for Success. We're here with Peter Day, the CTO, Quantcast and Shruti Koparkar, Head of Product Marketing Quancast. Thanks for coming on. Talk about the changing advertising landscape. >> Thanks for having us. >> Thank you for having us. >> So we've been hearing the story out to the big players, want to keep the data, make that centralized, control all the leverage, and then you've got the other end. You've got the open internet that still wants to be free and valuable for everyone. What's what are you guys doing to solve this problem? Because if cookies go away, what's going to happen there? How do people track things? You guys are in this business? First question, what is Quancast strategy to adapt to third-party cookies going away? What's going to be the answer? >> Yeah, so very rightly said, John. The mission, the Quancast mission is to champion of free and open internet. And with that in mind, our approach to this a world without third party cookies is really grounded in three fundamental things. First is industry standards. We think it's really important to participate and to work with organizations who are defining the standards that will guide the future of advertising. So with that in mind we've been participating with IAB Tech Lab, We've been part of their project, we are same thing with Prebid, who's kind of trying to figure out the pipes of identity the ID pipes of the future. And then also is W3C which is the World Wide Web Consortium. And our engineers and our engineering team are participating in their weekly meetings, trying to figure out what's happening with the browsers and keeping up with the progress there on things such as Google's FLoC. The second sort of thing is interoperability. As you've mentioned that a lots of different ID solutions that are emerging. You have UID 2.0, you have LiveRamp, you have Google's FLoC, and there will be more, there are more, and they will continue to be more. We really think it is important to build a platform that can ingest all of these signals. And so that's what we've done. The reason really is to meet our customers where they are at. Today our customers use multiple Data Management Platforms, DMPs. And that's why we support multiple of those. This is not going to be much different than that. We have to meet our customers where we are, or where they are at. And then finally, of course, which is at the very heart of who Quancast is, is innovation. As you can imagine being able to take all of these multiple signals in, including the IDs and the cohorts, but also others like contextual first party consent is becoming more and more important. And then there are many other signals like time, language, geolocation. So all of these signals can help us understand user behavior, intent and interests. In absence of third party cookies. However there's something to note about these. They're very raw, they're complex, they're messy, all of these different signals. They are changing all the time, their real time. And those incomplete in information isolation, just one of these signals can not help you build up true and complete picture. So what you really need is a technology like AI and Machine Learning, to really bring all of these signals together, combine them statistically, and get an understanding of user behavior intent and interest, and then act on it. Be it in terms of providing audience insights, or responding to bid requests and so on and so forth. So those are sort of the three fundamentals that our approach is grounded in which is industry standards, interoperability, and innovation. And you know, you have Peter here >> Yeah. who is the expert so you can dive much deeper into it. >> So Peter is CTO. You've got to tell us, how is this going to actually work? What are you guys doing from a technology standpoint to help with data-driven advertising and a third-party cookieless world? >> Well, we've been this is not a shock. You know, I think anyone who's been close to this space has known that the third party cookie has been reducing in quality in terms of its pervasiveness and its longevity for many years now. And the kind of death knell is really Google Chrome, making the changes that, they're going to be making. So we've been embarrassing in this space for many years and we've had to make a number of hugely diverse investments. So one of them is in how to, as a marketer how do I tell it my marketing still working in a world without (indistinct). The majority of marketers, completely relying on third party cookies today. It's tell them if their marketing is working or not. And so we've had to invest heavily and statistical techniques, which are closer to kind of echo metric models that marketers are used to have things like out of home advertising. It's going to be establishing whether their advertising is working or not in a digital environment. And actually this as with often the case in these kind of times of massive disruption, there's always opportunity to make things better. And we really think that's true. And you know, digital measurement is often mistaken precision for accuracy and there's a real opportunity to kind of see the wood for the trees if you'd like. And start to come up with better methods of measuring the effectiveness of advertising without third party cookies. And we've had to make countless other investments in areas like contextual modeling, and targeting that third-party cookies and connecting directly to publishers rather than going through this kind of loom escape that's going to tied together third party cookies. So I could, if I was to enumerate all the investments we've made I think it would be here till midnight, but we've had to make a number of investments over a number years. And that level investments only increasing at the moment. >> Peter, on that contextual, can you just double click on that and tell us more? >> Yeah, I mean, contextual it is, unfortunately when I think this is really poorly defined. It can mean everything from a publisher saying, Hey trust us this page is about SUV's, it's a what's possible now. And it's only really been possible the last couple of years which is to build statistical models of the entire internet based on the content that people are actually consuming. And this type of technology requires massive data processing capabilities, it's able to take advantage of the latest innovations in areas like natural language processing. And really gives computers, that kind of much deeper and richer understanding of the internet, which ultimately makes it possible to kind of organize the internet, in terms of the types of content of pages. So this type of technology has only been possible for the last few years. And, but we've been using contextual signals since our inception. Had always been massively predictive in terms of audience behaviors, in terms of where advertising is likely to work. And so we've been very fortunate to keep that investment going and take advantage of many of these innovations that are happening in academia and in kind of an adjacent areas >> On the AI and Machine Learning aspect. That seems to be a great differentiator in this day and age for getting the most out of the data. How is machine learning and AI factoring into your platform? >> I think it's how we've always operated, right from our inception. When we started as a measurement company. The way that we were giving our customers at the time we were just publishers, just the publisher side of our business. Insights into who their audience was, which was using Machine Learning techniques. And that's never really changed. The foundation of our platform has always been Machine Learning from before it was cool. A lot of our, kind of a lot of our co-teams have backgrounds in Machine Learning, and the PhDs in statistics and Machine Learning. And that really drives our decision-making. I mean, data is only useful if you can make sense of it and if you can organize it, and if you can take action on it, and to do that at this kind of scale it's absolutely necessary to use Machine Learning technology. >> So you mentioned contextual also, you know, in advertising we have everyone knows and that world that you got the contextual and behavioral dynamics. The behavior that's kind of generally can everyone's believing is happening. The consensus is undeniable is that, people are wanting to expect an environment where there's trust, there's truth, but also they want to be locked in. They don't want to get walled into a walled garden. Nobody wants to be in a wall garden. They want to be free to pop around and visit sites. It's more horizontal scalability than ever before yet. The bigger players are becoming walled garden vertical platforms. So with future of AI, the experience is going to come from this data. So the behaviors out there. How do you get >> Yeah. that contextual relevance and provide the horizontal scale that users expect? >> Yeah, I think it's a really good point and we're definitely at this kind of tipping point, we think in the broader industry. I think, you know, every publisher, right? We're really blessed to work with the biggest publishers in the world. All the way through to my mom's blog, right? So we get to hear the perspectives of the publishers at every scale. And they consistently tell us the same thing. Which is they want some more directly connect to consumers. They don't want to be tied into these walled gardens, which dictate how they must present their content. And in some cases what content they're allowed to present. And so, you know, our job as a company is to really provide level the playing field a little bit. Provide them the same capabilities they're only used to in the walled gardens, but let, give them more choice. In terms of how they structure their content, how they organize their content, how they organize their audiences, but make sure that they can fund that effectively. By making their audiences and their environments discoverable by marketers, measurable by marketers, and connect them as directly as possible to make that kind of ad funded economic model, as effective in the open internet as it is in social. And so a lot of the investments we've made over recent years have been really to kind of realize that vision, which is, it should be as easy for a marketer to be able to understand people on the open internet, as it is in social media. It should be as effective for them to reach people in that environment, is really high quality content as it is on Facebook. And so we've invested a lot of our R&D dollars in making that true. And we're now live with the Quantcast Platform which does exactly that. And as third party cookies go away, it only kind of exaggerate all kind of further emphasizes the need for direct connections between brands and publishers. And so we just want to build a technology that helps make that true, and gives the kind of technology to these marketers and publishers to connect, and to deliver great experiences without relying on these kind of walled gardens. >> Yeah. The direct to consumer, direct to audience is a new trend. You're seeing it everywhere. How do you guys support this new kind of signaling from for that's happening in these new world? How do you ingest the content, ingest this consent signaling? >> We were really fortunate to have an amazing an amazing R&D team. And, you know, we've had to do all sorts to make this, you know, to realize our vision. This has meant things like we, you know we have crawlers which stand the entire internet at this point, extract the content of the pages, and kind of make sense of it, and organize it. And organize it for publishers so that they can understand how their audiences overlap with potentially their competitors or collaborators, but more importantly, organize it for marketers. So they can understand what kind of high-impact opportunities are there for them there. So, you know, we've had to build a lot of technology. We've had to build analytics engines which can get answers back in seconds, so that, you know marketers and publishers can kind of interact with it with their own data and make sense of it and present it in a way that is compelling and then help them drive their strategy as well as their execution. We've had to invest in areas like consent management. Because we believe that a free and open internet is absolutely reliant on trust. And therefore we spend a lot of our time thinking about how do we make it easy for end-users to understand who has access to that data and easy friendly and users to be able to opt out. And as a result of that, we've now got the world's most widely adopted consent management platform. So it's hard to tackle one of these problems without tackling all of them. And we're fortunate enough to have had a large enough R&D budget over the last four or five years, make a number of investments, everything from consent and identity, through to contextual signals, through to measurement technologies, which really bring advertisers and publishers closer together. >> Great insight there. Shruti last word for you. What's the customer view here as you bring these new capabilities of the platform. What's what are you guys seeing as the highlight from a platform perspective? >> So the initial response that we've seen from our customers has been very encouraging. Both on the publisher side, as well as the marketer side. I think, you know, one of the things we hear quite a lot is you guys are at least putting forth a solution and action solution for us to test. Peter mentioned measurement. That really is where we started because you cannot optimize what you cannot measure. So that is where his team has started. And we have some measurement, very very initial capabilities still in alpha, but they are available in the platform for marketers to test out today. So the initial response has been very encouraging. People want to engage with us. Of course, our, you know, our fundamental value proposition which is that the Quantcast platform was never built to be reliant on third party data, these stale segments. Like we operate we've always operated on real time live data. The second thing is our premium publisher relationships. We have had the privilege of working like Peter served with some of the biggest publishers but we also have a very wide footprint. We have first party tags across over a hundred million plus web and mobile destinations. And, you know, as you must've heard like that sort of first party footprint, is going to come in really handy in a world without third party cookies. We are encouraging all of our customers, publishers and marketers to grow their first party data. And so that's something that's a strong point that customers love about us and lean into it quite a bit. So, yeah, the initial response has been great. Of course it doesn't hurt that we've made all these R&D investments. We can talk about consent, and, you know, I often say that consent it sounds simple, but it isn't, there's a lot of technology involved. But there's lots of legal work involved as it as well. We have a very strong legal team who has expertise built in. So yeah, a very good response initially. >> Democratization, everyone's a publisher, everyone's a media company. They have to think about being a platform. You guys provide that. So congratulations Peter, thanks for dropping the gems there. Shruti thanks for sharing the product highlights. Thanks for your time. >> Thank you. >> Okay, this is the Quancast Industry Summit on the demise of third-party cookies and what's next The Cookie Conundrum, the Recipe for success with Quancast I'm John Berger with theCUBE. Thanks for watching. (upbeat music)

(upbeat music) >> Hello, welcome back to the Cookie Conundrum, A Recipe For Success an industry conference and summit from Quancast on the demise of third-party cookies. We've got a great industry panel here to break it down. Chris Guenther, senior vice president global head of Programmatic at News Corp. Chris, thanks for coming on. Xiao Lin, managing director solutions at Xaxis, and Somer Simpson, vice president of product at Quancast stellar panel. Looking forward to this conversation. Thanks for coming on and chatting about the cookie conundrum. >> Thank you for having us. >> So, Chris, we'll start with you at News Corp obviously major publisher. Deprecation of third-party cookies affects everyone. You guys have a ton of traffic, ton of audience across multiple formats. Tell us about the impact to you guys and the reliance you guys had on them. And what are you going to do to prepare for this next level change? >> Sure. I mean, I think like everyone in this industry there is a, you know, a significant reliance and I think it's something that a lot talk about audience targeting, but obviously they realize that third party cookies pervasive across the whole ad tech ecosystem, MarTech stack. And so, you know, we have to think about, you know how that impact, you know, our vendor the vendors we work with, what it means in terms of our use cases across marketing, across advertising across site experience. So, you know, without a doubt, it's significant. But you know, we look at it as listen. It's disruptive in disruption and change is always a little scary, but overall it's a it's a long overdue reset. I mean, I think that, you know, our perspective is that the the cookies, as we all know, is it was a crutch, right? It's sort of a technology being used in way it shouldn't. And so, as we look at what's going to happen presumably after Jan 2022, then it's a good way to kind of fix on some bad practices practices that lead to data, leakage, practice sort of devalued for our perspective. Some of the, you know, we offered as, as publishers. And I think that this is a key thing is that we're not just looking to as we look through post gen world, not just kind of recreating the prior world. Because the prior world was flawed or I guess I could say the current world since it hasn't changed yet. But the current world is flawed. Let's not just replicate that. You know, let's make sure that third party cookies goes away other work around like fingerprinting and things like that, you know, also go away. So, you know, philosophically that's where our head's at. And so, you know, as we look at how we are preparing you look at sort of what are the core building blocks of preparing for this world. Obviously one of the key ones is privacy compliance. Like how do we treat our users with consent? You know, obviously are we aligned with the regulatory environments? You know, in some ways we're not looking just to Jan 2022 but Jan 2023, where there's going to be the majority of our audiences, we covered by regulation. And so I think from regulation up to data gathering, to data activation, all built around an internal identifier that we've developed that allows us to have a a consistent look at our user is whether they're logged in or obviously, anonymous. So it's really looking across all those components, across all our sites, and all in a privacy compliant way. So a lot of work to be done, a lot of work in progress but you know, we're excited about what's going on. >> I like how you framed it, you know, old world or next gen kind of the current situation is kind of flawed. And as you think about Programmatic, the concept is mind blowing and what needs to be done. So we'll come back to that because I think that original content view is certainly relevant. It's a huge investment, and you've got great content and audience consuming it. Xiao, from a major media standpoint get your perspective on the impact because you've got clients who want to get their message out in front of the audience at the right time, at the right place and the right context. Right? So yeah, privacy, you got consent and all of these things kind of boiling up how do you help clients prepare? Because now they can go direct to the consumer. You know, everyone, everyone has a megaphone now everyone's you know, everyone's here, everyone's connected. So how are you impacted by this new notion? >> You know, if the cookieless future was a tik tok dance, we'd be dancing right now and at least until the next year. This has been top of mind for us and our clients for quite some time. But I think as each day passes the picture becomes clearer and more in focus. The end of the third party cookie does not mean the end of Programmatic. So clients work with us in transforming their investments into real business outcomes based on our expertise and based on our tech. So we continue to be in a great position to lead, to educate, to partner, and to grow with them along this cookieless future. The impact will be all encompassing in changing the ways we do things now and also accelerating the things that we've already been building on. So we take it from the top. Planning will have a huge impact because it's going to start becoming more strategic around real business outcomes. We're omni-channel. So clients wants to drive outcomes through multiple touch points of a consumer's journey. Whether that's programmatic, whether that's as a cookie free environment like connected TV, out of home, audio, gaming, and so forth. So we're going to see more of these strategic holistic plans. Creative will have a lot of impact. It will start becoming more important with Creative testing, Creative insights, you know, Creative in itself is cookieless. So there will be more focus on how to drive a brand dialogue, to connect to consumers with less targeting, with less cookies. With the cohesiveness of holistic planning, Creative can align through multiple channels. And lastly, the role of AI will become increasingly important. You know, we've always looked to build our tech, our products, to compliment new and existing technology as well as the client's own data and tech stack to deliver these outcomes for them. And AI in its core is just taking inputted data and having an output of your desired outcomes. So input data could be DSP data beyond cookies such as browser, such as location, such as contextual, a publisher taking client's first party data, first party CRM data like store visitation sales site activity. And using that to optimize in real time regardless of what vendor or what channel we're on. So as we're learning more about this cookieless dance, we're helping our clients on the steps of it, and also introducing our own moves. >> That's awesome. Data is going to be a key value proposition, you know connecting in with content real time. Great stuff. Somer, with your background in journalism and you're the tech VP of product at Quancast. You have the keys to the kingdom over there. It's interesting, journalism is about truth you know, good content, original content. But now you have a data challenge, problem, opportunity on both sides, brands and publishers coming together. This is a data problem in a way. It's a tech stack, not so much just, you know getting the right ads to show up at the right place, the right time. It's really bigger than that now. What's your take on this? >> You know, I, so first I think that consumers already sort of accept that there is a reasonable value exchange, you know, for their data, in order to access free content. Right? And that's a critical piece for us to all kind of understand. Over the past. Yeah, probably two years, since even before the GDPR, we've been doing a ton of discovery with customers, both publishers and marketers. And so, you know, we kind of known this this cookie going away thing is, has been coming and you know, Google's announcement just kind of confirmed it. And it's been really really interesting since Google's announcement how the conversations have changed with our customers and other folks that we talk to. And I've almost gone from being like a product manager to a therapist because there's such an emotional response. From the marketer perspective, there's real fear there. There's like, Oh my God, how you know, it's not just about delivering ads. It's about how do I control frequency? How do I measure, you know, success? You know, because the technology has grown so much over the years to really give marketers the ability to deliver personalized, you know, advertising good content to consumers and be able to monitor it and control it so that it's not too, too intrusive. On the publisher perspective side, we see a slightly different response. It's more of a yes. Right? You know, we're taking back control and we're going to stop the data leakage. We're going to get the value back for our inventory. Both things are a good thing. But if it's not managed, it's going to be like ships passing in the night. Right? In terms of, you know, them coming together. Right? And that's the critical pieces that they have to come together. They have to get closer. You got to cut out a lot of like that LUMAscape in the middle so that they can talk to each other and understand what's the value exchange happening between marketers and publishers and how do we do that without cookies? >> Yeah. It's a fascinating, I love your insight there. I think it's so relevant. And it's got broader implications because, you know, if you look at how data is impacting some of these big structural changes and refactoring of industries look at cybersecurity, you know no one wants to share their data but now if they share, they get more insight more machine learning, benefit, more AI benefit. So now we have the sharing notion but that goes against counter the big guys that want a walled garden. They want to hoard all the data and control that to provide their own personalization. So you have this confluence of, hey I want to hoard the data and then now I want to share the data. So Chris and Homer, in the wheelhouse you've got original content and there's other providers out there. So is there the sharing model coming? with privacy and these kinds of services is the open come back again? How do you guys see this? The confluence of open versus walled gardens. Because you need the data to make machine learning good. >> I'll start off. I mean, listen, I think you have to give credit to the walled gardens I've created. And I think as we look as publishers, what are we offering to our clients? What are we offering to the buy-side? We need to be compelling. We shouldn't just be, obviously, as journalists I think that there is a case of, you know the importance of funding journalism. But ultimately we need to make sure we're meeting the the KPIs and the business needs of the buy-side. And I think around that, it is, you know there's sort of three core pillars to that. It's ease of access, it's scope of activation and targeting, and finally, measurable results. So as I think, as us, as an individual publisher of so we have multiple publications so we do have scale, but then in partnership with other publishers perhaps organizations like Prebid, you know I think we can, we're trying to address that. And I think we can offer something that's compelling and transparent in terms of what these results are. But obviously, you know, I want to make sure it's clear that transparent terms of results, but obviously where there's privacy in terms of the data. And I I think we've all heard about like data clean rooms, a lot of them out there flogging those wares. And I think there's something valuable, but you know I think it's who is sort of the right partner or partners, and ultimately who allows us to get as close as possible to the buy side. And so that we can share that data for targeting shared for perhaps for measurement, but obviously all in a privacy compliant way. >> Somer, what's your take on this? Because you talk about the future of the open internet democratization. The network effect that we're seeing in virality and across multiple omni-channels as Xiao pointed out, it's happening. That's the distribution now. So that's almost an open garden model. So it's like >> Yeah. And yeah, it's, it's, you know back in the day, you know, Nightrider who was the first group that I, that I worked for, you know each of those individual properties were not hugely valuable on their own from a digital perspective. but together as a unit, they became valuable. Right. And got a scale for advertisers. Now we're in a place where, you know, I kind of think that each of those big networks are going to have to come together and work together to compare in size to the, to the walled gardens. And yeah, this is something that we've talked about before, an open garden. I think that's the definitely the right route to take. And I agree with Chris. It's about publishers getting as close to the marketers as possible, working with the tech companies that enable them to do that, and doing so in a very privacy centric way. >> Xiao how do we bring the brands and agencies together to get ready for third-party cookies? Because there is a therapist moment here of it's going to be okay, the parachute will open. The future is not going to be as grim. It's a real opportunity, but if managed properly. What's your take on this? Is it just more first party data strategy? And what's your assessment of this? >> So we're collaborating right now with ball grants on how to distill very complex cookieless future you know, what's going to happen in the future. To six steps that we can take right now and marketers should take. The first step is gather Intel on what's working on your current campaign analyzing the data sets across cookie free environment. So you can translate those tactics eventually when the cookies do go away. So we have to look at things like temporal or time analysis. We can look at log level data. We can look at site analytics data. We can look at brand measurement tools and how Creative really impacts the campaign success. The second thing we can look at is geo-targeting strategies. The geo-targeting strategy has been underrated because the granularity and DL data could go down all the way to the local level, even beyond zip code. So for example, the census block data. And this is especially important for CPG brands. So we're working closely with the client teams to understand not only the online data, but the offline data and how we can utilize that in the future. We want to optimize investments around markets that are working, so strong markets, and then test in underperforming markets. The third thing we can look at is contextual. So contextual by itself is cookie free. We could build on small-scale usage to test and learn various keywords and content categories based sets, working closely with partners to find ways to leverage their data, to mimic audiences that you are trying to target right now with cookies. The fourth one is publisher data or publisher targeting. So working with your publishers that you have strong relationships with who can curate similar audiences using their own first party data and conducting RFIs to understand the scale and reach against your audience and your future roadmap. So work with your top publishers based on historical data to try to recreate your best strategies. The fifth thing, and I think this is very important, is first party data. That's going to matter more than ever in the cookieless future. Brands will need to think about how to access and develop the first party data starting with the consumer, seeing of value in exchange for the information it's a goldmine and understanding your consumer their intent, their journey. And you need a really great data sciences team to extract insights out of that data, which will be crucial. So partner with strategic onboarding vendors and vet their ability to accept first party data into a clean room environment for targeting, for modeling, for insights. And lastly, the sixth thing that we can do is begin inform prospecting by dedicating test budget to start gaining learnings about cookieless. One, one place that we can start, and it is under invested right now, is Safari and Firefox. They have been cookieless for quite some time. So you can start here and begin testing here. Work with your data scientist team to understand the right mixes to target and start exploring other channels outside of just programmatic cookies. Like CTV, digit auto home, radio, gaming, and so forth. So those are the six steps that we're taking right now with our clients to prepare and plan for the cookieless future. >> So, Chris, let's go back to you. What's the solution here? Is there one, is there multiple solutions? What's the future look like for a cookieless future? >> I think the one certain answer is there definitely is not just one solution. As we all know right now, there seems to be endless solutions, a lot of ideas out there, proposals when the W3C, work happening within other industry bodies, you know, private company solutions being offered. And you know, it's a little bit, it's enough to make everyone's head spin and to try to track it to understand it and understand the impact. And as a publisher, we're obviously, you know, a lot of people are knocking on our door, you know they're saying, hey, our solution is one that it's going to bring in lots of money. You know, all the buy-side is going to use it. This is the one like unlock all the spend. And it's our experience so far is that none of these solutions are, cause I think everyone's still testing and learning. No one on the buy side from our, from our knowledge is really committed to one or a few. It's all about a testing stage. I think that, you know, putting aside all that noise I think what matters the most to us as publishers, actually something Somer mentioned before. It's about control. You know, if we're going to work with a, you know, again outside of our sort of independent internal identifier work that we're doing, if we're going to work with an outside party or an outside approach, does it give us control >> As a publisher to ensure that it is, you know we control the, the data from our users, you know there isn't that data leakage, it's privacy compliant. You know, what information gets shared out there? What is it what's released within, you know within the bitstream? If it is something that's attached to a, someone, a declared user, a registered user that if that then is not somehow amplified or leverage off in another site in a way that is leveraging bit stream data or fingerprinting and going again. And so I think that the spirit of what we're trying to do in a post third party cookie world. And so those controls are critical. And I think to have those controls as publisher we have to be collectively be disciplined. And you know, what solutions that we sort of we test out and what we eventually adopt. But even when that adoption point arrives it definitely will not be one. There will be multiple because there's just too many cases to address. >> Great, great insight there from you guys at News Corp. Somer, let's get back to you. I want to get your thoughts. You've been in many waves of innovation, ups and downs. We're on a new one now. We talked about the open internet and democratization. Journalism is under a lot of pressure now but there's now a wave of quality people, really leaning in towards fighting misinformation, understanding truth and community and data is at the heart of it. What do you see as the new future for journalists to reward journalism? Is there a way, is there a path forward? >> So there's what I hope is going to happen. And then I'm just going to ignore what could, right. You know, there's a trend in market right now at a number of fronts, right? So there are marketers who are leaning in to wanting to spend their marketing dollars with quality journalists, focusing on BiPAC owned and operated, really leaning into supporting those businesses that have been and those publishers that have been ignored for years. I really hope that this trend continues. We are leaning into helping marketers curate that supply, right. And, and really, you know, speak with their dollars about the things that they support and value in market. So I'm hoping that that trend continues. And it's not just sort of like a marketing blip but we will do everything possible to kind of encourage that behavior and give people the information that they need to find. You know, truly high quality journalism. >> That's awesome. Chris, Xiao, Somer, thanks for coming on and sharing your insight on this panel on the cookieless future. Before we go, just quick summary, each of you if you don't mind just giving a quick sound bite or bumper sticker of what we can expect. If you had to throw a prediction for what's going to happen in the next 24 months. Chris, we'll start with you. >> It's going to be quite a ride. I think that's an understatement. I think that there, I wouldn't be surprised if if Google delays the change to the Chrome by a couple months. And may give the industry some much needed time. But no one knows, I guess, I guess I'm not except for someone somewhere, we are deep within Chrome. So I think we all have to operate in a way that changes that happen, changes that happen quickly. And it's going to cover across all facets of the industry, all facets of, you know, from advertising and marketing. So just be prepared. >> Okay. Xiao. Along those same lines, be prepared. Nobody knows what's going to happen in the future. You know, we're all dancing in this together. I think for us, it's planning and preparing and also building on what we've already been working on. So omni-channel, AI, Creative, and I think clients will lean more into those different channels. >> Awesome. Somer, take us home. Last words. >> I think we're in the throwing spaghetti against the wall stage, right? So this is a time of discovery of leaning and trying everything out learning and iterating as fast as we possibly can. >> Awesome. And I love the cat in the background over your shoulder. I can't stop staring at your wonderful cat. Somer, thanks for coming on. Xiao, Chris, thanks for coming on this awesome panel industry breakdown of the Cookie Conundrum, a Recipe for Success data AI open the future is here. It's coming. It's coming fast. I'm John Furrier with theCUBE. Thanks for watching.

(smooth music) >> Hello, everyone. I'm John Furrier with theCUBE. I want to welcome Konrad Feldman, the founder and CEO of Quantcast here, to kick off the Quantcast Industry Summit on the demise of third-party cookies. The event's called 'The Cookie Conundrum, A Recipe for Success', the changing advertising landscape. Super relevant conversation, especially now more than ever. Konrad, welcome to your own program. Kicking this off! Thanks for holding this event. >> It's a pleasure. Great to chat with you today. >> So a big fan, been following your company since the founding of it, and analytics is always the prize of any data-driven company media. Anything's all data-driven now, talk about the open internet because now more than ever, it's under siege. As I, as I mentioned in my open we've been seeing the democratization a new trend of decentralization. We're starting to see, you know everyone's present online now. Clay Shirky, he wrote a book called, 'Here Comes Everyone' in 2005. Well, everyone's here, right? So, you know, we're, we're here. It's got to be more open but yet people are looking at it as closed right now you're seeing the big players, hoarding the data. What's your vision of this open internet? >> Well, an open internet exists for everyone. And if you think about the evolution of the internet, when the internet was created for the first time really in history, anyone that had access to the internet could publish the content whatever they were interested in, you could find an audience. And of course, that's grown to where we are today where 5 billion people around the world are able to engage in all sorts of content, whether that's entertainment or education, news, movies. What's perhaps not so widely understood is that most of that content is paid for by advertising. And there's a lot of systems that support advertising on the open internet and some of those are under siege today, certainly. >> And what's the big pressure point. Is it just more control of the data? Is it just that these walled gardens are wanting to you know, suck the audience in there? Is it monetization driving it? What's the, where's the friction? >> Well, the, the challenge is, is sort of the accumulation of power into a really small number of now giant corporations who have actually reduced a lot of the friction that marketers have in spending their money effectively. And it means that those companies are capturing a disproportionate spend of the, the ad budgets, that fund digital content. So the problem is if more of the money goes to them, less of it's going to independent content creators. It's actually getting harder for independent voices to to emerge and be heard. And so that's the real challenge is that as more power consolidates into just the limited number of tech giants. The funding path for the open internet becomes constrained. And there'll be less choice for consumers without having to pay for subscriptions. >> Yeah, everyone knows the more data you have the better and certainly but the centralized power when the trend is going the other way that the consensus is everyone wants to be decentralized more truth, more trust. All of this is being talked about on the heels of the Google's news around, you know, getting rid of third-party cookies and others have followed suit. What does this mean? I mean, this cookies have been the major vehicle for you know, tracking and getting that kind of data. What is it going to be replaced with? What is this all about? And can you share with us what the future will look like? >> Sure. Well, just as advertising funds the open internet, it's advertising technology that supports that advertising spend and it supports sort of the business of advertising that funds the open internet and within all of that technology is the need for different systems to be able to align around the identification of, for example, a consumer have they been to this site before? Have they seen an ad before? So there's all of these different systems that might be used for advertising, for measurement, for attribution, for creating personalization. And historically they've relied upon the third party cookie as the mechanism for synchronization. Well, the third-party cookie has been in decline for some time. It's already mostly gone from actually Apple Safari browser but Google's Chrome has so much control over how people access the internet. And so it was when Google announced that Chrome was going to deprecate the third party cookie that it really sort of focused the minds of the industry in terms of finding alternative ways to tailor content and ultimately to just simply measure the effectiveness of advertising. And so there's an enormous amount of innovation taking place right now to find alternative solutions. >> You know, some are saying that the free open internet was pretty much killed when you know, the big companies like Facebook and Google started bringing all this data in and kind of pulls all, sucks all the options out of the room, so to speak. What does this mean with cookies now getting rid of by Google. How does it impact publishers, because is it helpful? I mean, hurtful, I mean, where's the, where's the what's a publisher impact? >> Well, I don't think anyone really knows right now. So first of all, cookies weren't necessarily a very good solution to the sort of the challenge of maintaining state and understanding those sorts of, you know the delivery of advertising and so on. It's just the one that's commonly used. I think for different publishers it may mean different things, but you know many publishers need to be able to demonstrate the value and the effectiveness of the advertising solutions that they, that they deliver. So there'll be innovating in terms of how they use their first party data. There'll be continuing to use contextual solutions that have long been used to create advertising relevant relevance. I think the big question of course is how are we going to measure it that any of this is effective at all? Because everyone relies upon measuring advertising effectiveness to justify capturing those budgets in the first place. >> You know, you mentioned a contextual like it's come up a lot. Also in the other interviews we've done with the folks around the internet around this topic of machine learning is a big one, too. What is the impact of this with the modernization of, of, of the solution? You mentioned cookies, okay. Cookies, old technology, but the mechanisms in this ecosystem around it or not, it funds the open internet. What is that modern solution that goes that next level? Is it contextual metadata? Is that a shared systems? What's the >> It's a modernization of that. It's all of those and, and more there's no, there's no single solution to replace the third-party cookie. There'll be a combination of solutions. Part of that will be alternative identity mechanisms. So, you know you will start to see more registration walls to access content so that you have what's called a deterministic identifier. There will be statistical models so-called probabilistic models. Contextual has always been important. It will become more important and it will be combined with, you know we use contextual combining natural language processing with machine learning models to really understand the detailed context of different pages across the internet. You'll also see the use of first party data. And there are discussions about shared beta services as well. I think that it's going to be a whole set of different innovations that we'll need to inter-operate and it's going to be an evolutionary process. As people get used to using these different systems to sort of satisfy the different stages of the media fulfillment cycle from research and planning to activation, to measurement >> You brought up walled gardens. I want to just touch on, on on this kind of concept of walled gardens and, and compare and contrast that with the demand for community. Open internet has always fostered a community vibe. You see network effects mostly in distinct user communities or subnets sub networks. if you will. Kind of walled gardens became that kind of group get together, but then became more of a media solution to make the users the product as they say, Facebook is a great example, right? People talk about Facebook and from that misinformation, abuse. So walled gardens, not the best thing happening right now in the world, but yet, is there any other choice? That's how they're going to make money but yet everyone wants trust, truth, community. Are they mutually exclusive? How do you see this evolving? What's your take? >> Well, I think the open internet is a forum where anyone can have their voice, put their voice out there and have it discovered. And it's in that regard, it's, it's a force for good. Look, I think there are, there are challenges obviously in terms of some of the some of the optimization that takes place within inside the walled gardens. Such as, sort of optimized to drive engagement can have some unintended consequences and obviously that's something that's broadly being discussed today and the impact on society, but sort of more at a more pointed level is just the absorption of advertising dollars. There's a finite amount of money from advertisers. It's estimated to be $400 billion this year in digital advertising. So it's a huge amount of money in terms of funding, the open internet, which sounds great except for it's increasingly concentrated in a tiny number of companies. And so our job at Quantcast as champions of the free and open internet is to help direct money effectively to publishers across the open internet and give advertisers a reliable, repeatable way of accessing the audiences that they care about in the environments they care about and delivering advertising results. >> As a publisher, we care a lot about what our audience wants and try to serve them and listen to them. If we could get the data, we want that data. And then also broker in the monetization with advertisers who might want to reach that audience in whatever way. So this brings up the question of, you know automation and role of data. You know, this is a huge thing of to having that data closed loop if you will, for, for publishers. But yet most publishers are small, some niche, and even as they can become super large, they don't have all the data and more the more data, the better the machine learning. >> That's right. >> So what's the answer to this, as it goes forward how do we get there? What's the dots that that we need to connect to get to that future state? >> So I think it takes, it takes companies working together effectively. I think a really important part of it is, is a more direct conversation with consumers. You know, we've seen that change beginning to happen over the past few years, with the introduction of of regulations that require clear communication to consumers about the data that's captured and why. And I think that creates an opportunity to explain to your audiences the way in which content, is funded. So I think that consumer can that consumer conversation will be part of the collective solution. >> You know, I want to, as we wind down this kickoff segment get your thoughts and vision around the evolution of the internet and you guys have done some great work at Quantcast, it's well documented. But everyone used to talk about traffic, you know buy traffic, then it became cost of acquisitions, PPC search. This is either mechanisms that people have been using for a long, long time. Then, you know your connections but audiences is about traffic, audience traffic. If everyone is online doesn't that become about networks and the people. So I want to get your thoughts and your vision because if community is going to be more important than people agree that it is and things are going to be decentralized, more openness more voices to be heard, you need to address the ability. The formation of networks and groups become super important. What's your vision on that? >> So, my vision is to create relevance and utility for consumers. I think there's one of the things that's often forgotten is that when we make advertising more relevant and useful for consumers, it automatically fulfills the objectives that publishers and marketers have. Everyone wins when advertising is more relevant and our vision is to make advertising relevant across the entire open internet. So that that ad supported model can continue to flourish in that and that 5 billion and hopefully many more billions in the future, people around the world have access to high quality, diverse content. >> If someone asks you Conrad what is Quantcast doing to make the open internet viable now that Cookie's going away? What's the answer? >> So well, the cookie piece is a is a central piece of it in terms of finding solutions that will enable sort of planning, activation and measurement post cookies. And we have a lot of innovation going on there. We're also working with a range of industry bodies and our partners to build solutions for this. What we're really trying to do is to make buying the open internet as straightforward for marketers as it is today in buying the walled gardens. The reason the walled gardens capture so much money is they made it really easy for marketers to get results. Marketers would like to be able to spend their money across all of the diverse publishers of the open internet. You know, our job at Quantcast is to make it just as easy to effectively spend money in funding the content that they really care about in reaching the audiences that they want. >> Great stuff. Great mission, Conrad. Thanks for coming on. Conrad Feldman, founder and CEO here at the 'Cookie Conundrum, Recipe for Success' event. Quantcast industry summit on the demise of third-party cookies. Thank you, Conrad. Appreciate it. >> Thank you. >> Stay with us for more on the industry event around the demise of cookies.

>>what? Hello, I'm john free with the cube. I want to welcome Conrad Feldman, the founder and Ceo of Kwan cast here to kick off the quan cast industry summit on the demise of third party cookies. The events called the cookie conundrum, a recipe for success. The changing advertising landscape, super relevant conversation just now. More than ever. Conrad welcome to your own program kicking this off. Thanks for holding this event. It's a pleasure. Great to chat with you today. So a big fan been following your company since the founding of it. Been analytics is always the prize of any data driven company. Media. Anything's all data driven now. Um, talk about the open internet because now more than ever it's under siege. As I, as I mentioned in my open, um, we've been seeing the democratization, a new trend of decentralization. We're starting to see um, you know, everyone's present online now, Clay Shirky wrote a book called, here comes everyone in 2005. Well everyone's here. Right? So you know, we're here, it's gonna be more open. But yet people are looking at as close right now. You're seeing the big players, um, or in the data. What's your vision of this open internet? >>Well, an open internet exists for everyone. And if you think about the evolution of the internet, when the internet was created for the first time really in history, anyone that had access to the internet could publish the content, whatever they were interested in and could find an audience. And of course that's grown to where we are today, where five billion people around the world are able to engage in all sorts of content, whether that's entertainment or education, news, movies. What's perhaps not so widely understood is that most of that content is paid for by advertising and there's a lot of systems that support advertising on the open Internet and some of those are under siege today certainly. >>And what's the big pressure point? Is it just more control the data? Is it just that these walled gardens are wanting to, you know, suck the audience in there? Is that monetization driving it? What's where's the friction? >>Well, the challenges is sort of the accumulation of power into a really small number of now giant corporations who have actually reduced a lot of the friction that marketers have in spending their money effectively. And it means that those companies are capturing a disproportionate spend of the ad budgets that fund digital content. So the problem is if more of the money goes to them, less of its going to independent content creators. It's actually getting harder for independent voices to emerge and be heard. And so that's the real challenges. That has more power consolidates into just a limited number of tech giants. The funding path for the open Internet becomes constrained and there'll be less choice for consumers without having to pay for subscriptions. >>Everyone knows the more data you have the better and certainly, but the centralized power when the trend is going the other way, the consensus is everyone wants to be decentralized more truth, more trust all this is being talked about on the heels of the google's news around, you know, getting rid of third party cookies and others have followed suit. Um, what does this mean? I mean, this cookies have been the major vehicle for tracking and getting that kind of data. What is gonna be replaced with what is this all about? And can you share with us what the future will look like? >>Sure, Well, just as advertising funds the open Internet is advertising technology that supports that advertising spend. It supports sort of the business of advertising that funds the open Internet. And within all of that technology is the need for different systems to be able to align around um the identification of for example, a consumer, Have they been to this site before? Have they seen an ad before? So there's all of these different systems that might be used for advertising for measurement, for attribution, for creating personalization. And historically they've relied upon the third party cookie as the mechanism for synchronization. Well, the third party cookie has been in decline for some time. It's already mostly gone from actually apple safari browser, but google's chrome has so much control over how people access the internet. And so it was when Google announced that chrome was going to deprecate the third party cookie, that it really sort of focus the minds of the industry in terms of finding alternative ways to tailor content and ultimately to just simply measure the effectiveness of advertising. And so there's an enormous amount of um innovation taking place right now to find alternative solutions. >>You know, some are saying that the free open internet was pretty much killed when, you know, the big comes like facebook and google started bringing all this data and kind of pulls all sucks all the auction in the room, so to speak. What's this mean with cookies now getting, getting rid of um, by google has an impact publishers because is it helpful? I mean hurtful. I mean, where's the where is that, what the publisher impact? >>Well, I don't think anyone really knows right now. So first of all, cookies weren't necessarily a very good solution to the sort of the challenge of maintaining state and understanding those sorts of the delivery of advertising and so on. It's just the one that's commonly used, I think for different publishers it may mean different things. But many publishers need to be able to demonstrate the value and the effectiveness of the advertising solutions that they deliver. So they'll be innovating in terms of how they use their first party data. They'll be continuing to use contextual solutions that have long been used to create advertising relevant, relevant. I think the big question of course is how we're going to measure it that any of this is effective at all because everyone relies upon measuring advertising effectiveness to justify capturing those budgets in the first place. >>You know, you mentioned contextual come up a lot also in the other interviews we've done with the folks in the around the internet around this topic of machine learning is a big 12 What is the impact of this with the modernization of the solution? You mentioned cookies? Okay cookies, old technology. But the mechanisms in this ecosystem around it or not, it funds the open internet. What is that modern solution that goes that next level? Is it contextual metadata? Is that shared systems? What's the it's the modernization of that. >>It's all of those and and more. There's no there's no single solution to replace the third party cookie. There'll be a combination of solutions. Part of that will be alternative identity mechanisms. So you know, you will start to see more registration wars to access content so that you have what's called a deterministic identify there will be statistical models so called probabilistic models, contextual has always been important. It will become more important and it will be combined with we use contextual combining natural language processing with machine learning models to really understand the detailed context of different pages across the internet. You'll also see the use of first party data and there are discussions about shared data services as well. I think there's gonna be a whole set of different innovations that will need to inter operate and it's going to be an evolutionary process as people get used to using these different systems to satisfy the different stages of the media fulfillment cycle from research and planning to activation to measurement. >>You know, you put up walled gardens. I want to just touch on the on on this kind of concept of walled gardens and and and and compare and contrast that with the demand for community, open internet has always fostered a community vibe. You see network effects mostly in distinct user communities or subnets of sub networks. If you will kind of walled gardens became that kind of group get together but then became more of a media solution to make the user is the product, as they say, facebook's a great example, right? People talk about facebook and from that misinformation abuse walled garden is not the best thing happening right now in the world, but yet is there any other other choice? That's how they're going to make money? But yet everyone wants trust, truth community. Are they usually exclusive? How do you see this evolving, what's your take? >>Well, I think the open internet is a, is a forum where anyone can have their voice, uh, put their voice out there and have it discovered and it's in that regard, it's a it's a force for good look. I think there are there are challenges, obviously in terms of some of the some of the optimization that takes place with inside the walled gardens, which is, is sort of optimized to drive engagement can have some unintended consequences. Um obviously that's something that's, that's broadly being discussed today and the impact on society, but sort of more at a more pointed level, it's just the absorption of advertising dollars. There's a finite amount of money from advertisers. It's estimated to be $400 billion this year in digital advertising. So it's a huge amount of money in terms of funding the open Internet, which sounds great except for its increasingly concentrated in a tiny number of companies. And so, you know, our job at Quan cast as champions of the free and open Internet is to help direct money effectively to publishers across the open internet and give advertisers a reliable, repeatable way of accessing the audiences that they care about in the environment they care about and delivering advertising results. >>It's a publisher, we care a lot about what our audience wants and try to serve them and listen to them. If we could get the data, we want that data and then also broker in the monetization with advertisers, who might want to reach that audience in whatever way. So this brings up the question of, you know, automation and role of data. You know, this is a huge thing to having that data closed loop, if you will for for publishers. But yet most publishers are small, some niche. And even as they can become super large, they don't have all the data and more, the more data, the better the machine learning. So what's the answer to this as it goes forward? How do we get there? What's the dots that that we need to connect to get that future state? >>So I think it takes it takes companies working together effectively. I think a really important part of it is, is a more direct conversation with consumers. We've seen that change beginning to happen over the past few years with the introduction of regulations that require clear communication to consumers about the data that's captured. And y and I think that creates an opportunity to explain to your audience is the way in which content is funded. So I think that consumer that consumer conversation will be part of the collective solution. >>You know, I want to as we wind down this kickoff segment, get your thoughts and vision around um, the evolution of the internet and you guys have done some great work at quan Cast is well documented, but everyone used to talk about traffic by traffic, then it became cost of acquisitions. PPC search. This is either mechanisms that people have been using for a long, long time, then you know, your connections but audience is about traffic, audience traffic. If this if my family is online, doesn't it become about networks and the people. So I want to get your thoughts and your vision because if community is going to be more important than people agree that it is and things are gonna be decentralized, more openness, more voices to be heard. You need to dress ability. The formation of networks and groups become super important. What's your vision on that? >>So my vision is to create relevance and utility for consumers. I think that's one of the things that's often forgotten is that when we make advertising more relevant and useful for consumers, it automatically fulfils the objectives that publishers and marketers have, everyone wins when advertising is more relevant. And our vision is to make advertising relevant across the entire open internet so that that ad supported model can continue to flourish and that five billion and hopefully many more billions in the future, people around the world have access to high quality, diverse content. >>If someone asked you Conrad, what is quant cast doing to make the open internet viable now that cookies are going away? What's the answer? >>So well, the cookie pieces is a central piece of it in terms of finding solutions that will enable sort of planning activation and measurement post cookies and we have a lot of innovation going on. There were also working with a range of industry bodies and our and our partners to build solutions for this. What we're really trying to do is to make buying the open internet as straightforward for marketers as it is today and buying the walled gardens. The reason the walled gardens capture so much money is they made it really easy for marketers to get results, marketers would like to be able to spend their money across all of the diverse publishes the open internet. You know, our job at Comcast is to make it just as easy to effectively spend money in funding the content that they really care about in reaching the audiences that they want. >>Great stuff. Great Mission. Conrad, thanks for coming on. Conrad Feldmann founder and Ceo here at the cookie conundrum recipe for success event, Quant Cast Industry summit on the demise of third party cookies. Thank you. Conrad appreciate it. Thank you. Yeah, I'm john ferrier, stay with us for more on the industry event around the middle cookies. Mhm Yeah, yeah, thank you. Mhm. Welcome back to the Qantas industry summit on the demise of third party cookies, the cookie conundrum, a recipe for success. I'm john furrier host of the cube, the changing landscape of advertising is here and shit Gupta, founder of you of digital is joining us chief. Thanks for coming on this segment. Really appreciate, I know you're busy, you've got two young kids as well as providing education to the digital industry, you got some kids to take care of and train them to. So welcome to the cube conversation here as part of the program. >>Yeah, thanks for having me excited to be here. >>So the office of the changing landscape of advertising really centers around the open to walled garden mindset of the web and the big power players. We know the big 34 tech players dominate the marketplace so clearly in a major inflection point and we've seen this movie before Web mobile revolution which was basically a reply platform NG of capabilities. But now we're in an error of re factoring the industry, not re platt forming a complete changing over of the value proposition. So a lot at stake here as this open web, open internet, global internet evolves. What are your, what's your take on this, this industry proposals out there that are talking to this specific cookie issue? What does it mean? And what proposals are out there? >>Yeah, so, you know, I I really view the identity proposals and kind of to to kind of groups, two separate groups. So on one side you have what the walled gardens are doing and really that's being led by google. Right, so google um you know, introduce something called the privacy sandbox when they announced that they would be deprecating third party cookies uh as part of the privacy sandbox, they've had a number of proposals unfortunately, or you know, however you want to say they're all bird themed for some reason, I don't know why. Um but the one, the bird theme proposal that they've chosen to move forward with is called flock, which stands for Federated learning of cohorts. And essentially what it all boils down to is google is moving forward with cohort level learning and understanding of users in the future after third party cookies, unlike what we've been accustomed to in this space, which is a user level understanding of people and what they're doing online for targeting tracking purposes. And so that's on one side of the equation, it's what google is doing with flock and privacy sandbox now on the other side is, you know, things like unified I. D. Two point or the work that I. D five is doing around building new identity frameworks for the entire space that actually can still get down to the user level. Right? And so again, unified I. D. Two point oh comes to mind because it's the one that's probably got the most adoption in the space. It's an open source framework. So the idea is that it's free and pretty much publicly available to anybody that wants to use it and unified, I need to point out again is user level. So it's it's basically taking data that's authenticated data from users across various websites you know that are logging in and taking those authenticated users to create some kind of identity map. And so if you think about those two work streams right, you've got the walled gardens and or you know, google with flock on one side and then you've got unified I. D. Two point oh and other I. D. Frameworks for the open internet. On the other side, you've got these two very differing type of approaches to identity in the future. Again on the google side it's cohort level, it's going to be built into chrome. Um The idea is that you can pretty much do a lot of the things that we do with advertising today, but now you're just doing it at a group level so that you're protecting privacy, whereas on the other side of the open internet you're still getting down to the user level. Um And that's pretty powerful. But the the issue there is scale, right? We know that a lot of people are not logged in on lots of websites. I think the stat that I saw is under five of all website traffic is authenticated. So really if you if you simplify things you boil it all down, you have kind of these two very differing approaches. >>I guess the question it really comes down to what alternatives are out there for cookies and which ones do you think will be more successful? Because I think, you know, the consensus is at least from my reporting, in my view, is that the world agrees. Let's make it open, Which one is going to be better. >>Yeah, that's a great question, john So as I mentioned, right, we have we have to kind of work streams here, we've got the walled garden work streams, work stream being led by google and their work around flock, and then we've got the open internet, right? Let's say unified I. D to kind of represents that. I personally don't believe that there is a right answer or an endgame here. I don't think that one of them wins over the other, frankly, I think that, you know, first of all, you have those two frameworks, neither of them are perfect, they're both flawed in their own ways. There are pros and cons to both of them. And so what we're starting to see now is you have other companies kind of coming in and building on top of both of them as kind of a hybrid solution. Right? So they're saying, hey, we use, you know, an open I. D. Framework in this way to get down to the user level and use that authenticated data and that's important. But we don't have all the scale. So now we go to google and we go to flock to kind of fill the scale. Oh and hey, by the way, we have some of our own special sauce, right? We have some of our own data, we have some of our own partnerships, we're gonna bring that in and layer it on top. Right? And so really where I think things are headed is the right answer, frankly, is not one or the other. It's a little mishmash of both. With a little extra something on top. I think that's that's what we're starting to see out of a lot of companies in the space. And I think that's frankly where we're headed. >>What do you think the industry will evolve to, in your opinion? Because I think this is gonna, you can't ignore the big guys on this because these programmatic you mentioned also the data is there. But what do you think the market will evolve to with this, with this conundrum? >>So, so I think john where we're headed? You know, I think we're right now we're having this existential existential crisis, right? About identity in this industry, because our world is being turned upside down, all the mechanisms that we've used for years and years are being thrown out the window and we're being told they were gonna have new mechanisms, Right? So cookies are going away device ids are going away and now we got to come up with new things and so the world is being turned upside down and everything that you read about in the trades and you know, we're here talking about it, right? Like everyone's always talking about identity right now, where do I think this is going if I was to look into my crystal ball, you know, this is how I would kind of play this out. If you think about identity today. Right? Forget about all the changes. Just think about it now and maybe a few years before today, Identity for marketers in my opinion has been a little bit of a checkbox activity. Right? It's been hey, um, okay, uh, you know ad tech company or a media company, do you have an identity solution? Okay. Tell me a little bit more about it. Okay, Sounds good. That sounds good. Now can we move on and talk about my business and how are you going to drive meaningful outcomes or whatever for my business? And I believe the reason that is, is because identity is a little abstract, right? It's not something that you can actually get meaningful validation against. It's just something that, you know. Yes, You have it. Okay, great. Let's move on, type of thing. Right. And so that, that's, that's kind of where we've been now, all of a sudden The cookies are going away, the device ids are going away. And so the world is turning upside down in this crisis of how are we going to keep doing what we were doing for the last 10 years in the future. So everyone's talking about it and we're trying to re engineer right? The mechanisms now if I was to look into the crystal ball right 2 3 years from now where I think we're headed is not much is going to change. And what I mean by that john is um uh I think that marketers will still go to companies and say do you have an ID solution? Okay tell me more about it. Okay uh Let me understand a little bit better. Okay you do it this way. Sounds good. Now the ways in which companies are going to do it will be different right now. It's flock and unified I. D. And this and that right. The ways the mechanisms will be a little bit different but the end state right? Like the actual way in which we operate as an industry and kind of like the view of the landscape in my opinion will be very simple or very similar, right? Because marketers will still view it as a tell me you have an ID solution. Make me feel good about it. Help me check the box and let's move on and talk about my business and how you're going to solve for my needs. So I think that's where we're going. That is not by any means to discount this existential moment that we're in. This is a really important moment where we do have to talk about and figure out what we're going to do in the future. My just my viewpoint is that the future will actually not look all that different than the present. >>And I'll say the user base is the audience. Their their data behind it helps create new experiences, machine learning and Ai are going to create those and we have the data you have the sharing it or using it as we're finding shit Gupta great insight dropping some nice gems here. Founder of you of Digital and also the Adjunct professor of Programmatic advertising at Levi School of Business and santa Clara University professor. Thank you for coming dropping the gems here and insight. Thank you. >>Thanks a lot for having me john really appreciate >>it. Thanks for watching. The cooking 100 is the cube host Jon ferrier me. Thanks for watching. Mhm. Yeah. Mhm. Hello welcome back to the cookie conundrum recipe for success and industry conference and summit from Guanacaste on the demise of third party cookies. Got a great industry panel here to break it down chris Gunther Senior Vice president Global Head of programmatic at news corp chris thanks for coming on Zal in Managing Director Solutions at Z axis and Summer Simpson. Vice president Product at quan cast stellar panel. Looking forward to this conversation. Uh thanks for coming on and chatting about the cookie conundrum. Thank you for having us. So chris we'll start with you at news corp obviously a major publisher deprecation of third party cookies affects everyone. You guys have a ton of traffic, ton of audience across multiple formats. Um, tell us about the impact to you guys and the reliance he has had on them. And what are you gonna do to prepare for this next level change? >>Sure. I mean, I think like everyone in this industry there's uh a significant reliance and I think it's something that a lot of talk about audience targeting but obviously that reliance on third party cookies pervasive across the whole at tech ecosystem Martek stack. And so you know, we have to think about how that impact vendor vendors, we work with what it means in terms of use cases across marketing, across advertising, across site experience. So, you know, without a doubt, it it's it's significant, but you know, we look at it as listen, it's disruptive, uh, disruption and change is always a little scary. Um, but overall it's a, it's a long overdue reset. I mean, I think that, you know, our perspective is that the cookies, as we all know was it was a crutch, right sort of a technology being used in way it shouldn't. Um, and so as we look at what's going to happen presumably after Jan 2022 then it's, it's a good way to kind of fix on some bad practices practices that lead to data leakage, um, practice or devalue for our perspective, some of the, you know, we offered as as publishers and I think that this is a key thing is that we're not just looking to as we look at the post gender world, not just kind of recreating the prior world because the prior world was flawed or I guess you could say the current world since it hasn't changed yet. But the current world is flawed. Let's not just not, you know, let's not just replicate that. Let's make sure that, you know, third party cookie goes away. Other work around like fingerprinting and things like that. You know, also go away so philosophically, that's where our heads at. And so as we look at how we are preparing, you know, you look at what are the core building blocks of preparing for this world. Obviously one of the key ones is privacy compliance. Like how do we treat our users with consent? Yeah, obviously. Are we um aligned with the regulatory environments? Yeah. In some ways we're not looking just a Jan 2022, but Jan 23 where there's gonna be the majority of our audiences we covered by regulation. And so I think from regulation up to data gathering to data activation, all built around an internal identifier that we've developed that allows us to have a consistent look at our users whether they're logged in or obviously anonymous. So it's really looking across all those components across all our sites and in all in a privacy compliant way. So a lot of work to be done, a lot of work in progress. But we're >>excited about what's going on. I like how you framed at Old world or next gen kind of the current situation kind of flawed. And as you think about programmatic, the concept is mind blowing and what needs to be done. So we'll come back to that because I think that original content view is certainly relevant, a huge investment and you've got great content and audience consuming it from a major media standpoint. Get your perspective on the impact because you've got clients who want to get their their message out in front of the audience at the right time, at the right place and the right context. Right, So your privacy, you got consent, all these things kind of boiling up. How do you help clients prepare? Because now they can go direct to the consumer. Everyone, everyone has a megaphone, now, everyone's, everyone's here, everyone's connected. So how are you impacted by this new notion? >>You know, if if the cookie list future was a tic tac, dance will be dancing right now, and at least into the next year, um this has been top of mind for us and our clients for quite some time, but I think as each day passes, the picture becomes clearer and more in focus. Uh the end of the third party cookie does not mean the end of programmatic. Um so clients work with us in transforming their investments into real business outcomes based on our expertise and based on our tech. So we continue to be in a great position to lead to educate, to partner and to grow with them. Um, along this uh cookie list future, the impact will be all encompassing in changing the ways we do things now and also accelerating the things that we've already been building on. So we take it from the top planning will have a huge impact because it's gonna start becoming more strategic around real business outcomes. Uh where Omni channel, So clients want to drive outcomes, drew multiple touch points of a consumer's journey, whether it has programmatic, whether it has uh cookie free environment, like connected tv, digital home audio, gaming and so forth. So we're going to see more of these strategic holistic plans. Creative will have a lot of impact. It will start becoming more important with creative testing. Creative insights. You know, creative in itself is cookie list. So there will be more focused on how to drive uh brand dialogue to connect to consumers with less targeting. With less cookies, with the cohesiveness of holistic planning. Creative can align through multiple channels and lastly, the role of a. I will become increasingly important. You know, we've always looked to build our tech our products to complement new and existing technology as well as the client's own data and text back to deliver these outcomes for them. And ai in its core it's just taking input data uh and having an output of your desired outcome. So input data could be dSP data beyond cookies such as browser such as location, such as contextual or publisher taking clients first party data, first party crm data like store visitation, sales, site activity. Um and using that to optimize in real time regardless of what vendor or what channel we're on. Um So as we're learning more about this cookie list dance, we're helping our clients on the steps of it and also introducing our own moves. >>That's awesome. Data is going to be a key value proposition, connecting in with content real time. Great stuff. Somewhere with your background in journalism and you're the tech VP of product at quan cast. You have the keys to the kingdom over there. It's interesting Journalism is about truth and good content original content. But now you have a data challenge problem opportunity on both sides, brands and publishers coming together. It's a data problem in a way it's a it's a tech stack, not so much just getting the right as to show up at the right place the right time. It's really bigger than that now. What's your take on this? >>Um you know, >>so first >>I think that consumers already sort of like except that there is a reasonable value exchange for their data in order to access free content. Right? And that's that's a critical piece for us to all kind of like understand over the past. Hi guys, probably two years since even even before the G. D. P. R. We've been doing a ton of discovery with customers, both publishers and marketers. Um and so you know, we've kind of known this, this cookie going away thing has been coming. Um And you know, Google's announcement just kind of confirmed it and it's been, it's been really, really interesting since Google's announcement, how the conversations have changed with with our customers and other folks that we talked to. And I've almost gone from being like a product manager to a therapist because there's such an emotional response. Um you know, from the marketing perspective, there's real fear there. There's like, oh my God, how you know, it's not just about, you know, delivering ads, it's about how do I control frequency? How do I, how do I measure, you know, success? Because the technology has has grown so much over the years to really give marketers the ability to deliver personalized advertising, good content, right. The consumers um and be able to monitor it and control it so that it's not too too intrusive on the publisher perspective side, we see slightly different response. It's more of a yes, right. You know, we're taking back control and we're going to stop the data leakage, we're going to get the value back for our inventory. Um and that both things are a good thing, but if it's, if it's not managed, it's going to be like ships passing in the night, right? In terms of um of, you know, they're there, them coming together, right, and that's the critical pieces that they have to come together. They have to get closer, you got to cut out a lot of that loom escape in the middle so that they can talk to each other and understand what's the value exchange happening between marketers and publishers and how do we do that without cookies? >>It's a fascinating, I love love your insight there. I think it's so relevant and it's got broader implications because, you know, if you look at how data's impact, some of these big structural changes and re factoring of industries, look at cyber security, you know, no one wants to share their data, but now if they share they get more insight, more machine learning, benefit more ai benefit. So now we have the sharing notion, but that goes against counter the big guys that want to wall garden, they want to hoard all the data and and control that to provide their own personalization. So you have this confluence of, hey, I want to hoard the data and then now I want to share the data. So so christmas summer you're in the, in the wheelhouse, you got original content and there's other providers out there. So is there the sharing model coming with privacy and these kinds of services? Is the open, come back again? How do you guys see this uh confluence of open versus walled gardens, because you need the data to make machine learning good. >>So I'll start uh start off, I mean, listen, I think you have to give credit to the walled gardens have created, I think as we look as publishers, what are we offering to our clients, what are we offering to the buy side? We need to be compelling. We shouldn't just be uh yeah, actually as journalists, I think that there is a case of the importance of funding journalism. Um but ultimately we need to make sure we're meeting the KPI is and the business needs of the buy side. And I think around that it is the sort of three core pillars that its ease of access, its scope of of activation and targeting and finally measurable results. So as I think is us as an individual publishers, so we have, we have multiple publications. So we do have scale. But then in partnership with other publishers perhaps to organizations like pre bid, you know, I think we can, you know, we're trying to address that and I think we can offer something that's compelling um, and transparent in terms of what these results are. But obviously, you know, I want to make sure it's clear transparent terms of results, but obviously where there's privacy in terms of the data and I think the form, you know, I think we've all heard a lot like data clean rooms, a lot of them out there flogging those wears. I think there's something valuable but you know, I think it's the right who is sort of the right partner or partners um and ultimately who allows us to get as close as possible to the buy side. And so that we can share that data for targeting, share it for perhaps for measurement, but obviously all in a privacy compliant >>way summer, what's your take on this? Because you talk about the future of the open internet democratization, the network effect that we're seeing in Vire al Itty and across multiple on the on the channels. Is that pointed out what's happening? That's the distribution now. So um that's almost an open garden model. So it's like um yeah, >>yeah, it's it's um you know, back in the day, you know, um knight ridder who was who was the first group that I that I worked for, um you know, each of those individual properties, um we're not hugely valuable on their own from a digital perspective, but together as a unit, they became valuable, right, and got scale for advertisers. Now we're in a place where, you know, I kind of think that each of those big networks are going to have to come together and work together to compare in size to the, to the world gardens. Um, and yeah, this is something that we've talked about before and an open garden. Um, I think that's the, that's the definitely the right route to take. And I and I agree with chris it's, it's about publishers getting as close to the market. Is it possible working with the tech companies that enable them to do that and doing so in a very privacy centric >>way. So how do we bring the brands and agencies together to get ready for third party cookies? Because there is a therapist moment here of it's gonna be okay. The parachute will open. The future is not gonna be as as grim. Um, it's a real opportunity. But if managed properly, what's your take on this is just more first party data strategy and what's your assessment of this? >>So we collaborated right now with ball grants on how did this still very complex cookie list future. Um, you know what's going to happen in the future? 2, 6 steps that we can take right now and market should take. Um, The first step is to gather intel on what's working on your current campaign, analyzing the data sets across cookie free environment. So you can translate those tactics eventually when the cookies do go away. So we have to look at things like temperature or time analysis. We could look at log level data. We could look at site analytics data. We can look at brand measurement tools and how creative really impacts the campaign success. The second thing we can look at is geo targeting strategies. The geo target strategy has been uh underrated because the granularity and geo data could go down all the way to the local level, even beyond zip code. So for example the census black data and this is especially important for CPG brands. So we're working closely with the client teams to understand not only the online data but the offline data and how we can utilize that in the future. Uh We want to optimize investments around uh markets that are working so strong markets and then test and underperforming markets. The third thing we can look at is contextual. So contextual by itself is cookie free. Uh We could build on small scale usage to test and learn various keywords and content categories based sets. Working closely with partners to find ways to leverage their data to mimic audiences that you are trying to target right now with cookies. Um the 4th 1 is publisher data or publisher targeting. So working with your publishers that you have strong relationships with who can curate similar audiences using their own first party data and conducting RFs to understand the scale and reach against your audience and their future role maps. So work with your top publishers based on historical data to try to recreate your best strategies. The 15 and I think this is very important is first party data, you know, that's going to matter more than ever. In the calculus future brands will need to think about how to access and developed the first party data starting with the consumers seeing a value in exchange for the information. It's a gold mine and understanding of consumer, their intent, the journey um and you need a really great data science team to extract insights out of that data, which will be crucial. So partner with strategic onboarding vendors and vet their ability to accept first party data into a cleaner environment for targeting for modeling for insight. And lastly, the six thing that we can do is begin to inform prospect prospecting by dedicating test budget to start gaining learnings about cookie list 11 place that we can start and it is under invested right now is Safari and Firefox. They have been calculus for quite some time so you can start here and begin testing here. Uh work with your data scientist team to understand the right mix is to to target and start exploring other channels outside of um just programmatic cookies like CTV digital, out of home radio gaming and so forth. So those are the six steps that we're taking right now with our clients to uh prepare and plan for the cookie list future. >>So chris let's go back to you. What's the solution here? Is there one, is there multiple solutions? What's the future look like for a cookie was future? >>Uh I think the one certain answers, they're definitely not just one solution. Um as we all know right now there there seems to be endless solutions, a lot of ideas out there, proposals with the W three C uh work happening within other industry bodies uh you know private companies solutions being offered and you know, it's a little bit of it's enough to make everyone's head spin and to try to track it to understand and understand the impact. And as a publisher were obviously a lot of people are knocking on our door. Uh they're saying, hey our solution is one that is going to bring in lots of money, you know, the all the buy side is going to use it. This is the one like I ma call to spend um, and so expect here and so far is that none of these solutions are I think everyone is still testing and learning no one on the buy side from our, from our knowledge is really committed to one or a few. It's all about a testing stage. I think that, you know, putting aside all that noise, I think what matters the most to us as publisher is actually something summer mentioned before. It's about control. You know, if we're going to work with a again, outside of our sort of, you know, internal identifier work that we're doing is we're going to work with an outside party or outside approach doesn't give us control as a publisher to ensure that it is, we control the data from our users. There isn't that data leakage, it's probably compliant. What information gets shared out there. What is it, what's released within within the bid stream? Uh If it is something that's attached to a somewhat declared user registered user that if that then is not somehow amplified or leverage off on another site in a way that is leveraging bit stream data or fingerprinting and going against. I think that the spirit of what we're trying to do in a post third party cookie world so that those controls are critical and I think they have those controls, his publisher, we have collectively be disciplined in what solutions that we we test out and what we eventually adopt. But even when the adoption point arrives, uh definitely it will not be one. There will be multiple because it's just too many use cases to address >>great, great insight there from, from you guys, news corp summer. Let's get back to you. I want to get your thoughts. You've been in many waves of innovation ups and downs were on a new one. Now we talked about the open internet democratization. Journalism is under a lot of pressure now, but there's now a wave of quality people really leaning in towards fighting misinformation, understanding truth and community and date is at the heart of it. What do you see as the new future for journalists, reward journalism is our ways their path forward. >>So there's uh, there's what I hope is going to happen. Um, and then I'm just gonna ignore what could write. Um, you know, there's there's a trend in market right now, a number of fronts, right? So there are marketers who are leaning into wanting to spend their marketing dollars with quality journalists, focusing on bipac owned and operated, really leaning into into supporting those businesses that have been uh, those publishers that have been ignored for years. I really hope that this trend continues. Um We are leaning into into helping um, marketers curate that supply right? And really, uh, you know, speak with their dollars about the things that that they support. Um, and uh, and and value right in market. So I'm hoping that that trend continues and it's not just sort of like a marketing blip. Um, but we will do everything possible to kind of like encourage that behavior and and give people the information they need to find, you know, truly high quality journalism. >>That's awesome chris Summer. Thanks for coming on and sharing your insight on this panel on the cookie list future. Before we go, just quick summary each of you. If you don't mind just giving a quick sound bite or bumper sticker of what we can expect. If you had to throw a prediction For what's going to happen in the next 24 months Chris We'll start with you. >>Uh it's gonna be quite a ride. I think that's an understatement. Um I think that there, I wouldn't be surprised if if google delays the change to the chrome by a couple of months and and may give the industry some much needed time, but no one knows. I guess. I guess I'm not except for someone somewhere deep within chrome. So I think we all have to operate in a way that changes to happen, changes to happen quickly and it's gonna cover across all facets of the industry, all facets of from advertising, marketing. So just be >>prepared. >>Yeah, along the same lines, be prepared, nobody knows what's going to happen in the future. Uh You know, while dancing in this together. Uh I think um for us it's um planning and preparing and also building on what we've already been working on. Um So omni channel ai um creative and I think clients will uh lean more into those different channels, >>awesome. So we'll pick us home, last word. >>I think we're in the throwing spaghetti against the wall stage. Right, so this is a time of discovery of leaning in trying everything out, Learning and iterating as fast as we possibly >>can. Awesome. And I love the cat in the background over your shoulder. Can't stop staring at your wonderful cat. Thanks for coming on chris, Thanks for coming on. This awesome panel industry breakdown of the cookie conundrum. The recipe for success data ai open. Uh The future is here, it's coming, it's coming fast. I'm john fryer with the cube. Thanks for watching. Mhm. Yeah. Mhm. Mhm. Welcome back to the Quant Cast industry summit on the demise of third party cookies. The cookie conundrum, a recipe for success. We're here peter day. The cto of quad cast and crew T cop car, head of product marketing quad cast. Thanks for coming on talking about the changing advertising landscape. >>Thanks for having us. Thank you for having >>us. So we've been hearing this story out to the big players. Want to keep the data, make that centralized control, all the leverage and then you've got the other end. You got the open internet that still wants to be free and valuable for everyone. Uh what's what are you guys doing to solve this problem? Because cookies go away? What's going to happen there? How do people track things you guys are in this business first question? What is quan cast strategies to adapt to third party cookies going away? What's gonna be, what's gonna be the answer? >>Yeah. So uh very rightly said, john the mission, the Qantas mission is the champion of free and open internet. Uh And with that in mind, our approach to this world without third party cookies is really grounded in three fundamental things. Uh First as industry standards, we think it's really important to participate and to work with organizations who are defining the standards that will guide the future of advertising. So with that in mind, we've been participating >>with I. A. B. >>Tech lab, we've been part of their project Triarc. Uh same thing with pre bid, who's kind of trying to figure out the pipes of identity. Di di di di di pipes of uh of the future. Um And then also is W three C, which is the World Wide Web Consortium. Um And our engineers and our engineering team are participating in their weekly meetings trying to figure out what's happening with the browsers and keeping up with the progress they're on things such as google's block. Um The second uh sort of thing is interoperability, as you've mentioned, there are lots of different uh I. D. Solutions that are emerging. You have you I. D. Two point oh, you have live RAM, you have google's flock. Uh And there will be more, there are more and they will continue to be more. Uh We really think it is important to build a platform that can ingest all of these signals. And so that's what we've done. Uh The reason really is to meet our customers where they are at today. Our customers use multiple different data management platforms, the mps. Um and that's why we support multiple of those. Um This is not going to be much different than that. We have to meet our customers where we are, where they are at. And then finally, of course, which is at the very heart of who contrast is innovation. Uh As you can imagine being able to take all of these multiple signals in including the I. D. S. And the cohorts, but also others like contextual first party um consent is becoming more and more important. Um And then there are many other signals, like time, language geo location. So all of these signals can help us understand user behavior intent and interests um in absence of 3rd party cookies. However, uh there's there's something to note about this. They're very raw, their complex, they're messy all of these different signals. Um They are changing all the time, they're real time. Um And there's incomplete information isolation. Just one of these signals cannot help you build a true and complete picture. So what you really need is a technology like AI and machine learning to really bring all of these signals together, combine them statistically and get an understanding of user behavior intent and interests and then act on it, be it in terms of providing audience insights um or responding to bid requests and and so on and so forth. So those are sort of the three um fundamentals that our approach is grounded in which is industry standards, interoperability and and innovation. Uh and you know, you have peter here, who is who is the expert So you can dive much deeper into >>it. Is T. T. O. You've got to tell us how is this going to actually work? What are you guys doing from a technology standpoint to help with data driven advertising in a third party cookie list world? >>Well, we've been um This is not a shock, you know, I think anyone who's been close to his space has known that the 3rd Party Cookie has been um uh reducing inequality in terms of its pervasiveness and its longevity for many years now. And the kind of death knell is really google chrome making a, making the changes that they're gonna be making. So we've been investing in the space for many years. Um and we've had to make a number of hugely diverse investment. So one of them is in how as a marketer, how do I tell if my marketing still working in the world without >>computers? The >>majority of marketers completely reliant on third party cookies today to tell them if they're if they're marketing is working or not. And so we've had to invest heavily and statistical techniques which are closer to kind of economic trick models that markets are used to things like out of home advertising, It's going to establishing whether they're advertising is working or not in a digital environment actually, >>just as >>often, you know, as is often the case in these kind of times of massive disruption, there's always opportunity to make things better. And we really think that's true. And you know, digital measurement has often mistaken precision for accuracy. And there's a real opportunity to kind of see the wood for the trees if you like. And start to come with better methods of measuring the affections of advertising without third party cookies. And in fact to make countless other investments in areas like contextual modeling and and targeting that third party cookies and and uh, connecting directly to publishers rather than going through this kind of bloom escape that's gonna tied together third party cookies. So if I was to enumerate all the investments we've made, I think we'll be here till midnight but we have to make a number of vestments over a number of years and that level investments only increasing at the moment. >>Peter on that contextual. Can you just double click on that and tell us more? >>Yeah, I mean contextual is unfortunately these things, this is really poorly defined. It can mean everything from a publisher saying, hey, trust us, this dissipated about CVS to what's possible now and has only really been possible the last couple of years, which is to build >>statistical >>models of the entire internet based on the content that people are actually consumed. And this type of technology requires massive data processing capabilities. It's able to take advantage of the latest innovations in there is like natural language processing and really gives um computers are kind of much deeper and richer understanding of the internet, which ultimately makes it possible to kind of organize, organized the Internet in terms of the types of content of pages. So this type of technology has only been possible the last two years and we've been using contextual signals since our inception, it's always been massively predictive in terms of audience behaviours, in terms of where advertising is likely to work. And so we've been very fortunate to keep the investment going um and take advantage of many of these innovations that have happened in academia and in kind of uh in adjacent areas >>on the ai machine learning aspect, that seems to be a great differentiator in this day and age for getting the most out of the data. How is machine learning and ai factoring into your platform? >>I think it's, it's how we've always operated right from our interception when we started as a measurement company, the way that we were giving our customers at the time, we were just publishers, just the publisher side of our business insights into who their audience was, were, was using machine learning techniques. And that's never really changed. The foundation of our platform has always been, has always been machine learning from from before. It was cool. A lot of our kind of, a lot of our core teams have backgrounds in machine learning phds in statistics and machine learning and and that really drives our our decision making. I mean, data is only useful if you can make sense of it and if you can organize it and if you can take action on it and to do that at this kind of scout scale, it's absolutely necessary to use machine learning technology. >>So you mentioned contextual also, you know, in advertising, everyone knows in that world that you've got the contextual behavioural dynamics, the behavior that's kind of generally everyone's believing is happening. The consensus is undeniable is that people are wanting to expect an environment where there's trust, there's truth, but also they want to be locked in. They don't wanna get walled into a walled garden, nobody wants to be in the world, are they want to be free to pop around and visit sites is more horizontal scalability than ever before. Yet, the bigger players are becoming walled garden, vertical platforms. So with future of ai the experience is going to come from this data. So the behavior is out there. How do you get that contextual relevance and provide the horizontal scale that users expect? >>Yeah, I think it's I think it's a really good point and we're definitely this kind of tipping point. We think, in the broader industry, I think, you know, every published right, we're really blessed to work with the biggest publishers in the world, all the way through to my mom's vlog, right? So we get to hear the perspectives of publishers at every scale. I think they consistently tell us the same thing, which is they want to more directly connected consumers, they don't wanna be tied into these walled gardens, which dictate how they must present their content and in some cases what content they're allowed to >>present. >>Um and so our job as a company is to really provide level >>the playing field a little bit, >>provide them the same capabilities they're only used to in the walled gardens, but let's give them more choice in terms of how they structure their content, how they organize their content, how they organize their audiences, but make sure that they can fund that effectively by making their audiences in their environments discoverable by marketers measurable by marketers and connect them as directly as possible to make that kind of ad funded economic model as effective in the open Internet as it is in social. And so a lot of the investments we've made over recent years have been really to kind of realize that vision, which is, it should be as easy for a marketer to be able to understand people on the open internet as it is in social media. It should be as effective for them to reach people in the environment is really high quality content as it is on facebook. And so we invest a lot of a lot of our R and D dollars in making that true. We're now live with the Comcast platform, which does exactly that. And as third party cookies go away, it only um only kind of exaggerated or kind of further emphasizes the need for direct connections between brands and publishers. And so we just wanna build the technology that helps make that true and gives the kind of technology to these marketers and publishers to connect and to deliver great experiences without relying on these kind of walled >>gardens. Yeah, the Director Director, Consumer Director audience is a new trend. You're seeing it everywhere. How do you guys support this new kind of signaling from for for that's happening in this new world? How do you ingest the content and just this consent uh signaling? >>Uh we were really fortunate to have an amazing, amazing R and D. Team and, you know, we've had to do all sorts to make this, you need to realize our vision. This has meant things like, you know, we have crawlers which scan the entire internet at this point, extract the content of the pages and kind of make sense of it and organize it uh, and organize it for publishers so they can understand how their audiences overlap with potential competitors or collaborators. But more importantly, organize it for marketers. So you can understand what kind of high impact opportunities are there for them there. So, you know, we've had to we've had to build a lot of technology. We've had to build analytics engines, which can get answers back in seconds so that marketers and publishers can kind of interact with their own data and make sense of it and present it in a way that's compelling and help them drive their strategy as well as their execution. We've had to invest in areas like consent management because we believe that a free and open internet is absolutely reliant on trust and therefore we spend a lot of our time thinking about how do we make it easy for end users to understand who has access to their data and easy for end users to be able to opt out. And uh and as a result of that, we've now got the world's most widely adopted adopted consent management platform. So it's hard to tackle one of these problems without tackling all of them. Were fortunate enough to have had a large enough R and D budget over the last four or five years, make a number investments, everything from consent and identity through context, your signals through the measurement technologies, which really bring advertisers >>and Publishers places together great insight. Last word for you is what's the what's the customer view here as you bring these new capabilities of the platform, uh what's what are you guys seeing as the highlight uh from a platform perspective? >>So the initial response that we've seen from our customers has been very encouraging, both on the publisher side as well as the marketer side. Um I think, you know, one of the things we hear quite a lot is uh you guys are at least putting forth a solution, an actual solution for us to test Peter mentioned measurement, that really is where we started because you cannot optimize what you cannot measure. Um so that that is where his team has started and we have some measurement very, very uh initial capabilities still in alpha, but they are available in the platform for marketers to test out today. Um so the initial response has been very encouraging. People want to engage with us um of course our, you know, our fundamental value proposition, which is that the Qantas platform was never built to be reliant on on third party data. These stale segments like we operate, we've always operated on real time live data. Um The second thing is, is our premium publisher relationships. We have had the privilege of working like Peter said with some of the um biggest publishers, but we also have a very wide footprint. We have first party tags across um over 100 million plus web and mobile destinations. Um and you know, as you must have heard like that sort of first party footprint is going to come in really handy in a world without third party cookies, we are encouraging all of our customers, publishers and marketers to grow their first party data. Um and so that that's something that's a strong point that customers love about us and and lean into it quite a bit. Um So yeah, the initial response has been great. Of course it doesn't hurt that we've made all these are in the investments. We can talk about consent. Um, and you know, I often say that consent, it sounds simple, but it isn't, there's a lot of technology involved, but there's lots of uh legal work involved as it as well. We have a very strong legal team who has expertise built in. So yeah, very good response. Initially >>democratization. Everyone's a publisher. Everyone's a media company. They have to think about being a platform. You guys provide that. So I congratulate Peter. Thanks for dropping the gems there. Shruti, thanks for sharing the product highlights. Thanks for, for your time. Thank you. Okay, this is the quan cast industry summit on the demise of third party cookies. And what's next? The cookie conundrum. The recipe for success with Kwan Cast. I'm john free with the cube. Thanks for watching. Mm

>>from around the globe. It's the Cube covering space and cybersecurity. Symposium 2020 hosted by Cal Poly >>Oven. Welcome back to the Space and Cyber Security Symposium. 2020 I'm John for your host with the Cuban silicon angle, along with Cal Poly, representing a great session here on industry success in developing space and cybersecurity. Resource is Got a great lineup. Brigadier General Steve Hotel, whose are also known as Bucky, is Call Sign director of Space Portfolio Defense Innovation Unit. Preston Miller, chief information security officer at JPL, NASA and Major General retired Clint Crozier, director of aerospace and satellite solutions at Amazon Web services, also known as a W s. Gentlemen, thank you for for joining me today. So the purpose of this session is to spend the next hour talking about the future of workforce talent. Um, skills needed and we're gonna dig into it. And Spaces is an exciting intersection of so many awesome disciplines. It's not just get a degree, go into a track ladder up and get promoted. Do those things. It's much different now. Love to get your perspectives, each of you will have an opening statement and we will start with the Brigadier General Steve Hotel. Right? >>Thank you very much. The Defense Innovation Unit was created in 2015 by then Secretary of Defense Ash Carter. To accomplish three things. One is to accelerate the adoption of commercial technology into the Department of Defense so that we can transform and keep our most relevant capabilities relevant. And also to build what we call now called the national Security Innovation Base, which is inclusive all the traditional defense companies, plus the commercial companies that may not necessarily work with focus exclusively on defense but could contribute to our national security and interesting ways. Um, this is such an exciting time Azul here from our other speakers about space on and I can't, uh I'm really excited to be here today to be able to share a little bit of our insight on the subject. >>Thank you very much. Precedent. Miller, Chief information security officer, Jet Propulsion Lab, NASA, Your opening statement. >>Hey, thank you for having me. I would like to start off by providing just a little bit of context of what brings us. Brings us together to talk about this exciting topic for space workforce. Had we've seen In recent years there's been there's been a trend towards expanding our space exploration and the space systems that offer the great things that we see in today's world like GPS. Um, but a lot of that has come with some Asian infrastructure and technology, and what we're seeing as we go towards our next generation expects of inspiration is that we now want to ensure that were secured on all levels. And there's an acknowledgement that our space systems are just a susceptible to cyber attacks as our terrestrial assistance. We've seen a recent space, uh, policy Directive five come out from our administration, that that details exactly how we should be looking at the cyber principle for our space systems, and we want to prevent. We want to prevent a few things as a result of that of these principles. Spoofing and jamming of our space systems are not authorized commands being sent to those space systems, lots of positive control of our space vehicles on lots of mission data. We also acknowledge that there's a couple of frameworks we wanna adopt across the board of our space systems levers and things like our nice miss cybersecurity frameworks. eso what has been a challenge in the past adopted somebody Cyber principles in space systems, where there simply has been a skill gap in a knowledge gap. We hire our space engineers to do a few things. Very well designed space systems, the ploy space systems and engineer space systems, often cybersecurity is seen as a after thought and certainly hasn't been a line item and in any budget for our spaces in racing. Uh, in the past in recent years, the dynamic started to change. We're now now integrating cyber principles at the onset of development of these life cycle of space. Systems were also taking a hard look of how we train the next generation of engineers to be both adequate. Space engineers, space system engineers and a cyber engineers, as a result to Mrs success on DWI, also are taking a hard look at What do we mean when we talk about holistic risk management for our space assistance, Traditionally risk management and missing insurance for space systems? I've really revolved around quality control, but now, in recent years we've started to adopt principles that takes cyber risk into account, So this is a really exciting topic for me. It's something that I'm fortunate to work with and live with every day. I'm really excited to get into this discussion with my other panel members. Thank you. >>You Preston. Great insight there. Looking forward. Thio chatting further. Um, Clint Closure with a W. S now heading up. A director of aerospace and satellite Solutions, formerly Major General, Your opening statement. >>Thanks, John. I really appreciate that introduction and really appreciate the opportunity to be here in the Space and Cybersecurity Symposium. And thanks to Cal Poly for putting it together, you know, I can't help, but as I think to Cal Poly there on the central California coast, San Luis Obispo, California I can't help but to think back in this park quickly. I spent two years of my life as a launch squadron commander at Vandenberg Air Force Base, about an hour south of Cal Poly launching rockets, putting satellites in orbit for the national intelligence community and so some really fond memories of the Central California coast. I couldn't agree more with the theme of our symposium this week. The space and cyber security we've all come to know over the last decade. How critical spaces to the world, whether it's for national security intelligence, whether it's whether communications, maritime, agriculture, development or a whole host of other things, economic and financial transactions. But I would make the case that I think most of your listeners would agree we won't have space without cybersecurity. In other words, if we can't guaranteed cybersecurity, all those benefits that we get from space may not be there. Preston in a moment ago that all the threats that have come across in the terrestrial world, whether it be hacking or malware or ransomware or are simple network attacks, we're seeing all those migrate to space to. And so it's a really important issue that we have to pay attention to. I also want to applaud Cow Pauling. They've got some really important initiatives. The conference here, in our particular panel, is about developing the next generation of space and cyber workers, and and Cal Poly has two important programs. One is the digital transformation hub, and the other is space data solutions, both of which, I'm happy to say, are in partnership with a W. S. But these were important programs where Cal Poly looks to try to develop the next generation of space and cyber leaders. And I would encourage you if you're interested in that toe. Look up the program because that could be very valuable is well, I'm relatively new to the AWS team and I'm really happy Thio team, as John you said recently retired from the U. S. Air Force and standing up the U. S. Space force. But the reason that I mentioned that as the director of the aerospace and satellite team is again it's in perfect harmony with the theme today. You know, we've recognized that space is critically important and that cyber security is critically important and that's been a W s vision as well. In fact, a W s understands how important the space domain is and coupled with the fact that AWS is well known that at a W s security is job zero and stolen a couple of those to fax A. W. S was looking to put together a team the aerospace and satellite team that focus solely and exclusively every single day on technical innovation in space and more security for the space domain through the cloud and our offerings there. So we're really excited to reimagine agree, envision what space networks and architectures could look like when they're born on the cloud. So that's important. You know, talk about workforce here in just a moment, but but I'll give you just a quick sneak. We at AWS have also recognized the gap in the projected workforce, as Preston mentioned, Um, depending on the projection that you look at, you know, most projections tell us that the demand for highly trained cyber cyber security cloud practitioners in the future outweighs what we think is going to be the supply. And so a ws has leaned into that in a number of ways that we're gonna talk about the next segment. I know. But with our workforce transformation, where we've tried to train free of charge not just a W s workers but more importantly, our customers workers. It s a W s we obsessed over the customer. And so we've provided free training toe over 7000 people this year alone toe bring their cloud security and cyber security skills up to where they will be able to fully leverage into the new workforce. So we're really happy about that too? I'm glad Preston raised SPD five space policy Directive five. I think it's gonna have a fundamental impact on the space and cyber industry. Uh, now full disclosure with that said, You know, I'm kind of a big fan of space policy directives, ESPN, Or was the space policy directive that directed to stand up of the U. S. Space Force and I spent the last 18 months of my life as the lead planner and architect for standing up the U. S. Space force. But with that said, I think when we look back a decade from now, we're going to see that s p d five will have as much of an impact in a positive way as I think SPD for on the stand up of the space Force have already done so. So I'll leave it there, but really look forward to the dialogue and discussion. >>Thank you, gentlemen. Clint, I just wanna say thank you for all your hard work and the team and the people who were involved in standing up Space force. Um, it is totally new. It's a game changer. It's modern, is needed. And there's benefits on potential challenges and opportunities that are gonna be there, so thank you very much for doing that. I personally am excited. I know a lot of people are excited for what the space force is today and what it could become. Thank you very much. >>Yeah, Thanks. >>Okay, So >>with >>that, let me give just jump in because, you know, as you're talking about space force and cybersecurity and you spend your time at Vanderburgh launching stuff into space, that's very technical. Is operation okay? I mean, it's complex in and of itself, but if you think about like, what's going on beyond in space is a lot of commercial aspect. So I'm thinking, you know, launching stuff into space on one side of my brain and the other side of brain, I'm thinking like air travel. You know, all the logistics and the rules of the road and air traffic control and all the communications and all the technology and policy and, you >>know, landing. >>So, Major General Clint, what's your take on this? Because this is not easy. It's not just one thing that speaks to the diversity of workforce needs. What's your reaction to that? >>Yeah. I mean, your observation is right on. We're seeing a real boom in the space and aerospace industry. For all the good reasons we talked about, we're recognizing all the value space from again economic prosperity to exploration to being ableto, you know, improve agriculture and in weather and all those sorts of things that we understand from space. So what I'm really excited about is we're seeing this this blossom of space companies that we sort of referred to his new space. You know, it used to be that really only large governments like the United States and a handful of others could operate in the space domain today and largely infused because of the technological innovation that have come with Cyber and Cyrus Space and even the cloud we're seeing more and more companies, capabilities, countries, all that have the ability, you know. Even a well funded university today can put a cube sat in orbit, and Cal Poly is working on some of those too, by the way, and so it's really expanded the number of people that benefits the activity in space and again, that's why it's so critically important because we become more and more reliant and we will become more and more reliant on those capabilities that we have to protect him. It's fundamental that we do. So, >>Bucky, I want you to weigh in on this because actually, you you've flown. Uh, I got a call sign which I love interviewing people. Anyone who's a call sign is cool in my book. So, Bucky, I want you to react to that because that's outside of the technology, you know, flying in space. There's >>no >>rule. I mean, is there like a rules? I mean, what's the rules of the road? I mean, state of the right. I mean, what I mean, what what's going? What's gonna have toe happen? Okay, just logistically. >>Well, this is very important because, uh and I've I've had access thio information space derived information for most of my flying career. But the amount of information that we need operate effectively in the 21st century is much greater than Thanet has been in the past. Let me describe the environment s so you can appreciate a little bit more what our challenges are. Where, from a space perspective, we're going to see a new exponential increase in the number of systems that could be satellites. Uh, users and applications, right? And so eso we're going we're growing rapidly into an environment where it's no longer practical to just simply evolved or operate on a perimeter security model. We and with this and as I was brought up previously, we're gonna try to bring in MAWR commercial capabilities. There is a tremendous benefit with increasing the diversity of sources of information. We use it right now. The military relies very heavily on commercial SAT com. We have our military capabilities, but the commercial capabilities give us capacity that we need and we can. We can vary that over time. The same will be true for remote sensing for other broadband communications capabilities on doing other interesting effects. Also, in the modern era, we doom or operations with our friends and allies, our regional partners all around the world, in order to really improve our interoperability and have rapid exchange of information, commercial information, sources and capabilities provides the best means of doing that. So that so that the imperative is very important and what all this describes if you want to put one word on it. ISS, we're involving into ah hybrid space architectures where it's gonna be imperative that we protect the integrity of information and the cyber security of the network for the things most important to us from a national security standpoint. But we have to have the rules that that allows us to freely exchange information rapidly and in a way that that we can guarantee that the right users are getting the right information at the right. >>We're gonna come back to that on the skill set and opportunities for people driving. That's just looking. There's so much opportunity. Preston, I want you to react to this. I interviewed General Keith Alexander last year. He formerly ran Cyber Command. Um, now he's building Cyber Security Technologies, and his whole thesis is you have to share. So the question is, how do you share and lock stuff down at the same time when you have ah, multi sided marketplace in space? You know, suppliers, users, systems. This is a huge security challenge. What's your reaction to this? Because we're intersecting all these things space and cybersecurity. It's just not easy. What's your reaction? >>Absolutely, Absolutely. And what I would say in response to that first would be that security really needs to be baked into the onset of how we develop and implement and deploy our space systems. Um, there's there's always going to be the need to collect and share data across multiple entities, particularly when we're changing scientific data with our mission partners. Eso with that necessitates that we have a security view from the onset, right? We have a system spaces, and they're designed to share information across the world. How do we make sure that those, uh, those other those communication channels so secure, free from interception free from disruption? So they're really done? That necessitates of our space leaders in our cyber leaders to be joining the hip about how to secure our space systems, and the communications there in Clinton brought up a really good point of. And then I'm gonna elaborate on a little bit, just toe invite a little bit more context and talk about some the complexities and challenges we face with this advent of new space and and all of our great commercial partners coming into therefore way, that's going to present a very significant supply chain risk management problems that we have to get our hands around as well. But we have these manufacturers developing these highly specialized components for the space instruments, Um, that as it stands right now, it's very little oversight And how those things air produced, manufactured, put into the space systems communication channels that they use ports protocols that they use to communicate. And that's gonna be a significant challenge for us to get get our hands around. So again, cybersecurity being brought in. And the very onset of these development thes thes decisions in these life cycles was certainly put us in a best better position to secure that data in our in our space missions. >>Yeah, E just pick up on that. You don't mind? Preston made such a really good point there. But you have to bake security in up front, and you know there's a challenge and there's an opportunity, you know, with a lot of our systems today. It was built in a pre cyber security environment, especially our government systems that were built, you know, in many cases 10 years ago, 15 years ago are still on orbit today, and we're thankful that they are. But as we look at this new environment and we understand the threats, if we bake cybersecurity in upfront weaken balance that open application versus the risk a long as we do it up front. And you know, that's one of the reasons that our company developed what we call govcloud, which is a secure cloud, that we use thio to manage data that our customers who want to do work with the federal government or other governments or the national security apparatus. They can operate in that space with the built in and baked in cybersecurity protocols. We have a secret region that both can handle secret and top secret information for the same reasons. But when you bake security into the upfront applications, that really allows you to balance that risk between making it available and accessible in sort of an open architecture way. But being sure that it's protected through things like ITAR certifications and fed ramp, uh, another ice T certifications that we have in place. So that's just a really important point. >>Let's stay high level for a man. You mentioned a little bit of those those govcloud, which made me think about you know, the tactical edge in the military analogy, but also with space similar theater. It's just another theater and you want to stand stuff up. Whether it's communications and have facilities, you gotta do it rapidly, and you gotta do it in a very agile, secure, I high availability secure way. So it's not the old waterfall planning. You gotta be fast is different. Cloud does things different? How do you talk to the young people out there, whether it's apparent with with kids in elementary and middle school to high school, college grad level or someone in the workforce? Because there are no previous jobs, that kind of map to the needs out there because you're talking about new skills, you could be an archaeologist and be the best cyber security guru on the planet. You don't have to have that. There's no degree for what, what we're talking about here. This >>is >>the big confusion around education. I mean, you gotta you like math and you could code you can Anything who wants to comment on that? Because I think this >>is the core issue. I'll say there are more and more programs growing around that educational need, and I could talk about a few things we're doing to, but I just wanna make an observation about what you just said about the need. And how do you get kids involved and interested? Interestingly, I think it's already happening, right. The good news. We're already developing that affinity. My four year old granddaughter can walk over, pick up my iPad, turn it on. Somehow she knows my account information, gets into my account, pulls up in application, starts playing a game. All before I really even realized she had my iPad. I mean, when when kids grow up on the cloud and in technology, it creates that natural proficiency. I think what we have to do is take that natural interest and give them the skill set the tools and capabilities that go with it so that we're managing, you know, the the interest with the technical skills. >>And also, like a fast I mean, just the the hackers are getting educated. Justus fast. Steve. I mean e mean Bucky. What do you do here? You CIt's the classic. Just keep chasing skills. I mean, there are new skills. What are some of those skills? >>Why would I amplify eloquent? Just said, First of all, the, uh, you know, cyber is one of those technology areas where commercial side not not the government is really kind of leading away and does a significant amount of research and development. Ah, billions of dollars are spent every year Thio to evolve new capabilities. And a lot of those companies are, you know, operated and and in some cases, led by folks in their early twenties. So the S O. This is definitely an era and a generation that is really poised in position. Well, uh, Thio take on this challenge. There's some unique aspects to space. Once we deploy a system, uh, it will be able to give me hard to service it, and we're developing capabilities now so that we could go up and and do system upgrades. But that's not a normal thing in space that just because the the technical means isn't there yet. So having software to find capabilities, I's gonna be really paramount being able to dio unique things. The cloud is huge. The cloud is centric to this or architectural, and it's kind of funny because d o d we joke because we just discovered the cloud, you know, a couple years ago. But the club has been around for a while and, uh, and it's going to give us scalability on and the growth potential for doing amazing things with a big Data Analytics. But as Preston said, it's all for not if if we can't trust the data that we receive. And so one of the concepts for future architectures is to evolve into a zero trust model where we trust nothing. We verify and authenticate everyone. And, uh, and that's that's probably a good, uh, point of departure as we look forward into our cybersecurity for space systems into the future. >>Block everyone. Preston. Your reaction to all this gaps, skills, What's needed. I mean it Z everyone's trying to squint through this >>absolutely. And I wanna want to shift gears a little bit and talk about the space agencies and organizations that are responsible for deploying these spaces into submission. So what is gonna take in this new era on, and what do we need from the workforce to be responsive to the challenges that we're seeing? First thing that comes to mind is creating a culture of security throughout aerospace right and ensuring that Azzawi mentioned before security isn't an afterthought. It's sort of baked into our models that we deploy and our rhetoric as well, right? And because again we hire our spaces in years to do it very highly. Specialized thing for a highly specialized, uh, it's topic. Our effort, if we start to incorporate rhetorically the importance of cybersecurity two missing success and missing assurance that's going to lend itself toe having more, more prepared on more capable system engineers that will be able to respond to the threats accordingly. Traditionally, what we see in organizational models it's that there's a cyber security team that's responsible for the for the whole kit kaboodle across the entire infrastructure, from enterprise systems to specialize, specialize, space systems and then a small pocket of spaces, years that that that are really there to perform their tasks on space systems. We really need to bridge that gap. We need to think about cybersecurity holistically, the skills that are necessary for your enterprise. I t security teams need to be the same skills that we need to look for for our system engineers on the flight side. So organizationally we need we need to address that issue and approach it, um todo responsive to the challenges we see our our space systems, >>new space, new culture, new skills. One of the things I want to bring up is looking for success formulas. You know, one of the things we've been seeing in the past 10 years of doing the Cube, which is, you know, we've been called the ESPN of Tech is that there's been kind of like a game ification. I want to. I don't wanna say sports because sports is different, but you're seeing robotics clubs pop up in some schools. It's like a varsity sport you're seeing, you know, twitch and you've got gamers out there, so you're seeing fun built into it. I think Cal Poly's got some challenges going on there, and then scholarships air behind it. So it's almost as if, you know, rather than going to a private sports training to get that scholarship, that never happens. There's so many more scholarship opportunities for are not scholarship, but just job opportunities and even scholarships we've covered as part of this conference. Uh, it's a whole new world of culture. It's much different than when I grew up, which was you know, you got math, science and English. You did >>it >>and you went into your track. Anyone want to comment on this new culture? Because I do believe that there is some new patterns emerging and some best practices anyone share any? >>Yeah, I do, because as you talked about robotics clubs and that sort of things, but those were great and I'm glad those air happening. And that's generating the interest, right? The whole gaming culture generating interest Robotic generates a lot of interest. Space right has captured the American in the world attention as well, with some recent NASA activities and all for the right reasons. But it's again, it's about taking that interested in providing the right skills along the way. So I'll tell you a couple of things. We're doing it a w s that we found success with. The first one is a program called A W s Academy. And this is where we have developed a cloud, uh, program a cloud certification. This is ah, cloud curriculum, if you will, and it's free and it's ready to teach. Our experts have developed this and we're ready to report it to a two year and four year colleges that they can use is part of the curriculum free of charge. And so we're seeing some real value there. And in fact, the governor's in Utah and Arizona recently adopted this program for their two year schools statewide again, where it's already to teach curriculum built by some of the best experts in the industry s so that we can try to get that skills to the people that are interested. We have another program called A W s educate, and this is for students to. But the idea behind this is we have 12 cracks and you can get up to 50 hours of free training that lead to A W s certification, that sort of thing. And then what's really interesting about that is all of our partners around the world that have tied into this program we manage what we call it ws educate Job board. And so if you have completed this educate program now, you can go to that job board and be linked directly with companies that want people with those skills we just helped you get. And it's a perfect match in a perfect marriage there. That one other piece real quickly that we're proud of is the aws Uh restart program. And that's where people who are unemployed, underemployed or transitioning can can go online. Self paced. We have over 500 courses they can take to try to develop those initial skills and get into the industry. And that's been very popular, too, So that those air a couple of things we're really trying to lean into >>anyone else want to react. Thio that question patterns success, best practices, new culture. >>I'd like Thio. The the wonderful thing about what you just touched on is problem solving, right, And there's some very, very good methodologies that are being taught in the universities and through programs like Hacking for Defense, which is sponsored by the National Security Innovation Network, a component of the I you where I work but the But whether you're using a lien methodologies or design school principals or any other method, the thing that's wonderful right now and not just, uh, where I work at the U. The Space force is doing this is well, but we're putting the problem out there for innovators to tackle, And so, rather than be prescriptive of the solutions that we want to procure, we want we want the best minds at all levels to be able to work on the problem. Uh, look at how they can leverage other commercial solutions infrastructure partnerships, uh, Thio to come up with a solution that we can that we can rapidly employ and scale. And if it's a dual use solution or whether it's, uh, civil military or or commercial, uh, in any of the other government solutions. Uh, that's really the best win for for the nation, because that commercial capability again allows us to scale globally and share those best practices with all of our friends and allies. People who share our values >>win win to this commercial. There's a business model potential financial benefits as well. Societal impact Preston. I want to come to you, JPL, NASA. I mean, you work in one of the most awesome places and you know, to me, you know, if you said to me, Hey, John, come working JP like I'm not smart enough to go there like I mean, like, it's a pretty It's intimidating, it might seem >>share folks out there, >>they can get there. I mean, it's you can get there if you have the right skills. I mean I'm just making that up. But, I mean, it is known to be super smart And is it attainable? So share your thoughts on this new culture because you could get the skills to get there. What's your take on all this >>s a bucket. Just missing something that really resonated with me, right? It's do it your love office. So if you put on the front engineer, the first thing you're gonna try to do is pick it apart. Be innovative, be creative and ways to solve that issue. And it has been really encouraging to me to see the ground welcome support an engagement that we've seen across our system. Engineers in space. I love space partners. A tackling the problem of cyber. Now that they know the West at risk on some of these cyber security threats that that they're facing with our space systems, they definitely want to be involved. They want to take the lead. They want to figure things out. They wanna be innovative and creative in that problem solving eso jpl We're doing a few things. Thio Raise the awareness Onda create a culture of security. Andi also create cyber advocates, cybersecurity advocates across our space engineers. We host events like hacked the lad, for example, and forgive me. Take a pause to think about the worst case scenarios that could that could result from that. But it certainly invites a culture of creative problem solving. Um, this is something that that kids really enjoy that are system engineers really enjoyed being a part off. Um, it's something that's new refreshing to them. Eso we were doing things like hosting a monthly cybersecurity advocacy group. When we talk about some of the cyber landscape of our space systems and invite our engineers into the conversation, we do outweighs programs specifically designed to to capture, um, our young folks, uh, young engineers to deceive. They would be interested and show them what this type of security has to offer by ways of data Analytic, since the engineering and those have been really, really successful identifying and bringing in new talent to address the skill gaps. >>Steve, I want to ask you about the d. O. D. You mentioned some of the commercial things. How are you guys engaging the commercial to solve the space issue? Because, um, the normalization in the economy with GPS just seeing spaces impacts everybody's lives. We we know that, um, it's been talked about. And and there's many, many examples. How are you guys the D o. D. From a security standpoint and or just from an advancement innovation standpoint, engaging with commercials, commercial entities and commercial folks? >>Well, I'll throw. I'll throw a, uh, I'll throw ah, compliment to Clint because he did such an outstanding job. The space forces already oriented, uh, towards ah, commercial where it's appropriate and extending the arms. Leveraging the half works on the Space Enterprise Consortium and other tools that allow for the entrepreneurs in the space force Thio work with their counterparts in a commercial community. And you see this with the, uh, you know, leveraging space X away to, uh, small companies who are doing extraordinary things to help build space situational awareness and, uh, s So it's it's the people who make this all happen. And what we do at at the D. O. D level, uh, work at the Office of Secretary defense level is we wanna make sure that they have the right tools to be able to do that in a way that allows these commercial companies to work with in this case of a space force or with cyber command and ways that doesn't redefine that. The nature of the company we want we want We want commercial companies to have, ah, great experience working with d o d. And we want d o d toe have the similar experience working, working with a commercial community, and and we actually work interagency projects to So you're going to see, uh, General Raymond, uh, hey, just recently signed an agreement with the NASA Esa, you're gonna see interagency collaborations on space that will include commercial capabilities as well. So when we speak as one government were not. You know, we're one voice, and that's gonna be tremendous, because if you're a commercial company on you can you can develop a capability that solves problems across the entire space enterprise on the government side. How great is that, Right. That's a scaling. Your solution, gentlemen. Let >>me pick you back on that, if you don't mind. I'm really excited about that. I mentioned new space, and Bucky talked about that too. You know, I've been flying satellites for 30 years, and there was a time where you know the U. S. Government national security. We wouldn't let anybody else look at him. Touch him. Plug into, um, anything else, right. And that probably worked at the time. >>But >>the world has changed. And more >>importantly, >>um, there is commercial technology and capability available today, and there's no way the U. S government or national security that national Intel community can afford economically >>to >>fund all that investment solely anymore. We don't have the manpower to do it anymore. So we have this perfect marriage of a burgeoning industry that has capabilities and it has re sources. And it has trained manpower. And we are seeing whether it's US Space Force, whether it's the intelligence community, whether it's NASA, we're seeing that opened up to commercial providers more than I've ever seen in my career. And I can tell you the customers I work with every day in a W s. We're building an entire ecosystem now that they understand how they can plug in and participate in that, and we're just seeing growth. But more importantly, we're seeing advanced capability at cheaper cost because of that hybrid model. So that really is exciting. >>Preston. You know you mentioned earlier supply chain. I don't think I think you didn't use the word supply chain. Maybe you did. But you know about the components. Um, you start opening things up and and your what you said baking it in to the beginning, which is well known. Uh, premise. It's complicated. So take me through again, Like how this all gonna work securely because And what's needed for skill sets because, you know, you're gonna open. You got open source software, which again, that's open. We live in a free society in the United States of America, so we can't lock everything down. You got components that are gonna be built anywhere all around the world from vendors that aren't just a certified >>or maybe >>certified. Um, it's pretty crazy. So just weigh in on this key point because I think Clint has it right. And but that's gonna be solved. What's your view on this? >>Absolutely. And I think it really, really start a top, right? And if you look back, you know, across, um in this country, particularly, you take the financial industry, for example, when when that was a burgeoning industry, what had to happen to ensure that across the board. Um, you know, your your finances were protected these way. Implemented regulations from the top, right? Yeah. And same thing with our health care industry. We implemented regulations, and I believe that's the same approach we're gonna need to take with our space systems in our space >>industry >>without being too directive or prescriptive. Instance she ating a core set of principles across the board for our manufacturers of space instruments for deployment and development of space systems on for how space data and scientific data is passed back and forth. Eso really? We're gonna need to take this. Ah, holistic approach. Thio, how we address this issue with cyber security is not gonna be easy. It's gonna be very challenging, but we need to set the guard rails for exactly what goes into our space systems, how they operate and how they communicate. >>Alright, so let's tie this back to the theme, um, Steve and Clint, because this is all about workforce gaps, opportunities. Um, Steve, you mentioned software defined. You can't do break fix in space. You can't just send a technician up in the space to fix a component. You gotta be software defined. We're talking about holistic approach, about commercial talk about business model technology with software and policy. We need people to think through, like you know. What the hell are you gonna do here, right? Do you just noticed road at the side of the road to drive on? There's no rules of engagement. So what I'm seeing is certainly software Check. If you wanna have a job for the next millennial software policy who solves two problems, what does freedom looked like in space Congestion Contention and then, obviously, business model. Can you guys comment on these three areas? Do you agree? And what specific person might be studying in grad school or undergraduate or in high school saying, Hey, I'm not a techie, but they can contribute your thoughts. I'll >>start off with, uh, speak on on behalf of the government today. I would just say that as policy goes, we need to definitely make sure that we're looking towards the future. Ah, lot of our policy was established in the past under different conditions, and, uh, and if there's anything that you cannot say today is that space is the same as it was even 10 years ago. So the so It's really important that our policy evolves and recognizes that that technology is going to enable not just a new ways of doing things, but also force us to maybe change or or get rid of obsolete policies that will inhibit our ability to innovate and grow and maintain peace with with a rapid, evolving threat. The for the for the audience today, Uh, you know, you want some job assurance, cybersecurity and space it's gonna be It's gonna be an unbelievable, uh, next, uh, few decades and I couldn't think of a more exciting for people to get into because, you know, spaces Ah, harsh environment. We're gonna have a hard time just dud being able differentiate, you know, anomalies that occur just because of the environment versus something that's being hacked. And so JPL has been doing this for years on they have Cem Cem great approaches, but but this is this is gonna be important if you put humans on the moon and you're going to sustain them there. Those life support systems are gonna be using, you know, state of the art computer technology, and which means, is also vulnerable. And so eso the consequences of us not being prepared? Uh, not just from our national security standpoint, but from our space exploration and our commercial, uh, economic growth in space over the long term all gonna be hinged on this cyber security environment. >>Clint, your thoughts on this too ill to get. >>Yeah. So I certainly agree with Bucky. But you said something a moment ago that Bucky was talking about as well. But that's the idea that you know in space, you can't just reach out and touch the satellite and do maintenance on the satellite the way you can't a car or a tank or a plane or a ship or something like that. And that is true. However, right, comma, I want to point out. You know, the satellite servicing industry is starting to develop where they're looking at robotic techniques in Cape abilities to go up in services satellite on orbit. And that's very promising off course. You got to think through the security policy that goes with that, of course. But the other thing that's really exciting is with artificial intelligence and machine learning and edge computing and database analytics and all those things that right on the cloud. You may not even need to send a robotic vehicle to a satellite, right? If you can upload and download software defined, fill in the blank right, maybe even fundamentally changing the mission package or the persona, if you will, of the satellite or the spacecraft. And that's really exciting to, ah, lot >>of >>security policy that you've gotta work through. But again, the cloud just opens up so many opportunities to continue to push the boundaries. You know, on the AWS team, the aerospace and satellite team, which is, you know, the new team that I'm leading. Now our motto is to the stars through the cloud. And there are just so many exciting opportunities right for for all those capabilities that I just mentioned to the stars through the cloud >>President, your thoughts on this? >>Yes, eso won >>a >>little bit of time talking about some of the business model implications and some of the challenges that exists there. Um, in my experience, we're still working through a bit of a language barrier of how we define risk management for our space systems. Traditionally traditionally risk management models is it is very clear what poses a risk to a flight mission. Our space mission, our space system. Um, and we're still finding ways to communicate cyber risk in the same terms that are system engineers are space engineers have traditionally understood. Um, this is a bit of a qualitative versus quantitative, a language barrier. But however adopting a risk management model that includes cybersecurity, a za way to express wish risk to miss the success, I think I think it would be a very good thing is something that that we have been focused on the J. P o as we Aziz, we look at the 34 years beyond. How do >>we >>risk that gap and not only skills but communication of cyber risk and the way that our space engineers and our project engineers and a space system managers understand >>Clinton, like Thio talk about space Force because this is the most popular new thing. It's only a couple of nine months in roughly not even a year, uh, already changing involving based on some of the reporting we've done even here at this symposium and on the Internet. Um, you know, when I was growing up, you know, I wasn't there when JFK said, you know, we're gonna get to the moon. I was born in the sixties, so, you know, when I was graduating my degree, you know, Draper Labs, Lincoln Lab, JPL, their pipeline and people wasn't like a surge of job openings. Um, so this kind of this new space new space race, you know, Kennedy also said that Torch has been passed to a new generation of Americans. So in a way that's happening right now with space force. A new generation is here is a digital generation. It's multi disciplinary generation. Could you take a minute and share, uh, for for our audience? And here at this symposium, um, the mission of Space Force and where you see it going because this truly is different. And I think anyone who's young e I mean, you know, if this was happening when I was in college would be like dropping everything. I'm in there, I think, cause there's so many areas thio jump into, um, it's >>intellectually challenging. >>It's intoxicating in some level. So can you share your thoughts? >>Yeah. Happy to do that. Of course. I I need to remind everybody that as a week ago I'm formally retired. So I'm not an official spokesman for US forces. But with that, you know, it said I did spend the last 18 months planning for it, designing and standing it up. And I'll tell you what's really exciting is you know, the commander of, uh, US Base Force General J. Raymond, who's the right leader at the right time. No question in my >>mind. But >>he said, I want to stand up the Space Force as the first fully digital service in the United States. Right? So he is trying >>to bake >>cloud baked cybersecurity, baked digital transformational processes and everything we did. And that was a guidance he gave us every day, every day. When we rolled in. He said, Remember, guys, I don't wanna be the same. I don't wanna be stale. I want new thinking, new capabilities and I want it all to be digital on. That's one of the reasons When we brought the first wave of people into the space force, we brought in space operations, right. People like me that flew satellites and launch rockets, we brought in cyber space experts, and we brought in intelligence experts. Those were the first three waves of people because of that, you know, perfect synergy between space and cyber and intel all wrapped in >>it. >>And so that was really, really smart. The other thing I'll say just about, you know, Kennedy's work. We're going to get to the moon. So here we are. Now we're going back to the Moon Project Artemus that NASA is working next man first woman on the moon by 2024 is the plan and >>then >>with designs to put a permanent presence on the moon and then lean off to march. So there was a lot to get excited about. I will tell you, as we were taking applications and looking at rounding out filling out the village in the U. S. Space Force, we were overwhelmed with the number of people that wanted, and that was a really, really good things. So they're off to a good start, and they're just gonna accomplishment major things. I know for sure. >>Preston, your thoughts on this new generation people out there were like I could get into this. This is a path. What's your what's your opinion on this? And what's your >>E could, uh, you so bold as to say >>that >>I feel like I'm a part of that new generation eso I grew up very much into space. Uh, looking at, um, listen to my, uh, folks I looked up to like Carl Sagan. Like like Neil Tyson. DeGrasse on did really feeling affinity for what What this country has done is for is a space program are focused on space exploration on bond. Through that, I got into our security, as it means from the military. And I just because I feel so fortunate that I could merge both of those worlds because of because of the generational, um, tailoring that we do thio promote space exploration and also the advent of cybersecurity expertise that is needed in this country. I feel like that. We are We are seeing a conversions of this too. I see a lot of young people really getting into space exploration. I see a lot of young people as well. Um uh, gravitating toward cybersecurity as a as a course of study. And to see those two worlds colliding and converse is something that's very near and dear to me. And again, I I feel like I'm a byproduct of that conversion, which is which, Really, Bothwell for space security in the future, >>we'll your great leader and inspiration. Certainly. Senior person as well. Congratulations, Steve. You know, young people motivational. I mean, get going. Get off the sidelines. Jump in Water is fine, Right? Come on in. What's your view on motivating the young workforce out there and anyone thinking about applying their skills on bringing something to the table? >>Well, look at the options today. You have civil space President represents you have military space. Uh, you have commercial space on and even, you know, in academia, the research, the potential as a as an aspiring cyber professional. All of you should be thinking about when we when we When? When we first invented the orbit, which eventually became the Internet, Uh, on Lee, we were, uh if all we had the insight to think Well, geez, you know whether the security implications 2030 years from now of this thing scaling on growing and I think was really good about today's era. Especially as Clint said, because we were building this space infrastructure with a cyber professionals at ground zero on dso the So the opportunity there is to look out into the future and say we're not just trying to secure independent her systems today and assure the free for all of of information for commerce. You know, the GPS signal, Uh, is Justus much in need of protection as anything else tied to our economy, But the would have fantastic mission. And you could do that. Uh, here on the ground. You could do it, uh, at a great companies like Amazon Web services. But you can also one of these states. Perhaps we go and be part of that contingency that goes and does the, uh, the se's oh job that that president has on the moon or on Mars and, uh, space will space will get boring within a generation or two because they'll just be seen as one continuum of everything we have here on Earth. And, uh, and that would be after our time. But in the meantime, is a very exciting place to be. And I know if I was in in my twenties, I wanna be, uh, jumping in with both feet into it. >>Yeah, great stuff. I mean, I think space is gonna be around for a long long time. It's super exciting and cybersecurity making it secure. And there's so many areas defeating on. Gentlemen, thank you very much for your awesome insight. Great panel. Um, great inspiration. Every one of you guys. Thank you very much for for sharing for the space and cybersecurity symposium. Appreciate it. Thank you very much. >>Thanks, John. Thank you. Thank you. Okay, >>I'm >>John for your host for the Space and Cybersecurity Symposium. Thanks for watching.

>> theCUBE's live coverage is made possible by funding from Dell Technologies: "Creating technologies that drive human progress." >> Good late afternoon from Barcelona, Spain at the Theater of Barcelona. It's Lisa Martin and Dave Nicholson of "theCUBE" covering MWC23. This is our third day of continuous wall-to-wall coverage on theCUBE. And you know we're going to be here tomorrow as well. We've been having some amazing conversations about the ecosystem. And we're going to continue those conversations next. Honore Labourdette is here, the VP global partner, Ecosystem Success Team, Telco Media and Entertainment at Red Hat. And Tony Jeffries joins us as well, a Senior Director of Product Management, Telecom Systems Business at Dell. Welcome to the theCUBE. >> Thank you. >> Thank you. >> Great to have both of you here. So we're going to be talking about the evolution of the telecom stack. We've been talking a lot about disaggregation the last couple of days. Honore, starting with you, talk about the evolution of the telecom stock. You were saying before we went live this is your 15th at least MWC. So you've seen a lot of evolution, but what are some of the things you're seeing right now? >> Well, I think the interesting thing about disaggregation, which is a key topic, right? 'Cause it's so relative to 5G and the 5G core and the benefits and the features of 5G core around disaggregation. But one thing we have to remember, when you disaggregate, you separate things. You have to bring those things back together again in a different way. And that's predominantly what we're doing in our partnership with Dell, is we're bringing those disaggregated components back together in a cohesive way that takes advantage of the new technology, at the same time taking out the complexity and making it easier for our Telco customers to deploy and to scale and to get much more, accelerate the time to revenue. So the trend now is, what we're seeing is two things I would say. One is how do we solve for the complexity with the disaggregation? And how do we leverage the ecosystem as a partner in order to help solve for some of those challenges? >> Tony, jump on in, talk about what you guys announced last week, Dell and Red Hat, and how it's addressing the complexities that Honore was saying, "Hey, they're there." >> Yeah. You know, our customers, our operators are saying, "Hey, I want disaggregation." "I want competition in the market." But at the same time who's going to support all this disaggregation, right? And so at the end of the day, there's going to be an operator that's going to have to figure this out. They're going to have an SLA that they're going to have to meet. And so they're going to want to go with a best-in-class partner with Red Hat and Dell, in terms of our infrastructure and their software together as one combined engineered system. And that's what we call a Dell Telecom infrastructure block for Red Hat. And so at the end of the day, things may go wrong, and if they do, who are they going to call for that support? And that's also really a key element of an engineered system, is this experience that they get both with Red Hat and with Dell together supporting the customer as one. Which is really important to solve this disaggregated problem that can arise from a disaggregated open network situation, yeah. >> So what is the market, the go to market motion look like? People have loyalties in the IT space to technologies that they've embraced and been successful with for years and years. So you have folks in the marketplace who are diehard, you know, dyed red, Red Hat folks. Is it primarily a pull from them? How does that work? How do you approach that to your, what are your end user joint customers? What does that look like from your perspective? >> Sure, well, interestingly enough both Red Hat and Dell have been in the marketplace for a very long time, right? So we do have the brand with those Telco customers for these solutions. What we're seeing with this solution is, it's an emerging market. It's an emerging market for a new technology. So there's an opportunity for both Red Hat and Dell together to leverage our brands with those customers with no friction in the marketplace as we go to market together. So our field sales teams will be motivated to, you know, take advantage of the solution for their customers, as will the Dell team. And I'll let Tony speak to the Dell, go to market. >> Yeah. You know, so we really co-sell together, right? We're the key partners. Dell will end up fulfilling that order, right? We send these engineered systems through our factories and we send that out either directly to a customer or to a OTEL lab, like an intermediate lab where we can further refine and customize that offer for that particular customer. And so we got a lot of options there, but we're essentially co-selling. And Dell is fulfilling that from an infrastructure perspective, putting Red Hat software on top and the licensing for that support. So it's a really good mix. >> And I think, if I may, one of the key differentiators is the actual capabilities that we're bringing together inside of this pre-integrated solution. So it includes the Red Hat OpenShift which is the container software, but we also add our advanced cluster management as well as our Ansible automation. And then Dell adds their orchestration capability along with the features and functionalities of the platform. And we put that together and we offer capability, remote automation orchestration and management capabilities that again reduces the operating expense, reduces the complexity, allows for easy scale. So it's, you know, certainly it's all about the partnership but it's also the capabilities of the combined technology. >> I was just going to ask about some of the numbers, and you mentioned some of them. Reduction of TCO I imagine is also a big capability that this solution enables besides reducing OpEx. Talk about the TCO reduction. 'Cause I know there's some numbers there that Dell and Red Hat have already delivered to the market. >> Yeah. You know, so these infrastructure blocks are designed specifically for Core, or for RAN, or for the Edge. We're starting out initially in the Core, but we've done some market research with a company called ACG. And ACG has looked at day zero, day one and day two TCO, FTE hours saved. And we're looking at over 40 to 50% TCO savings over you know, five year period, which is quite significant in terms of cost savings at a TCO level. But also we have a lot of numbers around power consumption and savings around power consumption. But also just that experience for our operator that says, hey, I'm going to go to one company to get the best in class from Red Hat and Dell together. That saves a lot of time in procurement and that entire ordering process as well. So you get a lot of savings that aren't exactly seen in the FTE hours around TCO, but just in that overall experience by talking to one company to get the best of both from both Red Hat and Dell together. >> I think the comic book character Charlie Brown once said, "The most discouraging thing in the world is having a lot of potential." (laughing) >> Right. >> And so when we talk about disaggregating and then reaggregating or reintegrating, that means choice. >> Tony: Yeah. >> How does an operator approach making that choice? Because, yeah, it sounds great. We have this integration lab and you have all these choices. Well, how do I decide, how does a person decide? This is a question for Honore from a Red Hat perspective, what's the secret sauce that you believe differentiates the Red Hat-infused stack versus some other assemblage of gear? >> Well, there's a couple of key characteristics, and the one that I think is most prevalent is that we're open, right? So "open" is in Red Hat's DNA because we're an open source technology company, and with that open source technology and that open platform, our customers can now add workloads. They have options to choose the workloads that they want to run on that open source platform. As they choose those workloads, they can be confident that those workloads have been certified and validated on our platform because we have a very robust ecosystem of ISVs that have already completed that process with open source, with Red Hat OpenShift. So then we take the Red Hat OpenShift and we put it on the Dell platform, which is market leader platform, right? Combine those two things, the customers can be confident that they can put those workloads on the combined platform that we're offering and that those workloads would run. So again, it goes back to making it simpler, making it easy to procure, easy to run workloads, easy to deploy, easy to operate. And all of that of course equates to saving time always equates to saving money. >> Yeah. Absolutely. >> Oh, I thought you wanted to continue. >> No, I think Honore sort of, she nailed it. You know, Red Hat is so dominant in 5G, and what they're doing in the market, especially in the Core and where we're going into the RAN, you know, next steps are to validate those workloads, those workload vendors on top of a stack. And the Red Hat leader in the Core is key, right? It's instant credibility in the core market. And so that's one of the reasons why we, Dell, want to partner with with Red Hat for the core market and beyond. We're going to be looking at not only Core but moving into RAN very soon. But then we do, we take that validated workload on top of that to optimize that workload and then be able to instantiate that in the core and the RAN. It's just a really streamlined, good experience for our operators. At the end of the day, we want happy customers in between our mutual customer base. And that's what you get whenever you do that combined stack together. >> Were operators, any operators, and you don't have to mention them by name, involved in the evolution of the infra blocks? I'm just curious how involved they were in helping to co-develop this. I imagine they were to some degree. >> Yeah, I could take that one. So, in doing so, yeah, we can't be myopic and just assume that we nailed it the first time, right? So yeah, we do work with partners all the way up and down the stack. A lot of our engineering work with Red Hat also brings in customer experience that is key to ensure that you're building and designing the right architecture for the Core. I would like to use the names, I don't know if I should, but a lot of those names are big names that are leaders in our industry. But yeah, their footprints, their fingerprints are all over those design best practices, those architectural designs that we build together. And then we further that by doing those validated workloads on top of that. So just to really prove the point that it's optimized for the Core, RAN, Edge kind of workload. >> And it's a huge added value for Red Hat to have a partner like Dell who can take all of those components, take the workload, take the Red Hat software, put it on the platform, and deliver that out to the customers. That's really, you know, a key part of the partnership and the value of the partnership because nobody really does that better than Dell. That center of excellence around delivery and support. >> Can you share any feedback from any of those nameless operators in terms of... I'm even kind of wondering what the catalyst was for the infra block. Was it operators saying, "Ah, we have these challenges here"? Was it the evolution of the Telco stack and Dell said, "We can come in with Red Hat and solve this problem"? And what's been some of their feedback? >> Yeah, it really comes down to what Honore said about, okay, you know, when we are looking at day zero, which is primarily your design, how much time savings can we do by creating that stack for them, right? We have industry experts designing that Core stack that's optimized for different levels of spectrum. When we do that we save a lot of time in terms of FTE hours for our architects, our operators, and then it goes into day one, right? Which is the deployment aspect for saving tons of hours for our operators by being able to deploy this. Speed to market is key. That ultimately ends up in, you know, faster time to revenue for our customers, right? So it's, when they see that we've already done the pre-work that they don't have to, that's what really resonates for them in terms of that, yeah. >> Honore, Lisa and I happen to be veterans of the Cloud native space, and what we heard from a lot of the folks in that ecosystem is that there is a massive hunger for developers to be able to deploy and manage and orchestrate environments that consist of Cloud native application infrastructure, microservices. >> Right. >> What we've heard here is that 5G equals Cloud native application stacks. Is that a fair assessment of the environment? And what are you seeing from a supply and demand for that kind of labor perspective? Is there still a hunger for those folks who develop in that space? >> Well, there is, because the very nature of an open source, Kubernetes-based container platform, which is what OpenShift is, the very nature of it is to open up that code so that developers can have access to the code to develop the workloads to the platform, right? And so, again, the combination of bringing together the Dell infrastructure with the Red Hat software, it doesn't change anything. The developer, the development community still has access to that same container platform to develop to, you know, Cloud native types of application. And you know, OpenShift is Red Hat's hybrid Cloud platform. So it runs on-prem, it runs in the public Cloud, it runs at the edge, it runs at the far edge. So any of the development community that's trying to develop Cloud native applications can develop it on this platform as they would if they were developing on an OpenShift platform in the public Cloud. >> So in "The Graduate", the advice to the graduate was, "Plastics." Plastics. As someone who has more children than I can remember, I forget how many kids I have. >> Four. >> That's right, I have four. That's right. (laughing) Three in college and grad school already at this point. Cloud native, I don't know. Kubernetes definitely a field that's going to, it's got some legs? >> Yes. >> Okay. So I can get 'em off my payroll quickly. >> Honore: Yes, yes. (laughing) >> Okay, good to know. Good to know. Any thoughts on that open Cloud native world? >> You know, there's so many changes that's going to happen in Kubernetes and services that you got to be able to update quickly. CICD, obviously the topic is huge. How quickly can we keep these systems up to date with new releases, changes? That's a great thing about an engineered system is that we do provide that lifecycle management for three to five years through this engagement with our customers. So we're constantly keeping them up with the latest and the greatest. >> David: Well do those customers have that expertise in-house, though? Do they have that now? Or is this a seismic cultural shift in those environments? >> Well, you know, they do have a lot of that experience, but it takes a lot of that time, and we're taking that off of their plate and putting that within us on our system, within our engineered system, and doing that automatically for them. And so they don't have to check in and try to understand what the release certification matrix is. Every quarter we're providing that to them. We're communicating out to the operator, telling them what's coming up latest and greatest, not only in terms of the software but the hardware and how to optimize it all together. That's the beauty of these systems. These are five year relationships with our operators that we're providing that lifecycle management end to end, for years to come. >> Lisa: So last question. You talked about joint GTM availability. When can operators get their hands on this? >> Yes. Yes. It's currently slated for early September release. >> Lisa: Awesome. So sometime this year? >> Yes. >> Well guys, thank you so much for talking with us today about Dell, Red Hat, what you're doing to really help evolve the telecom stack. We appreciate it. Next time come back with a customer, we can dig into it. That'd be fun. >> We sure will, absolutely. That may happen today actually, a little bit later. Not to let the cat out the bag, but good news. >> All right, well, geez, you're going to want to stick around. Thank you so much for your time. For our guests and for Dave Nicholson. This is Lisa Martin of theCUBE at MWC23 from Barcelona, Spain. We'll be back after a short break. (calm music)

(gentle music) >> Welcome back to our coverage here on theCUBE of AWS re:Invent 22. We are on day three, starting to wind down, but still a lot of exciting topics to cover here on the AWS Global Showcase, part of the startup program there at AWS. Joining us now, two representatives from LTI Mindtree. You say LTI Mindtree? I thought they were two different companies. Well, they're actually one and the same. Been together just a mere two weeks now. We'll hear more about that from Sid Bohra, who is the Chief Business Officer at LTI Mindtree and Ashish Varerkar, who is the Vice President of Cloud Success at LTI Mindtree. Gentlemen, thanks for being with us here on theCUBE. >> Pleasures all ours. >> Thank you. >> And congratulations. So two weeks in the making in its infancy, still in the honeymoon period, but how's the two weeks been? Everything all right? >> Well, two weeks have been very exciting. >> I'll bet. >> Well, I would say the period prior to that was just as exciting as you can imagine. >> John: Oh, sure. And we are super excited about what the future holds for this company because we truly believe that we have a remarkable opportunity to create value for our clients as one company. >> Well let's talk about LTI Mind tree then a little bit. Ashish, I'll let you carry the ball on this. Tell us about your services, about your core focus, and about those opportunities that Siddharth was just telling us about. >> So I think with the two companies coming together, we have a larger opportunity to like go to market with our end to end business transformation services and leveraging cloud platforms, right? So, and that's what we do. My responsibility particularly is to see to it that what customers are deploying on cloud is aligned to their business outcomes and then take it forward from there. >> Yeah, Vice President of Cloud Success, that gives you a lot of runway, right? Does it not? I mean, how do you define success in the cloud? Because there are a lot of different areas of complexity with which companies are dealing. >> So I think you would agree that in today's scenario, customers are not looking for a platform, right? But they're looking for a platform which can deliver business value. They're looking at business value and resiliency and then at the end, the cost, right? So if you're able to deliver these three things to the customer through the cloud implementation, I think that's success for us. >> Right. We've talked about transformation a lot this week and modernization, right, which is those are two pretty key buzzwords right now we're hearing a lot of. So when you see said, you know, companies come to you and they say, okay, it's time for us to make this commitment. Do they make it generally wholeheartedly? Is there still some trepidation of the unknown? Because there's a lot of, as we've said, complexity to this, it's multidimensional. We can go public, we can go hybrid, we can go multicloud. I mean, we got a lot of flavors. >> Yeah >> Absolutely. >> No, we see a spectrum. There are customers who are very early in the journey of getting onto cloud and are a little uncertain about what value they can get out of it. And on the other end of the spectrum, there are companies who are well into the journey who have understood what are the benefits of truly leveraging cloud who also understand what are the challenges they will face in getting onto the journey. So we get to meet a spectrum of customers, I would say. If you ask me where do bulk of them lie, I would say early in their journey. I would say there are only a handful who have that maturity where they can predict what's exactly going to happen on the cloud journey, what value they will accumulate through the process. So there's a lot of hand holding to be done, a lot of, you know, solving together to be done with our clients. >> You know, it is such a dynamic environment too, right? You have new opportunities that seem to be developed and released on a daily basis, almost, right? There's a large amount of flexibility, I would think, that has to be in place because where you think you're going to go today might not be where you wind up in six months. >> That's true. >> Is that fair? >> Absolutely fair. And I think from that perspective, if you look at the number of services that AWS provides, right? And what customers are looking for is how can they compose their business processes using this multiple services in a very seamless manner. And most of the announcements that we have seen during the re:Invent as well, they're talking about seamless connectivity between their services. They're talking about security, they're talking about creating a data fabric, the data zone that they announced. I think all these things put together, if you're able to kind of connect the dots and drive the business processes, I think that's what we want to do for our customers. >> And the value to AWS, it just can't be underscored enough I would assume, because there's comfort there, there's confidence there. When you bring that to the table as well along with your services, what kind of magnitude are we talking about here? What kind of force do you think? How would you characterize that? >> Well I think, you know, firstly, I would say that most of our engagements are not just services. Ashish and team and the company have invested heavily in building IP that we pair with our services so that we bring non-linearity and more, I would say, certainty to the outcomes that our customers get. And I can share some examples in the course of the conversation, but to answer your question in terms of magnitude, what we are collaborating with AWS on for our clients ranges from helping customers build more resiliency. And I'm talking about life sciences companies build more resiliency in the manufacturing R and D processes. That's so critical. It was even more critical during the pandemic times because we were working with some of the pharma companies who were contributing to the efforts in the pandemic. That's one end of the spectrum. On the other side, we are helping streaming companies and media companies digitize their supply chain, and their supply chains, the media supply chain, so that it is more effective, it's more efficient, it's more real time, again, using the power of the cloud. We are helping pharmaceutical companies drive far greater speed in the R and D processes. We are helping banking companies drive far more compliance in their anti-money laundering efforts and all of those things. So if you look at the magnitude, we judge the magnitude by the business impact that it's creating and we are very excited about what AWS, LTI Mindtree, and the customer are able to create in terms of those business impacts. >> And these are such major decisions. >> That's right. >> For a company, right, to make, and there are a number of factors that come into play here. What are you hearing from the C-Suite with regard to what weighs the most in their mind and is there, is it a matter of, you know, fear missing out? Or is it about trying to stay ahead of your competition, catching up the competition? I mean, generally speaking, you know, where are the, where's the C-Suite weighing in on this? >> I think in the current times, I think there is a certain level of adoption of cloud that's already happened in most enterprises. So most CIOs in the C-suite- >> They already get it. They already get it. >> They kind of get it, but I would say that they're very cagey about a bunch of things. They're very cagey about, am I going to end up spending too much for too little? Am I going to be able to deliver this transformation at the speed that I'm hoping to achieve? What about security? Compliance? What about the cost of running in the cloud? So those are some really important factors that sometimes end up slowing the cloud transformation journeys down because customers end up solving for them or not knowing for them. So while there is a decent amount of awareness about what cloud can do, there are some, a whole bunch of important factors that they continue to solve for as they go down that journey. >> And so what kind of tools do you provide them then? >> Primarily, what we do is, to Siddharth's point, right? So on one end, we want to see to it that we are doing the business transformation and all our cloud journeys start with a business North Star. So we align, we have doubled down on, say, five to six business domains. And for each of these business domains industries, we have created business North Star. For these business North Star, we define the use cases. And these use cases then get lit up through our platform. So what we have done is we have codified everything onto our platform. We call it Infinity. So primarily business processes from level one, level two, level three, level, and then the KPIs which are associated with these business processes, the technical KPIs and the business KPIs, and then tying it back to what you have deployed on cloud. So we have end to end cloud transformation journeys enabled for customers through the business North Star. >> And Infinity is your product. >> Can I add something? >> Please do. Yeah, please. >> Yeah so, you know, Ashish covered the part about demystifying if I were to do this particular cloud initiative, it's not just modernizing the application. This is about demystifying what business benefit will accrue to you. Very rare to find unless you do a very deep dive assessment. But what the platform we built also accelerates, you talked about modernization early in the conversation, accelerates the modernization process by automating a whole bunch of activities that are often manual. It bakes insecurity and compliance into everything it does. It automates a whole bunch of cloud operations including things like finops. So this is a life cycle platform that essentially codifies best practices so that you are not getting success by coincidence, you're getting success by design. So that's really what, that's really how we've approached the topic of realizing the true power of cloud by making sure that it's repeatedly delivered. >> Right. You know, I want to hit on security too because you brought that up just a few moments ago. Obviously, you know, we all, and I'd say we, we can do a better job, right? I mean, there's still problems, there's still challenges, there are a lot of bad actors out there that are staying ahead of the game. So as people come to you, clients come to you, and they raise these security concerns, what's your advice to them in terms of, you know, what kind of environment they're going into and what precautions or protections they can put in place to try to give themselves a little bit of peace of mind about how they're going to operate? >> You want to take it? >> So I think primarily, if you are going to cloud, you are going with an assumption that you are moving out of your firewalls, right? You're putting something out of your network area. So and from that perspective, the parameter security from the cloud perspective is very, very important. And then each and every service or the interactions between the services and what you integrate out of your organization, everything needs to be secured through the right guard rates. And we integrate all those things into our platform so that whatever new apps that get deployed or build or any cost product that gets deployed on cloud, everything is secure from a 360 degree perspective. So primarily, maintaining a good security posture, which on a hybrid cloud, I would not say only cloud, but extending your on-prem security posture to cloud is very, very important to when you go to implementing anything on could. >> If you had a crystal ball and we were sitting down here a year from now, you know, what do you think we'd be talking about with regard to, you know, developing these end-to-end opportunities that you are, what's the, I wouldn't say missing piece, but a piece that you would like to have refined to the point where you come back next year and say, John, guess what we did? Look what we were able to accomplish. Anything that you're looking at that you want to tackle here in 2023? Or is there some fine tuning somewhere that you think could even tighten your game even more than it is already? >> We have a long, long way to go, I would say. I think my core takeaway in terms of where the world of technology is headed because cloud is, you know, is essentially a component of what customers want to achieve. It's a medium through which they want to achieve. I think we live in a highly change oriented economy. Every industry is what I call getting re-platformed, right? New processes, new experiences, new products, new efficiency. So a year from now, and I can tell you even for few years from now, we would be constantly looking at our success in terms of how did cloud move the needle on releasing products faster? How did cloud move the needle on driving better experience and better consumer loyalty, for example. How did cloud move the needle on a more efficient supply chain? So increasingly, the technology metrics like, you know, keeping the lights on, or solving tickets, or releasing code on time, would move towards business metrics because that's really the ultimate goal of technology or cloud. So I would say that my crystal ball says we will increasingly be talking business language and business outcomes. Jeff Bezos is an incredible example, right? One of his annual letters, he connected everything back into how much time did consumers save by using Amazon. And I think that's really where in the world, that's the world we are headed towards. >> Ashish, any thoughts on that? >> I think Siddharth put it quite well. I would say if you are able to make a real business impact for our customers in next one year, helping them in driving some of their newer services on cloud through cloud, that would be a success factor for us. >> Well gentlemen, congratulations on the merger. I said two weeks. Still very much in the honeymoon phase and I'm sure it's going to go very well and I look forward to seeing you back here in a year. We'll sit down, same spot, let's remember, fifth floor, and we'll give it a shot and see how accurate you were on that. >> Absolutely. >> Wonderful. It's been a pleasure. >> Thank you gentlemen. >> Thank you for joining us. >> Thank you. >> Very good. Ashish, good to see you, sir. >> Thank you. >> A pleasure. We'll continue here. We're at the Venetian at AWS re:Invent 22, continue at the AWS Global Showcase startup. I'm John Walls. You're watching theCUBE, the leader in high tech coverage. (gentle music)

>>Hello from Chicago, Lisa Martin, back with you and John Furrier. This is day one of the Cube's coverage of Ansible Fest 2022. John, we've been having great conversations all morning about automation and how it's really pivotal and central. One of the things that we want to talk about next is automation as a strategy. Yeah. You know, some of the barriers to customer adoption, one of them is, well, can we, can we really understand where the most ROI is gonna be? But another one is automation happening kind of in pockets and silos. And we're gonna be talking next with one of our alumni about breaking those down. >>This is gonna be a great segment from the customer perspective, the conversations they're having problems trying to solve, and really got a great cube alumni back to share. And we're excited. It's be a good segment. >>We do have a great alumni, Walter Bentley, Fresh from the keynote stages back with us, the senior manager of the automation practice at Red Hat. Walter, it's great to have you back on the program. >>Thank you. Thank you for having me back. I really look forward to doing this every year and you know, it's, it's >>Exciting. So we had your great energetic keynote this morning and you were really talking about organizations need to think about automation from a strategic lens perspective, a really a true long term investment. Where are most organizations today and how are you gonna help them get there? >>Right. So most organizations today are kind of in that sweet spot where they've discovered that they can do the tactical automation and they can deal with those small day-to-day things. And now they wanna move into the space where they're really able to plug automation into their current workflows and try to optimize it. And, and that's the perfect direction to be heading. And, and what I always encourage our customers is that once you get to that point, don't stop. You gotta keep going because the next phase is, is when you begin to innovate with automation. And when automation is at first is, is at the beginning of the, of everything you're creating. And at that point, that's when you're really gonna see the great benefits from it. >>How have your customer conversations evolved over the last couple of years, particularly as the world has changed, but we've also seen the acceleration of automation and so much, so much advancement in the technology. >>Right. You know, you'll be shocked that our customers wanted us to speak to them in more of an enterprise architecture level. They wanted us to really be able to come in and help them design how they're going to lay out their automation vision. And that surprised me at first. My background being in architecture for many years, I didn't know that, you know, automation had evolved to that level. And, and that was one of the things that we, we tried to do our best to rise to the occasion and be able to answer that call. >>You know, Walter, one of the things when we were in person last in 2019, you were on the cube and then we did the remote. We were kind of right. You got it right. When we were, we were talking about this, Hey, if this goes the way we think it's gonna go, the automation layer is gonna be horizontally scaled with the cloud. So income, cloud, growth, lift and shift. Now I got some refactored applications in the cloud and I got on premises edge coming hybrid steady state. What does automation look like? You had said it's gonna scale. Yep. And so as clients realize, well this is was the kind of a group within the group doing some automation stuff with Ansible, all great stuff, Product leadership, great community check, check, check. Now, how do you make that a global architecture for a company? What, what's it take to make that an enterprise scale architecture? What's the next step for the, for the journey and, and for the community and the customers? >>So one of the major announcements today is actually one of the right steps in the right direction, which is now that you can deploy a on all of your hyperscalers, right? So you have it local, you're covering your private cloud area, now you're able to cover your hyperscalers. Now it's time to unite them together so that they can all kind of work as one function. And to me, that is the enterprise approach that that to aap. And I'm just so excited that we finally have rolled it out for aws. We have it for Azure, of course we have it inside. And we're also working on things like you said, like the edge, but also things like making sure we're covering customers that are air gaped customers that do not have the capability of the ingress in, in, in, in being, of being able to go in and out of that environment and that network. Right. We're working on strategic, strategic solutions to be able to do that better >>For what's interesting, we've been talking about super cloud on the cube. I, we coined that term at reinvent about people using cloud in a different way to kind of do things and it's become kind of also a, a term for multi-cloud. Yes. So if you think about what you just said, it's interesting, this cloud services that could, they all have stores, they have compute, There might be a day where they're all kind of invisible. Yes. And you can have spanning services across the cloud, but yet they can still differentiate on their own. So it's not so much about sneakers, it's more about that interoperability. How do you see that? What's your reaction to that? Right. >>Well, that's one of the core reasons why we move to the name of the answ automation platform. Platform being the key right? Is, is the platform is supposed to be able to span into different environments and really kind of unite them together. And that was one of the the things that I really liked about when we went to that late last year. Yeah. Late last year. And, and we've been working with our customers and make sure that we make that front and center, that they move towards that environment so that they can begin to do better scale and really operate at that, at that executive level. >>What's your favorite customer story that you think really articulates the value of what you just said? >>Right. So the one, so I'll give you a different one from the one that I, that I talked about on stage. And, and again, it it, when we went in from a services engagement, we did not expect the outcome of the fact that they would access this particular customer. We went in something very tactical, just laying down the platform for them. And, and the expectation was we would lay it down and walk away and then hopefully they would pick it up and kind of run with it. What we came to realize is that they liked the oversight and they liked the way that we were working with them. And they wanted to take those preferred approaches and really embed them Right. And their organization. And so they invited us back actually for two or three different consulting engagements to come back and just help them drive that adoption. And this is at the, they're at the very beginning, right? So they're doing it a little bit different in a lot of other organizations. The other organizations would lay down the platform, do some things, and then call us back to help them them with adoption, Right. >>Is the report card out? Yeah, >>Absolutely. They did it differently. And, and that to me stood out as the level of maturity their IT organization is. >>It sounds like they went from tactical to strategic Yes. Pretty quickly. Which is not normally the >>Case. No, no, not at all. Not normally the case. But as you can clearly see that, we're starting to see that more and more with our customers. They're upleveling, I hate for the theme, but they're upleveling. Right. And, and, and that's what I meant by my organization, my team that I, that I run, we have to do more with our customers because they're expecting more >>For them to level up. And I loved how that was used this morning. I'm like, Yeah, that's a cool term. Level up. We all gotta level up to some degree. How are you helping organizations do that from a cultural shift perspective? Because of course the people are so integral to this being successful. Can't forget >>That. Absolutely. So, you know, you know, remember the days of when you would have the DevOps team and that was like the thing, like you have to form your DevOps team and once you got that, you're good to go. And, and I always tell our customers that's a good start, but that's definitely not where you want to end. And you have to get to the point where you have all parts of your organization writing automation content, feeling comfortable, being able to kind of control their day to day. And so that's where you have to break down those silos. You have to really have those, you know, your operators and your developers and, and your DBAs and your networking folks really communicating. And, and if everyone kind of takes care of their own world and write content to control what they do on a day to day, they can bring those together. >>Walter, on buzzword it's been kicking around Silicon Valley in the tech industry re recently is multiplayer versus single player software. Yes. And I I heard that must be from gamers obviously. Yes. Discourse pop. I heard that on, stayed here in the matrix announcement earlier. You know, when you talk about teamwork ops devs while working together, clearly the operator role is changing. What that means is changing devs are getting stronger and more open source, they're shifting left and all that good stuff in the, in the CID pipeline as the teams work together, multiplayer in an organization. What's the success form of that you see emerging for how to organize, how to motivate, how to get people kind of in a good, you know, teamwork pass score kind of team oriented approach? >>Well, I'm really proud to talk about is how AAP has really enabled that and, and kind of fast tracks that ability for everyone to work together within a, the all the functionality that's now built into it. There's pieces of it that are focused on different operators or different parts of the IT organization, right. And, and, and we're made to be able to help to bring them all together. You know, I love the components such as the service catalog. You know, imagine being able to have a place where you can publish all of your, your content for other people to consume. You know, back in the day everything was stored in, in a repository, right? And you had to know what you were looking for. And so just small changes like that, having the, the, the Ansible toy, right? So you're having tools that are actually built in for those who are writing the content to be able to have at their fingertips the ability to test their content right from inside of the, the, the toy, right? So the terminal interface, just those small little nuances to me is what helps to bring it all together and kind of create that >>Great leverage glue. Yes. Not a lot of busy work and you know, absolutely. Hunting and packing for stuff like configuring manually. >>Absolutely. >>Awesome. What's next for you guys? >>Well, you know, we have some big announcements coming up tomorrow. I won't, I won't get into as much as I want to talk about >>It. Events. Yeah, >>Yeah, yeah. Something starts with the e but also some really fantastic technology. We're, what we're doing is, is we're really taking the idea of automation and really feeding into it in a sense that we're building into some mar some, some really smart technology into aap. And I'm, I'm, I'm excited, I'm excited for direction it's going and I know everyone tomorrow are gonna really, really hear some great >>Things. We heard upleveling, we heard upleveling culture shift. If I asked you what does culture shift mean, how would you answer that? >>I would answer that in a sense that it, it, the culture shift is, is shifting from the place where you feel that you're on an island and you have to solve for it alone as well as feeling that you have to solve for the whole ribbon of whatever you're working on. And that culture shift is moving from that mentality to the fact that you have a whole team of folks who may know how to solve for that already. And you feel comfortable being able to reach out to them and work with them to be able to build that. And that's, that to me is the change. You know, I'm, I'm a old school infrastructure dude, you know, I was the one who would, who would wake up two o'clock in the morning to fix a problem, right? I thought it was on me, but now the culture shift is now it's, we are a team and we're gonna work together to solve it. So that's, that's kind of my view on >>It. And the appetite in organizations is there, cuz oftentimes in the, in the siloed world, it's, I own this, this is my baby. Right? Right. How do you help them as a, as a trusted advisor to really open up the kimono and embrace that collaboration? Because ultimately that's the right strategic direction for the business, >>Right? The first step in that is making sure that everyone is kind of operating from the same book, right. Or the same plan. And, and until you actually write that plan down and publish it in a place for other people to consume it, it creates a little bit of a barrier, right? So that's the first thing we do is write down that plan, make it available for all the consume. And at the beginning, you know, not everyone runs to it, but over time if their curiosity begins to peak and then over time they begin to consume it and possibly contribute to it themselves over time, that's, that's how we kind of conquer that. And so far we've seen some good success. >>What would you say if someone said, you know, I want some proof, proof in the pudding proven methods to help accelerate the time to value with automation and help organizations to really understand and quantify the ROI for doing so. >>Right. And, and to me that's, this is the conversation I love having because we've, we've come out with something that we call success metrics and, and yes, they are exactly what they sound like, right? There are some metrics that you can use to measure in your organization to kind of determine your maturity around automation. The two key things that I would love to share about that is that when we think of metrics, right? We think of performance, we think of, you know, how well something is running, how long it's been running. Those are all great, but the two additional success metrics that we include in there are around more of the cultural field. The perception, right? The perception as well as how comfortable your employees feel using that product. And that's where that, that the shift of looking at the cultural, not just the technical side, but the cultural side of things has made a big difference. So I love sharing those metrics with our customers. It usually resonates and then we help them dig in on, to see how they, how they fit, and also give them some ideas as to how they can improve going forward. >>I'm sure they appreciate that knowing where that, where we are now, how do we get to the end, not the end state. Obviously it's a journey, but how do we get farther along in this from a unified front approach rather than absolutely operating in these silos, which is not gonna get us to the, the the on the journey that we should be on. Correct. Yeah. Yep. So some good stuff coming out tomorrow. Not gonna give us any nuggets, which totally understands. Nope. >>No, but it's, you're gonna be very excited. Yes. It's good stuff. >>Awesome. I gotta ask you one quick question before we wrap up. You mentioned multi-cloud earlier. This is a big conversation in the industry. A lot of people are debating what that is. It sounds good on paper. Where is the customer's view as they look at this journey? Because we, we see a future where there'll be services that won't be common across clouds. There's a differentiation and some that will be, and that, that just be shared like compute for instance. And let, let us be there where you can call in to the multi-cloud. What's, how do you, how do your customers think about multi-cloud? Are they having that conversation more they go, Is that more of a destination of the future? In their mind >>It feels more like a destination of the future. Right now, a lot of organizations have kind of solidified on one cloud per se that they want to be able to roll out as far as being able to scale up and down their resources. But the idea is, is eventually, you know, you, you're gonna go with whatever works best for that product or whatever works best for that, that business case that you're trying to solve for. And, and that's why I love the fact that AEP is kind of generically being able to be applied across all of them. So that, that is, that is gonna be your unifier, right? That's gonna be the layer that will stay the same no matter where you go. And that's one of the things that I love about our product around that is that, that we are meant to be the unifier and we're >>Bless the whole today. It's a great opportunity for Ansible that's there. All >>Right. To be the unifier. Last question for you before we wrap. What was some of the feedback about, from your session this morning on Ansible really being that unifier? Any, any folks come up to you and say anything that was particularly insightful? >>Well, you know what, it it, what was kind of alluded to or shared with me directly was the fact that, you know, thinking about automation as you would traditional platforms, right? And, and building a strategy and, and the idea that you need to write that down and actually make some decisions around that. And, and it wasn't that it wasn't thought about it, it was just, it just never came front to mind. And, and so I'm happy that I was able to plant that seed because that, that's what we're seeing that makes the difference between those who are very successful with automation and those, those who may >>Not be writing it down. Sometimes it's fact to basics that back to basics really help absolutely fuel the growth of organizations. Walter, thank you. Thanks for joining John and me on the queue today talking about what's going on, automation as a strategy, the vision and how Ansible is really on its way to becoming that unifier. We appreciate your insights. Cool. >>No, it's my pleasure. And thank you for having me again. All >>Right, cool. Our pleasure for Walter Bentley and John Furrier. I'm Lisa Martin. You're watching The Cube Live from Chicago. Day one of our coverage of Ansible Fest 2022 continues next.

(upbeat music) >> Hello everyone, welcome to the special CUBE presentation of the AWS Partner Showcase season one, episode two. I'm John Furrier, your host of theCUBE. We've got two great guest here. Douglas Ko, Director of product marketing at Cohesity and Sabina Joseph General Manager of AWS, Amazon Web Services. Welcome to the show. >> Thank you for having us. >> Great to see you Sabina and Douglas. Great to see you, congratulations at Cohesity. Loved the shirt, got the colors wearing there on Cohesity, Always good I can't miss your booth at the shows, can't wait to get back in person, but thanks for coming in remotely. I got to say it's super excited to chat with you, appreciate it. >> Yeah, pleasure to be here. >> What are the trends you're seeing in the market when it comes to ransomware threats right now. You guys are in the middle of it right now more than ever. I was hearing more and more about security, cloud scale, cloud refactoring. You guys are in the middle of it. What's the latest trends in ransomware? >> Yeah, I have to say John, it's a pleasure to be here but on the other hand, when you asked me about ransomware, right? The data and the statistics are pretty sobering right now. If we look at what just happened in 2020 to 2021, we saw a tenfold increase in a ransomware attacks. We also saw the prediction of a ransomware attack happening every 11 seconds meaning by the time I finished this sentence there's going to be another company falling victim to ransomware. And it's also expected by 2031 that the global impact of ransomware across businesses will be over $260 billion, right? So, that's huge. And even at Cohesisity, right, what we saw, we did our own survey, and this one actually directly to end users and consumers. And what we found was over 70% of them would reconsider doing business with a company that paid a ransom. So all these things are pretty alarming and pretty big problems that we face today in our industry. >> Yeah, there's so many dimensions to it. I mean, you guys at Cohesity have been doing a while. It's being baked in from day one, security in the cloud and backup recovery, all that is kind of all in one thing now. So to protect against ransomware and other threats is huge Sabina, I got to ask you Amazon's view of ransomware is serious. You guys take it very seriously. What's the posture and specifically, what is AWS doing to protect customers from this threat? >> Yeah, so as Doug mentioned, right, there's no industry that's immune to ransomware attacks. And just as so we all level set, right? What it means is somebody taking control over and locking your data as an individual or as a company, and then demanding a ransom for it, right? According to the NIST, the National Institute of Standards and Technology cybersecurity framework, there are basically five main functions which are needed in order to plan and manage these kind of cybersecurity ransomware attacks. They go across identifying what do you need to protect, actually implementing the things that you need in order to protect yourself, detecting things if there is an attack that's going on, then also responding, how do you get out of this attack? And then bringing things, recovery, right? Bringing things back to where they were before the attack. As we all know, AWS takes security very seriously. We want to make sure that our customer's data is always protected. We have a number of native security solutions, but we are also looking to see how we can work with partners. And this is in fact when in the fall of 2019, the Cohesity CEO, Mohit Aron, myself and a couple of us, we met and we brainstorm, what could we do something that is differentiated in the market? When we built this data management as a service native solution on top of AWS, it's a first of a kind solution, John. It doesn't exist anywhere else in the market, even to even today. And we really focused on using the well architected review, the five pillars of security, reliability, operational excellence, performance, and cost optimization. And we built this differentiated solution together, and it was launched in April, 2020. And then of course from a customer viewpoint, they should use a comprehensive set of solutions. And going back to that security, that cyber security framework that I mentioned, the Cohesity data management as a service solution really falls into that recovery, that last area that I mentioned and solution actually provides, granular management of data, protection of data. Customers can spin up things very quickly and really scale their solution across the globe. And ensure that there is compliance, no matter how many times we do data changes, ads and so on across the world. >> Yeah, Sabina, that's a great point about that because a lot of the ransomware actually got bad actors, but also customers can misconfigure things. They don't follow the best practice. So having that native solutions are super important. So that's a great call out. Douglas, I got to go back to you because you're on the Cohesity side and a the partner of AWS. They have all these best practices that for the good actors, got to pay attention to the best practices and the bad actors also trying to get in creates a two, challenge an opportunity. So how do organizations protect their data against these attacks? And also how do they maintain their best practices? Because that's half the battle too, is the best practices to make sure you're following the guidelines on AWS side, as well as protecting the attacks. What's your thoughts? >> Yeah, absolutely. First and foremost, right? As an organization, you need to understand how ransomware operates and how it's evolved over the years. And when you first look at it, Sabina already mentioned it, they started with consumers, small businesses, attacking their data, right? And some of these, consumers or businesses didn't have any backup. So the first step is just to make sure your data is backed up, but then the criminals kind of went up market, right? They understood that big organizations had big pocket and purses. So they went after them and the larger organizations do have backup and recovery solutions in place. So the criminals knew that they had to go deeper, right? And what they did was they went after the backup systems themselves and went to attack, delete, tamper with those backup systems and make it difficult or impossible to recover. And that really highlighted some solutions is out there that had some vulnerabilities with their data immutability and capabilities around WORM. And those are areas we suggest customers look at, that have immutability and WORM. And more recently again, given the way attacks have happened now is really to add another layer of defense and protection. And that includes, traditionally what we used to call, the 3-2-1 rule. And that basically means, three copies of data on two different sets of media with one piece of that data offsite, right? And in today's world and the cloud, right? That's a great opportunity to kind of modernize your environment. I wish that was all that ransomware guys we're doing right now and the criminals were doing, but unfortunately that's not the case. And what we've seen is over the past two years specifically, we've seen a huge increase in what you would call data theft or data exfiltration. And that essentially is them taking that data, a specific sense of the data and they're threatening to expose it to the dark web or selling it to the highest bidder. So in this situation it's honestly very difficult to manage. And the biggest thing you could do is obviously harden your security systems, but also you need a good understanding about your data, right? Where all that sensitive information is, who has access to it and what are the potential risks of that data being exposed. So that takes another step in terms of leveraging a bunch of technologies to help with that problem set. >> What can businesses do from an architectural standpoint and platform standpoint that you guys see there's key guiding principles around how their mindset should be? What's the examples of other approaches- >> Yeah. >> Approach here? >> No, I think they are both us at Cohesity and I'll speak for Sabina, AWS, we believe in a platform approach. And the reason for that is this a very complicated problem and the more tools and more things you have in there, you add risk of complexity, even potential new attack surfaces that the criminals can go after. So we believe the architecture approach should kind of have some key elements. One is around data resiliency, right? And that again comes from things like data encryption, your own data is encrypted by your own keys, that the data is immutable and has that, right, want to read many or WORM capabilities, so the bad guys can't temper with your data, right? That's just step one. Step two is really understanding and having the right access controls within your environment, right? And that means having multi factor authentication, quorum, meaning having two keys for the closet before you can actually have access to it. But it's got to go beyond there as well too. We got to leverage some newer technologies like AI and machine learning. And that can help you with detection and analysis of both where all your sensitive information is, right? As well as understanding potential anomalies that could signify attack or threat in progress. So, those are all key elements. And the last one of course is I think it takes a village, right? To fight the ransomware war. So we know we can't do it alone so, that's why we partner with people like AWS. That's why we also partner with other people in the security space to ensure you really have a full ecosystem support to manage all those things around that framework. >> That's awesome. Before I get to Sabina, I want to get into the relationship real quick, but I want to come back and highlight what you said about the data management as a service. This is a joint collaboration. This is some of the innovation that Cohesity and AWS are bringing to the market to combat ransomware. Can you elaborate more on that piece 'cause this is important. It's a collaboration that we're going to gather. So it's a partner and you guys were going to take us through what that means for the customer and to you guys. I mean, that's a compelling offering. >> So when we start to work with partners, right? we want to make sure that we are solving a customer problem. That's the whole working backwards from a customer. We are adding something more that the customer could not do. That's why when either my team or me, we start to either work on a new partnership or a new solution, it's always focused on, okay, is this solution enabling our customer to do something that they couldn't do before? And this approach has really helped us, John, in enabling majority of the fortune 500 companies and 90% of the fortune 100 companies use partner solutions successfully. But it's not just focused on innovation and technology, it's also focused on the business side. How are we helping partners grow their business? And we've been scaling our field teams, our AWS sales teams globally. But what we realized is through partner feedback, in fact, that we were not doing a great job in helping our partners close those opportunities and also bring net new opportunities. So in our field, we actually introduced a new role called the ISV Success Manager, ISMs that are embedded in our field to help partners either close existing opportunities, but also bring net new opportunities to them. And then at re:Invent 2020, we also launched the ISB accelerate program, which enables our field teams, the AWS field teams to get incentive to work with our partners. Cohesity, of course, participates in all of these programs and has access to all of these resources. And they've done a great job in leveraging and bringing our field teams together, which has resulted in hundreds of wins for this data management as a service solution that was launched. >> So you're bringing customers to Cohesity. >> Absolutely. >> Okay, I got to get the side. So they're helping you, how's this relationship going? Could you talk about the relationship on the customer side? How's that going? Douglas, what's your take on that? >> Yeah, absolutely. I mean, it's going great. That's why we chose to partner with AWS and to be quite honest, as Sabina mentioned, we really only launched data management and service back in 2020, late 2020. And at that time we launched with just one service then, right, when we first launched with backup as a service. Now about 15 months later, right? We're on the brink of launching four services that are running on AWS cloud. So, without the level of support, both from a go to market standpoint that Sabina mentioned as well as the engineering and the available technology services that are on the AWS Cloud, right? There's no way we would've been able to spin up new services in such a short period of time. >> Is that Fort Knox and Data Govern, those are the services you're talking about Or is that- >> Yeah, so let me walk you through it. Yeah, so we have Cohesity DataProtect, which is our backup as a service solution. And that helps customers back their data to the cloud, on-prem, SaaS, cloud data like AWS, all in a single service and allows you to recover from ransomware, right? But a couple months ago we also announced a couple new services that you're alluding to John. And that is around Fort Knox and DataGovern. And basically Fort Knox, it is basically our SaaS solution for data isolation to a vaulted copy in the AWS cloud. And the goal of that is to really make it very simple for customers, not only to provide data immutability, but also that extra layer of protection by moving that data offsite and keeping it secure and vaulted away from cyber criminals and ransomware. And what we're doing is simplifying the whole process that normally is manual, right? You either do it manually with tapes or you'll manually replicate data to another data center or even to the cloud, but we're providing it as a service model, basically providing a modern 3-2-1 approach, right? For the cloud era. So, that's what's cool about Fort Knox, DataGovern, right? That's also a new service that we announced a few months ago and that really provides data governance and user behavior analytics services that leverages a lot that AI machine learning that everybody's so excited about. But really the application of that is to automate the discovery of sensitive data. So that could be your credit card numbers, healthcare records, a personal information of customers. So understanding where all that data is, is very important because that's the data that the criminals are going to go after and hold you host. So that's kind of step one. And then step two is again, leveraging machine learning, actually looking at how users are accessing and managing that data is also super important because that's going to help you identify potential anomalies, such as people sharing that data externally, which could be a threat. It could be in improper vault permissions, or other suspicious behaviors that could potentially signify data exfiltration or ransomware attack in progress. >> That's some great innovation. You got the data resiliency, of course, the control mechanism, but the AI piece machine learning is awesome. So congratulations on that innovation. Sabina, I'm listening to conversation and hear you talk. And it reminds me of our chat at re:Invent. And the whole theme of the conference was about the innovation and rapid innovations and how companies are refactoring with the cloud and this NextGen kind of journey. This is a fundamental pillar of AWS's rapid innovation concept with your partners. And I won't say it's new, but it's highly accelerated. How are you guys helping partners be with this rapid innovation, 'cause you're seeing benefits can come faster now, Agile is here. What are some of the programs that you're doing? How are you helping customers take advantage of the rapid innovation with the secret sauce of AWS? >> Yeah, so we have a number of leadership principles, John, and one of them, of course, is customer obsession. We are very focused on making sure we are developing things that our customers need. And we look for these very same qualities when we work with partners such as Cohesity. We want to make sure that it's a win-win approach for both sides because that's what will make the partnership durable over time. And this John, our leadership team at AWS, right from our CEO down believes that partners are critical to our success and as partners lean in, we lean in further. And that's why we signed the strategic collaboration agreement with Cohesity in April, 2020, where data management as a service solution was launch as part of that agreement. And for us, we've launched this solution now and as Doug said, what are the next things we could be doing, right? And just to go back a little bit when Cohesity was developing this solution with us, they used a number of our programs. Especially on the technical side, they used our SaaS factory program, which really helped them build this differentiated solution, especially focused around security compliance and cost optimizing the solution. Now that we've launched this solution, just like Doug mentioned, we are now focused on leveraging other services like security, AIML, and also our analytic services. And the reason for that is Cohesity, as we all know, protects, manages this data for the customer, but we want to make sure that the customer is extracting value from this data. That is why we continue to look, what can we do to continue to differentiate this solution in this market. >> That's awesome. You guys did a great job. I got to say, as it gets more scale, there's more needs for this rapid, I won't say prototyping, but rapid innovation and the Cohesity side does was you guys have been always on point on the back and recovery and now with security and the new modern application development, you guys are in the front row seats of all the action. So, I'll give you the final worry what's going on at Cohesity, give an update on what you guys are doing. What's it like over there these days? How's life give a quick plug for Cohesity. >> Yeah, Cohesity is doing great, right? We're always adding folks to the team, on our team, we have a few open racks open both on the marketing side, as well as the technology advocacy side. And of course, some of our other departments too, and engineering and sales and also our partner teams as well, working with AWS partners such as that. So, in our mind, the data delusion and growth is not going to slow down, right? So in this case, I think all tides raises all the boats here and we're glad to be innovative leader in this space and really looking to be really, the new wave of NextGen data management providers out there that leverages things like AI that leverages cybersecurity at the core and has an ecosystem of partners that we're working with, like AWS, that we're building out to help customers better manage their data. >> It's all great. Data is in the mid center of the value proposition. Sabina, great to see you again, thanks for sharing. And Douglas, great to see you too. Thanks for sharing this experience here in theCUBE. >> Thanks, John. >> Okay, this is theCUBE's AWS Partner Showcase special presentation, speeding innovation with AWS. I'm John Furrier your host of theCUBE. Thanks for watching. (upbeat music)

(upbeat electronic music) >> Welcome back to the Quantcast Industry Summit on the demise of third-party cookies. The Cookie Conundrum, A Recipe for Success. I'm John Furrier, host of theCUBE. The changing landscape of advertising is here, and Shiv Gupta, founder of U of Digital is joining us. Shiv, thanks for coming on this segment. I really appreciate it. I know you're busy. You've got two young kids, as well as providing education to the digital industry. You got some kids to take care of and train them too. So, welcome to the cube conversation here as part of the program. >> Yeah, thanks for having me. Excited to be here. >> So, the house of the changing landscape of advertising really centers around the open to walled garden mindset of the web and the big power players. We know the big three, four tech players dominate the marketplace. So, clearly in a major inflection point. And you know, we've seen this movie before. Web, now mobile revolution. Which was basically a re-platforming of capabilities, but now we're in an era of refactoring the industry, not replatforming. A complete changing over of the value proposition. So, a lot at stake here as this open web, open internet-- global internet, evolves. What are your, what's your take on this? There's industry proposals out there that are talking to this specific cookie issue? What does it mean and what proposals are out there? >> Yeah, so, you know, I really view the identity proposals in kind of two kinds of groups. Two separate groups. So, on one side you have what the walled gardens are doing. And really that's being led by Google, right? So, Google introduced something called the Privacy Sandbox when they announced that they would be deprecating third-party cookies. And as part of the Privacy Sandbox, they've had a number of proposals. Unfortunately, or you know, however you want to say, they're all bird-themed, for some reason I don't know why. But the one, the bird-themed proposal that they've chosen to move forward with is called FLOC, which stands for Federated Learning of Cohorts. And, essentially what it all boils down to is Google is moving forward with cohort level learning and understanding of users in the future after third-party cookies. Unlike what we've been accustomed to in this space, which is a user level understanding of people and what they're doing online for targeting and tracking purposes. And so, that's on one side of the equation. It's what Google is doing with FLOC and Privacy Sandbox. Now, on the other side is, you know, things like unified ID 2.0 or the work that ID5 is doing around building new identity frameworks for the entire space that actually can still get down to the user level. Right? And so again, Unified ID 2.0 comes to mind because it's the one that's probably gotten the most adoption in the space. It's an open source framework. So the idea is that it's free and pretty much publicly available to anybody that wants to use it. And Unified ID 2.0 again is user level. So, it's basically taking data that's authenticated data from users across various websites that are logging in and taking those authenticated users to create some kind of identity map. And so, if you think about those two work streams, right? You've got the walled gardens and or, you know, Google with FLOC on one side. And then you've got Unified ID 2.0 and other ID frameworks for the open internet on the other side. You've got these two very different type of approaches to identity in the future. Again, on the Google side it's cohort level, it's going to be built into Chrome. The idea is that you can pretty much do a lot of the things that we do with advertising today but now you're just doing them at a group level so that you're protecting privacy. Whereas, on the other side with the open internet you're still getting down to the user level and that's pretty powerful but the the issue there is scale, right? We know that a lot of people are not logged in on lots of websites. I think the stat that I saw was under 5% of all website traffic is authenticated. So, really if you simplify things and you boil it all down you have kind of these two very differing approaches. >> So we have a publishing business. We'd love to have people authenticate and get that closed loop journalism thing going on. But, if businesses wannna get this level too, they can have concerns. So, I guess my question is, what's the trade-off? Because you have power in Google and the huge data set that they command. They command a lot of leverage with that. And again, centralized. And you've got open. But it seems to me that the world is moving more towards decentralization, not centralization. Do you agree with that? And does that have any impact to this? Because, you want to harness the data, so it rewards people with the most data. In this case, the powerful. But the world's going decentralized, where there needs to be a new way for data to be accessed and leveraged by anyone. >> Yeah. John, it's a great point. And I think we're at kind of a crossroads, right? To answer that question. You know, I think what we're hearing a lot right now in the space from publishers, like yourself, is that there's an interesting opportunity right now for them, right? To actually have some more control and say about the future of their own business. If you think about the last, let's say 10, 15, 20 years in advertising in digital, right? Programmatic has really become kind of the primary mechanism for revenue for a lot of these publishers. Right? And so programmatic is a super important part of their business. But, with everything that's happening here with identity now, a lot of these publishers are kind of taking a look in the mirror and thinking about, "Okay, we have an interesting opportunity here to make a decision." And, the decision, the trade off to your question is, Do we continue? Right? Do we put up the login wall? The registration wall, right? Collect that data. And then what do we do with that data? Right? So it's kind of a two-fold process here. Two-step process that they have to make a decision on. First of all, do we hamper the user experience by putting up a registration wall? Will we lose consumers if we do that? Do we create some friction in the process that's not necessary. And if we do, right? We're taking a hit already potentially, to what end? Right? And, I think that's the really interesting question, is to what end? But, what we're starting to see is publishers are saying you know what? Programmatic revenue is super important to us. And so, you know, path one might be: Hey, let's give them this data. Right? Let's give them the authenticated information, the data that we collect. Because if we do, we can continue on with the path that our business has been on. Right? Which is generating this awesome kind of programmatic revenue. Now, alternatively we're starting to see some publishers say hold up. If we say no, if we say: "Hey, we're going to authenticate but we're not going to share the data." Right? Some of the publishers actually view programmatic as almost like the programmatic industrial complex, right? That's almost taken a piece of their business in the last 10, 15, 20 years. Whereas, back in the day, they were selling directly and making all the revenue for themselves, right? And so, some of these publishers are starting to say: You know what? We're not going to play nice with FLOC and Unified ID. And we're going to kind of take some of this back. And what that means in the short term for them, is maybe sacrificing programmatic revenue. But their bet is long-term, maybe some of that money will come back to them direct. Now, that'll probably only be the premium pubs, right? The ones that really feel like they have that leverage and that runway to do something like that. And even so, you know, I'm of the opinion that if certain publishers kind of peel away and do that, that's probably not great for the bigger picture. Even though it might be good for their business. But, you know, let's see what happens. To each business their own >> Yeah. I think the trade-off of monetization and user experience has always been there. Now, more than ever, people want truth. They want trust. And I think the trust factor is huge. And if you're a publisher, you wannna have your audience be instrumental. And I think the big players have sucked out of the audience from the publishers for years. And that's well-documented. People talk about that all the time. I guess the question, it really comes down to is, what alternatives are out there for cookies and which ones do you think will be more successful? Because, I think the consensus is, at least from my reporting and my view, is that the world agrees. Let's make it open. Which one's going to be better? >> Yeah. That's a great question, John. So as I mentioned, right? We have two kinds of work streams here. We've got the walled garden work stream being led by Google and their work around FLOC. And then we've got the open internet, right? Let's say Unified ID 2.0 kind of represents that. I personally don't believe that there is a right answer or an end game here. I don't think that one of them wins over the other, frankly. I think that, you know, first of all, you have those two frameworks. Neither of them are perfect. They're both flawed in their own ways. There are pros and cons to both of them. And so what we're starting to see now, is you have other companies kind of coming in and building on top of both of them as kind of a hybrid solution, right? So they're saying, hey we use, you know, an open ID framework in this way to get down to the user level and use that authenticated data. And that's important, but we don't have all the scale. So now we go to a Google and we go to FLOC to kind of fill the scale. Oh and hey, by the way, we have some of our own special sauce. Right? We have some of our own data. We have some of our own partnerships. We're going to bring that in and layer it on top, right? And so, really where I think things are headed is the right answer, frankly, is not one or the other. It's a little mishmash of both with a little extra, you know, something on top. I think that's what we're starting to see out of a lot of companies in the space. And I think that's frankly, where we're headed. >> What do you think the industry will evolve to, in your opinion? Because, I think this is going to be- You can't ignore the big guys on this Obviously the programmatic you mentioned, also the data's there. But, what do you think the market will evolve to with this conundrum? >> So, I think John, where we're headed, you know, I think right now we're having this existential crisis, right? About identity in this industry. Because our world is being turned upside down. All the mechanisms that we've used for years and years are being thrown out the window and we're being told, "Hey, we're going to have new mechanisms." Right? So cookies are going away. Device IDs are going away. And now we've got to come up with new things. And so, the world is being turned upside down and everything that you read about in the trades and you know, we're here talking about it, right? Everyone's always talking about identity, right? Now, where do I think this is going? If I was to look into my crystal ball, you know, this is how I would kind of play this out. If you think about identity today, right? Forget about all the changes. Just think about it now and maybe a few years before today. Identity, for marketers, in my opinion, has been a little bit of a checkbox activity, right? It's been, Hey, Okay. You know, ad tech company or media company. Do you have an identity solution? Okay. Tell me a little bit more about it. Okay. Sounds good. That sounds good. Now, can we move on and talk about my business and how are you going to drive meaningful outcomes or whatever for my business. And I believe the reason that is, is because identity is a little abstract, right? It's not something that you can actually get meaningful validation against. It's just something that, you know? Yes, you have it. Okay, great. Let's move on, type of thing, right? And so, that's kind of where we've been. Now, all of a sudden, the cookies are going away. The device IDs are going away. And so the world is turning upside down. We're in this crisis of: how are we going to keep doing what we were doing for the last 10 years in the future? So, everyone's talking about it and we're tryna re-engineer the mechanisms. Now, if I was to look into the crystal ball, right? Two, three years from now, where I think we're headed is, not much is going to change. And what I mean by that, John is, I think that marketers will still go to companies and say, "Do you have an ID solution? Okay, tell me more about it. Okay. Let me understand a little bit better. Okay. You do it this way. Sounds good." Now, the ways in which companies are going to do it will be different. Right now it's FLOC and Unified ID and this and that, right? The ways, the mechanisms will be a little bit different. But, the end state. Right? The actual way in which we operate as an industry and the view of the landscape in my opinion, will be very simple or very similar, right? Because marketers will still view it as a, tell me you have an ID solution, make me feel good about it, help me check the box and let's move on and talk about my business and how you're going to solve for my needs. So, I think that's where we're going. That is not by any means to discount this existential moment that we're in. This is a really important moment, where we do have to talk about and figure out what we're going to do in the future. My viewpoint is that the future will actually not look all that different than the present. >> And then I'll say the user base is the audience, their data behind it helps create new experiences, machine learning and AI are going to create those. And if you have the data, you're either sharing it or using it. That's what we're finding. Shiv Gupta, great insights. Dropping some nice gems here. Founder of U of Digital and also the adjunct professor of programmatic advertising at Leavey School of business in Santa Clara University. Professor, thank you for coming and dropping the gems here and insight. Thank you. >> Thanks a lot for having me, John. Really appreciate it. >> Thanks for watching The Cookie Conundrum This is theCUBE host, John Furrier, me. Thanks for watching. (uplifting electronic music)

>> Narrator: From theCUBE studios in Palo Alto, in Boston, connecting with thought leaders all around the world. This is theCUBE conversation. >> Everyone welcome to this special CUBE conversation. I'm John Furrier, host of theCUBE here in our Palo Alto studios. During this time of the pandemic, we're doing a lot of remote interviews, supporting a lot of events. theCUBE virtual is our new brand because there's no events to go to, but we certainly want to talk to the best people and get the most important stories. And today I have a great segment with a world-class entrepreneur, Ajeet Singh co-founder and executive chairman of ThoughtSpot. And they've got an event coming up, which is going to be coming up in December 9th and 10th. But this interview is really about what it takes to be a world-class leader and what it takes to see the future and be a visionary, but then execute an opportunity because this is the time that we're in right now is there's a lot of change, data, technology, a sea change is happening and it's upon us and leadership around technology and how to capture opportunities is really what we need right now. And so Ajeet I want to thank you for coming on to theCUBE conversation. >> Thanks for having me, John. Pleasure to be here. >> For the folks watching, the startup that you've been doing for many, many years now, ThoughtSpot you're the co-founder executive chairman, but you also were involved in Nutanix as the co-founder of that company as well. You know, a little about unicorns and creating value and doing things early, but you're a visionary and you're a technologist and a leader. I want to go in and explore that because now more than ever, the role of data, the role of the truth is super important. And as the co-founder, your company is well positioned to do that. I mean, your tagline today on the website says insight is the speed of thought, but going back to the beginning, probably wasn't the tagline. It was probably maybe like we got to leverage data, take us through the vision initially when you founded the company in 2012. What was the thinking? What was on your mind? Take us through the journey. >> Yeah. So as an entrepreneur, I think visionary is a very big term. I don't know if I qualify for that or not, but what I'm really passionate about is identifying very large markets, with very, very big problems. And then going to the white board and from scratch, building a solution that is perfectly designed for the big problem that the market might be facing from scratch. And just an absolute honest way of approaching the problem and finding the best possible solution. So when we were starting ThoughtSpot, the market that we identified was analytics, analytics software. And the big problem that we saw was that while on one hand, companies were building very big data lakes, data warehouses, there was a lot of money being spent in capturing and storing data how that data was consumed by the end-users, the non-technical people, the sales, marketing, HR people, the doctors, the nurses, that process was not changing. That process was still stuck in old times where you have to ask an analyst to go and build a dashboard for you. And at the same time, we saw that in the consumer space, when anyone had a question they wanted to learn about something, they would just go to Google and ask that question. So we said, why can't analytics be as easy as Google? If I have a question, why do I have to wait for three weeks for some data experts to bring some insights to me for most simple questions, if I'm doing some very deep analysis, trying to come up with fraud algorithms, it's understood, you know, you need data expert. But if I'm just trying to understand how my business is doing, how my customers are doing, I shouldn't have to wait. And so that's how we identified the market and the problem. And then we build a solution that is designed for that non-technical user with a very design thinking UX first approach to make it super easy for anyone to ask that question. So that was the Genesis of the company. >> You know, I just love the thinking because you're solving a problem with a clean sheet piece of paper, you're looking at what can be done. And it's just, you can bring up Google because you know, you think about Google's motto was find what you're looking for. And they had a little gimmicky buttons, like I'm feeling lucky, which just took you to a random webpage at that time while everyone else was tryna build these walled gardens and this structural apparatus, Google wanted you in and out with your results fast. And that mindset just never came over to the enterprise and with all that legacy structure and all the baggage associated with it. So I totally loved the vision, but I got to ask you, how did you get to beachhead? How did you get that first success milestone? When did you see results in your thinking? >> Yeah, so I mean, I believe that once you've identified a big market and a big problem, it comes down to the people. So I sort of went on a recruit recruiting mission and I recruited perhaps the best technology and business team that you can find in any enterprise segment, not only just analytics, some of the early engineers, my co-founder, he was at Google before that, Amit Prakash, before that he was at Microsoft working on Bing. So it took a lot of very deliberate effort to find the right kind of people who have a builder's mentality and are also deep experts in areas like search large-scale distributed systems. Very passionate about user experience. And then you start building the product, you know, it took us almost, I would say one and a half three years to get the initial working version of the product. And we were lucky enough to engage with some of the largest companies in the world, such as Walmart who are very interested in our solution because they were facing these kinds of problems. And we almost co-developed this technology with our early customers, focusing on ease of use, scale, security, governance, all of that, because it's one thing to have a concept where you want to make access to data as easy as Google, you have a certain interface people can type and get an answer. But when you are talking about enterprise data and enterprise needs, they are nowhere similar to what you have in consumer space. Consumer space is free for all, all the information is there you can crawl it and then you can access it. In enterprise, for you to take this idea of search, but make it production grid, make it real and not just a concept card. You need to invest a lot in building deep technology and then enabling security and scalability and all of that. So it took us almost , I would say a two and a half to three years to get to the initial version of the product and the problem we are solving and the area of technology search that we are working on. We brought it to the market. It's almost an infinite game. You know, you can keep making things easier and easier. And we've seen how Google has continued to evolve their search over time And it is still evolving. We just feel so lucky to be in this market, taking the direction that we have taken. >> Yeah. It's easy to talk a big game in this area because like you said, it's a hard technical problem because it'll structural data, whether it's schema databases or whatever, legacy baggage, but to make it easy, hard. And I like what you guys go with this, find the right information and put it in the right place, the right time. It's a really hard problem. And the beautiful thing is you guys are building a category while there's spend in the market that needs the problem today. So category creation with an existing market that needs it. So I got to ask you, if you could do me a favor and define for the audience, what is search-driven analytics? What does that mean from your standpoint? >> Yeah, what it means is for the end user, it looks like search but under the hood is driving large scale analytics. I like to say that our product looks like a search engine on the surface, but under the hood, it's a massive number crunching machine. So Search and AI driven analytics. There's two goals there. One, if the user has, any user and we're talking about non-technical users here, we're not talking about necessarily data experts, but if a user has a question, they should be able to get an answer instantly. They shouldn't have to wait. That is what we achieve with Search and with Spot IQ, our AI engine, we help surface insights where people may not even know that those are the questions they should be asking because data has become so complex. People often don't even know what question they should be asking. And we give them a pool that's very easy to use, but it helps surface insights to them. So there is both a pool model that we enabled through Search and a push model that we enable through Spot IQ. >> So I have to ask you that you guys are pioneering this segment you're in first. And sometimes when you're first, you have arrows in your back as you know, it's not all the beginners survive, they get competition copies, but you guys have had a lead. You had success. What's different today as you have competition coming in trying to say, "Oh, we got Search too." So what's different today with ThoughtSpot? How are you guys differentiated? >> Yeah. I mean, that's always a sign of success. If what you are trying to do, if others are saying we have it too, you have done something that is valuable. And that happens in all industry. I think the best example is Tesla. They were the first to look at this very well-known problem. I mean, we haven't had a very sort of unique take on the existence of the problem itself. Everybody knows that there is a problem with access to data, but the technology that we have built is so deep that it's very, very hard to really copy it and make it work in real world with Tesla in automotive industry in cars, there is obviously so many other companies that have launched battery powered cars, electric cars, but there is Tesla and there is all the other electric cars which are a bit of an afterthought, because if you want to build an analytics product, where Search is at the core, Search cannot be added on the top, Search has to be the core, and then you build around it. And that requires you to build a fundamental architecture from the ground up. And you can't take an existing BI product that is built for dash boarding and add a search bar. I have always said that adding a search bar in a UI is perhaps, you know, 10 to 20 lines of JavaScript code. Anyone can add it and there is so much open source stuff out there that you can just take it and plug it. And many people have tried to do that, but taking off the shelf, Search technology that is built for unstructured data and sticking it on to a product that is required to do analytics on enterprise data, that doesn't work. We built a search technology that understands enterprise data at a very deep level, so that when our customers take our product and bring it into their environment, they don't have to fundamentally change how they manage their data. Our goal is to add value to their existing enterprise data Cloud Data Warehouses and deliver this amazing Search experience where our Search engine is enable to understand what's in their data Lake, what's in their Cloud Data Warehouse. What are the schema, the tables, the joints, the cardinality, the data archive, the security requirements, all of things have to be understood by the technology for you to deliver the experience. So now that said, we pride ourselves in not resting on our laurels. You know, we have this sort of motto in the company. We say we are only 2% done. So we are on our own sort of a continuous journey of innovation. And we have been working on taking our Search technology to the next level. And that is something really powerful that we are going to unveil at our upcoming conference, Beyond, in December. And that is one to create even more distance between us and the competition. And it's all driven by what we have seen with our customers, how they're using our product or learnings what they like, what they don't like, where we see gaps and where we see opportunity to make it even easier to deliver value to our customers and our users. >> I think that's a really profound insight you just shared, because if you look at what you just said around thinking about Search as an embedded architectural foundational, you know, embedded in the architecture, that's different than bolting on a feature where you said Java code or some open source library. You know, we see in the security market, people bolted on security had huge problems. Now, all you hear is, "Oh, you got a big security in from the beginning." You actually have baked Search into everything from the beginning. And it's not just a utility, it's a mindset. And it's also a technology metadata data about data software, and all kinds of tech is involved. Am I getting that right? I mean, cause I think this is what I heard you say. It's like, you got to have the data. >> This is totally right. I mean, if I can use an analogy, there is Google search and obviously Yahoo also tried to bring their own search Yahoo search Yahoo actually, Yahoo versus Google is a perfect example or a perfect analogy to compare with ThoughtSpot versus other BI product Yahoo was built for predefined content consumption. You know, you had a homepage, somebody defined it. You could make some customizations. And there is predefined content you can consume it. Now, they also did add search, but that didn't really go so far. While Google said, we will vary from scratch ability to crawl all the data, ability to index all the data and then build a serving infrastructure that deliver this amazing performance and interactivity and relevance for the user. Relevance is where Google already shined. And you can't do those things until you think about the architecture from the ground up. >> Ajeet I'm looking forward to having more deep dive conversations on that one topic. But for the folks who might not be old enough, like me to remember Google back at that time, Yahoo was the best search engine and it was directory basically with a keyword search. It was trivial, technically speaking, but they got big. And then the portal wars came out, we got to have a portal. Google was very much not looked down as an innovator, but they had great technical chops and they just stayed the course. They had a mission to provide the best search engine to help users find what they're looking for. And they never wavered. And it was not fashionable about that time to your point. And then Yahoo was number one, then Google just became Google and the rest is history. So I really think that's super notable because companies face the same problem. What looks like fashionable tech today might not be the right one. I think that's... >> Yeah, and I totally agree. And I think a lot of times in our space, there's a lot of sort of hype around AI and machine learning. We as a company have tried to stay close to our customers and users and build things that will work for them. And a lot of stuff that we are doing, it has never been done before. So it's not to say that along the way, we don't have our own failures. We do have failures and we learn from them. >> Yeah. Yeah. Just don't make the same mistake twice. >> Yeah, I think if you have a process of learning quickly, improving quickly, those are the companies that will have a competitive advantage. In today's world, nobody gets it right the first time. If you're trying to do something fundamentally different, if you're copying somebody else, then you're too late already. >> I totally agree. >> If you do something new, it's about how fast you penetrate And that's... >> That's a great mindset. That's a great mindset. And I think that's worth capturing calling out, but I got to ask you because what's first of all, distinguished history and I love your mindset and just solving problems, big problems. All great. I want to ask you something about the industry and where you guys were in 2012 alright when you started the company, you were literally in what I call the before Cloud phase. Cause it was before Cloud companies and then during Cloud companies and then after Cloud, you know, Amazon clearly took advantage of that for a lot of startups. So right around 2012 through 2016, I'd call that the Amazon is growing up years. How did the Cloud impact your thinking around the product and how you guys were executing because you were right on that wave. You were probably in the sweet spot of your development. >> Yeah. >> Pre business planning. You were in the pre-business planning mode, incomes, Amazon. I'm sure you're probably using Amazon cause your starters and all start up sort of use Amazon at first, but I just think about, do we all have found premise with a data center? How did that impact you guys? And how does that change today? >> Certainly. Yeah it's been fascinating to see how the world is evolving how enterprises have also really evolved in depth, thinking on how they leverage the cloud infrastructure now. In the Cloud, there is the compute and storage infrastructure. And then you have a Cloud Data Warehouse, the analytics stack in the Cloud. That's becoming more popular now with a company like Google, having BigQuery and then Snowflake really amazing concepts and things like that. So when we started, we looked at where our customers are , where is their data. And what kind of infrastructure is available to us at the time there wasn't enough compute to drive the search engine that we wanted to build. There were also not any significant Cloud Data Warehousing at the time, but our engineering team our co-founders, they came from companies like Google, where building a Cloud based architecture and elastic architecture, service oriented architecture is in their DNA. So we architected the product to run on infrastructure that is very elastic that can be run practically anywhere. But our initial customers and applies the Global 2000. They had their data on-prem. So we had started more with on-prem as a go-to-market strategy. and then about four and a half years ago, once cloud infrastructure I'm talking about the compute infrastructure started to become more mature, we certified our software, to run on all three clouds So today we have more than 75 to 80% of our customers already running our software in the Cloud. And as now, because we connect to our primary data sources, our Cloud Data Warehouses, Cloud Data Lakes. Now with Snowflake and BigQuery and Synapse and Redshift, we have enough of our customers who have deployed Cloud Data Warehouses. So we are also able to directly integrate with them. And that's why we launched our own hosted SaaS Offering about a month ago. So I would say our journey in this area has been sort of similar to companies like Splunk or Elastic, which started with a software model initially deployed more on-prem, but then evolved with the customers to the Cloud. So we have a lot of focus and momentum and lot of our customers, as they're moving their data to the Cloud, they're asking us as well to be in the Cloud and provide a hosted offering. And that is what we have built for the last one year. And we launched it a month ago. >> It's nice to be on the right side of history. I got to say, when you're on the way to be there. And that also makes integrations easy too. I love the Cloud play. Let's get to the final segment here. I want to get your thoughts on your customers, your advice. There's a huge untapped opportunity for companies when it comes to data, a lot of them are realizing that the pandemic is highlighting a lot of areas where they have to go faster and then to go to Cloud, they're going to build modern apps more data's coming in than ever before. Where are these untapped opportunities for customers to take advantage of the data? And what's your opinion on where they should look and what they should do? >> Yeah, I really think that the pandemics has shown for the first, the value of data to society at large, there is probably more than a billion people in the world that have seen a chart for the first time in their life. Everybody is being... and COVID has done some magic. But everybody was looking at charts of infection and so on and so forth. So there is a lot more broad awareness of what data can do in improving our society at large for the businesses of course, in the last six, seven months, you heard it enough from lot of leaders that digital transformation is accelerating. Everybody is realizing that the way to interact in the world is becoming more and more digital expecting your customers to come to your branch to do banking is not really an option. And people are also seeing how all the SaaS companies and SaaS businesses, digital businesses, they have really taken off. So if a company like Zoom can suddenly have a a hundred, $150 billion valuation, because you are able to do everything remote, all the enterprises are looking to really touch their customers and partners in a lot more digital way than they could do before. And definitely COVID has also really created this almost, you know, pool buckets of organization. There is lot of companies that have tremendously benefited from it. And there a lot of companies that have been poorly affected, really in a difficult place. And I think both of them for the first category, they are looking at how do I maintain this revenue even after COVID, because one of this thing, you know, hopefully early next year we have a vaccine and things can start to look better again sometime next year. But we have learned so much. We have attracted so many new customers, how do we retain and grow them further? And that means I need to invest more and more in my technology. Now, companies that are not doing well, they really want to figure out how to become more operationally efficient. And they are really under pressure to get more value from there and both categories, improving your revenue, retaining customers. You need to understand the customer behavior. You need to understand which products they are buying at a fine grain level, not with the law of averages, not by looking at a dashboard and saying our average customer likes this kind of product. That one doesn't really work. You have to offer people personalized services and that personalization is just not possible at scale, without really using data on the front lines. You can't have just manager sitting in their office, looking at dashboards and charts and saying these are the kinds of campaigns I need to run because my average customer seems to like these kinds of offers. I need to really empower my sales people, my individual frontline workers, who are interfacing with the customer to be able to make customized offers of services and products to them. And that is possible on the data. So we see a really, a lot more focus in getting value from data, delivering value quickly and digital transformation broadly but definitely leveraging data in businesses. There is tremendous acceleration that is happening and, you know, next five years, it's all going to be about being able to monetize data on the front lines when you are interfacing with your customers and partners >> Ajeet, that's great insight. And I really appreciate what you're saying. And you know, I wrote a blog post in 2007. I said, data will be the new development kit. Back then we used to call development kits, software user development. >> John, you are the real visionary. It took me until 2012 to be able to do this. >> Well, it wasn't clear, but you saw other data was going to have to be programmed be part of the programming. And I think, what you're getting at here is so profound because we're living 2020 people can see the value of data at the right time. It changes the conversations, it changes what's going on in the real time communications of our world with real-time access to information, whether that's machine to machine or machine to human, having data in the right place, changes the context. >> Yap. >> And that is a true, not a tech thing, that's just life, right? I think this year, I think we're going to look back and say, this was the year that everyone realized that real time communications, real-time society needs real time data. And I think it's going to be more important than ever. So it's a really big problem and important one. And thank you for sharing that. >> Yeah. And actually you bring up a very good point programming, developing big data. Data as a development kit. We are also going to announce a new product at Beyond, which will be about bringing ThoughtSpot everywhere, where a lot of business users are in their business applications. And by using ThoughtSpot product, using our full experience, they can obviously do enterprise wide analytics and look at all the data. But if they're looking for insights and nuggets, and they want to ask questions in their business workflows. We are also launching a product capability that will allow software developers to inject data in their business applications and enable and empower their own business users to be able to ask any questions that they might have without having to go to yet another BI product. >> It's data as code. I mean, you almost think about like software metaphors, where's the compiler? Where's the source code? Where's the data code? You start to get into this new mindset of thinking about data as code, because you got to have data about the data. Is it clean data, dirty data? Is it real time? Is it useful? There's a lot of intelligence needed to manage this. This is like a pretty big deal. And it's fairly new in the sense in the science side. Yeah, machine learning has been around for a while and you know, there's tracks for that. But thinking of this way as an operating system mindset, it's not just being a data geek. You know what I'm saying? So I think you're on the right track Ajeet. I really appreciate your thoughts here. Thank you. >> Thank you John. >> Okay. This is a cube conversation. Unpacking the data. The data is the future. We're living in a real-time world and in real-time data can change the outcomes of all kinds of contexts. And with truth, you need data and Ajeet Singh co-founder executive chairman of ThoughtSpot shares his thoughts here in theCUBE. I'm John furrier. Thanks for watching. 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>> Narrator: From around the globe, it's theCUBE. Presenting Accelerating Automation with DevNet. Brought to you by Cisco. >> Hello and welcome to theCUBE. I'm John Furrier, your host. We've got a great conversation and a virtual event, Accelerating Automation with DevNet , Cisco DevNet. And of course we got the Cisco brain trust here. Cube alumni, Susie Wee, Vice President, Senior Vice President, GM, and also CTO of Cisco DevNet and Ecosystem Success CX, all that great stuff. Mandy Whaley, who's the Director, Senior Director of DevNet Certifications, And Eric Thiel, Director of Developer Advocacy, Susie, Mandy, Eric, great to see you. Thanks for coming on. >> Great to see you, John. >> So we're not in person >> It's great to be here. >> We don't, can't be at the DevNet Zone. We can't be on site doing DevNet Create, all the great stuff we've been doing over the past few years. We're virtual, theCUBE virtual. Thanks for coming on. Susie, I got to ask you because you know, we've been talking years ago when you started this mission and just the success you had has been awesome, but DevNet Create has brought on a whole nother connective tissue to the DevNet community. This ties into the theme of accelerating automation with DevNet, because you said to me, I think four years ago, everything should be a service or XaaS as it's called (Susie laughs) and automation plays a critical role. Could you please share your vision because this is really important and still only five to 10% of the enterprises have containerized things. So there's a huge growth curve coming with developing and programmability. What's your vision? >> Yeah, absolutely. I mean, what we know is that as more and more businesses are coming online as, well I mean, they're all online, but as they're growing into the cloud, as they're growing in new areas, as we're dealing with security, as everyone's dealing with the pandemic, there's so many things going on. But what happens is, there's an infrastructure that all of this is built on and that infrastructure has networking, it has security, it has all of your compute and everything that's in there. And what matters is how can you take a business application and tie it to that infrastructure? How can you take, you know, customer data? How can you take business applications? How can you connect up the world securely and then be able to, you know, really satisfy everything that businesses need? And in order to do that, you know, the whole new tool that we've always talked about is that the network is programmable. The infrastructure is programmable, and you don't need just apps riding on top, but now they get to use all of that power of the infrastructure to perform even better. And in order to get there, what you need to do is automate everything. You can't configure networks manually. You can't be manually figuring out policies, but you want to use that agile infrastructure in which you can really use automation, you can rise to higher level business processes and tie all of that up and down the stack by leveraging automation. >> You know, I remember a few years ago when DevNet Create first started, I interviewed Todd Nightingale, and we were talking about Meraki, you know, not to get in the weeds about you know, switches and hubs and wireless. But if you look at what we were talking about then, this is kind of what's going on now. And we were just recently, I think our last physical event was at Cisco Europe in Barcelona before all the COVID hit. And you had >> Susie: Yeah. >> The massive cloud surge and scale happening going on, right when the pandemic hit. And even now more than ever the cloud scale, the modern apps, the momentum hasn't stopped because there's more pressure now to continue addressing more innovation at scale because the pressure to do that, because the businesses need to stay alive. >> Absolutely, yeah. >> I just want to get your thoughts on what's going on in your world, because you were there in person. Now we're six months in, scale is huge. >> We are. Yeah, absolutely. And what happened is as all of our customers, as businesses around the world, as we ourselves all dealt with, how do we run a business from home? You know, how do we keep people safe? How do we keep people at home and how do we work? And then it turns out, you know, business keeps rolling, but we've had to automate even more because you have to go home and then figure out how from home can I make sure that my IT infrastructure is automated? How from home can I make sure that every employee is out there and working safely and securely? You know, things like call center workers, which had to go into physical locations and be in kind of, you know, just, you know, blocked off rooms to really be secure with their company's information. They had to work from home. So we had to extend business applications to people's homes in countries like, you know, well around the world, but also in India where it was actually not, you know, not, they didn't have rules to let people work from home in these areas. So then what we had to do was automate everything and make sure that we could administer, you know, all of our customers could administer these systems from home. So that put extra stress on automation. It put extra stress on our customer's digital transformation and it just forced them to, you know, automate digitally transform quicker. And they had to, because you couldn't just go into a server room and tweak your servers, you had to figure out how to automate all of that. And we're still in that environment today. >> You know one of the hottest trends before the pandemic was observability, Kubernetes microservices. So those things, again, all DevOps and, you know, you guys got some acquisitions, you've bought ThousandEyes, you got a new one. You just bought recently PortShift to raise the game in security, Kuber and all these microservices. So observability super hot, but then people go work at home as you mentioned. How do you (chuckles) >> Yeah What are you observing? The network is under a huge pressure. I mean, it's crashing on people's Zooms and Web Ex's and education, huge amount of network pressure. How are people adapting to this in the app side? How are you guys looking at the, what's being programmed? What are some of the things that you're seeing with use cases around this programmability challenge and observability challenge that's such a huge deal? >> Yeah, absolutely. And you know, going back to Todd Nightingale, right? You know, back when we talked to Todd before, he had Meraki and he had designed this simplicity, this ease of use, this cloud managed, you know, doing everything from one central place. And now he has Cisco's entire enterprise and cloud business. So he is now applying that at that bigger, at that bigger scale for Cisco and for our customers. And he is building in the observability and the dashboards and the automation and the APIs into all of it. But when we take a look at what our customers needed is again, they had to build it all in. They had to build in. And what happened was how your network was doing, how secure your infrastructure was, how well you could enable people to work from home and how well you could reach customers. All of that used to be an IT conversation. It became a CEO and a board-level conversation. So all of a sudden, CEOs were actually, you know, calling on the Heads of IT and the CIO and saying, you know, "How's our VPN connectivity? Is everybody working from home? How many people are connected and able to work and what's their productivity?" So all of a sudden, all these things that were really infrastructure IT stuff became a board level conversation and, you know, once again, at first everybody was panicked and just figuring out how to get people working, but now what we've seen in all of our customers is that they are now building in automation and digital transformation and these architectures, and that gives them a chance to build in that observability, you know, looking for those events, the dashboards, you know, so it really has been fantastic to see what our customers are doing and what our partners are doing to really rise to that next level. >> Susie, I know you got to go, but real quick, describe what accelerating automation with DevNet means. >> (giggles)Well, you've been, you know, we've been working together on DevNet and the vision of the infrastructure programmability and everything for quite some time and the thing that's really happened is yes, you need to automate, but yes, it takes people to do that and you need the right skill sets and the programmability. So a networker can't be a networker. A networker has to be a network automation developer. And so it is about people and it is about bringing infrastructure expertise together with software expertise and letting people run things. Our DevNet community has risen to this challenge. People have jumped in, they've gotten their certifications. We have thousands of people getting certified. You know, we have, you know, Cisco getting certified. We have individuals, we have partners, you know, they're just really rising to the occasion. So accelerating automation, while it is about going digital. It's also about people rising to the level of, you know, being able to put infrastructure and software expertise together to enable this next chapter of business applications, of, you know, cloud directed businesses and cloud growth. So it actually is about people, just as much as it is about automation and technology. >> And we got DevNet Create right around the corner, Virtual, unfortunately, won't be in person, but will be virtual. Susie, thank you for your time. We're going to dig into those people challenges with Mandy and Eric. Thank you for coming on. I know you've got to go, but stay with us. We're going to dig in with Mandy and Eric. Thanks. >> Thank you so much. Have fun. >> Thank you. >> Thanks John. >> Okay. Mandy, you heard Susie, it's about people. And one of the things that's close to your heart, you've been driving as Senior Director of DevNet Certifications, is getting people leveled up. I mean the demand for skills, cybersecurity, network programmability, automation, network design, solution architect, cloud, multi-cloud design. These are new skills that are needed. Can you give us the update on what you're doing to help people get into the acceleration of automation game? >> Oh yes, absolutely. You know, what we've been seeing is a lot of those business drivers, that Susie was mentioning. Those are what's accelerating a lot of the technology changes and that's creating new job roles or new needs on existing job roles where they need new skills. We are seeing customers, partners, people in our community really starting to look at, you know, things like DevSecOps engineer, network automation engineer, network automation developer, which Susie mentioned, and looking at how these fit into their organization, the problems that they solve in their organization. And then how do people build the skills to be able to take on these new job roles or add that job role to their current scope and broaden out and take on new challenges. >> Eric, I want to go to you for a quick second on this piece of getting the certifications. First, before we get started, describe what your role is as Director of Developer Advocacy, because that's always changing and evolving. What's the state of it now because with COVID people are working at home, they have more time to contact Switch, and get some certifications and yet they can code more. What's your role? >> Absolutely. So it's interesting. It definitely is changing a lot. A lot of our, historically a lot of focus for my team has been on those outward events. So going to the DevNet Creates, the Cisco Lives and helping the community connect and to help share technical information with them, doing hands on workshops and really getting people into how do you really start solving these problems? So that's had to pivot quite a bit. Obviously Cisco Live US, we pivoted very quickly to a virtual event when conditions changed. And we're able to actually connect as we found out with a much larger audience. So, you know, as opposed to in person where you're bound by the parameters of, you know, how big the convention center is, we were actually able to reach a worldwide audience with our DevNet Day that was kind of attached onto Cisco Live. And we got great feedback from the audience that now we were actually able to get that same enablement out to so many more people that otherwise might not have been able to make it, but to your broader question of, you know, what my team does. So that's one piece of it is getting that information out to the community. So as part of that, there's a lot of other things we do as well. We are always helping out build new sandboxes, new learning labs, things like that, that they can come and get whenever they're looking for it out on the DevNet site. And then my team also looks after communities, such as the Cisco Learning Network where there's a huge community that has historically been there to support people working on their Cisco certifications. We've seen a huge shift now in that group, that all of the people that have been there for years are now looking at the DevNet certifications and helping other people that are trying to get onboard with programmability. They're taking a lot of those same community enablement skills and propping up the community with helping you answer questions, helping provide content. They've moved now into the DevNet space as well, and are helping people with that set of certifications. So it's great seeing the community come along and really see that. >> I got to ask you on the trends around automation, what skills and what developer patterns are you seeing with automation? Is there anything in particular, obviously network automation has been around for a long time. Cisco has been leader in that, but as you move up the stack as modern applications are building, do you see any patterns or trends around what is accelerating automation? What are people learning? >> Yeah, absolutely. So you mentioned observability was big before COVID and we actually really saw that amplified during COVID. So a lot of people have come to us looking for insights. How can I get that better observability now that we need it while we're virtual. So that's actually been a huge uptick and we've seen a lot of people that weren't necessarily out looking for things before that are now figuring out' how can I do this at scale? And I think one good example that Susie was talking about the VPN example. And we actually had a number of SEs in the Cisco community that had customers dealing with that very thing where they very quickly had to ramp up. And one in particular actually wrote a bunch of automation to go out and measure all of the different parameters that IT departments might care about, about their firewalls, things that you didn't normally look at in the old days. You would size your firewalls based on, you know, assuming a certain number of people working from home. And when that number went to 100%, things like licenses started coming into play, where they needed to make sure they have the right capacity in their platforms that they weren't necessarily designed for. So one of the SEs actually wrote a bunch of code to go out, use some open source tooling to monitor and alert on these things and then published it, so the whole community could go out and get a copy of it, try it out in their own environment. And we saw a lot of interest around that in trying to figure out, okay, now I can take that and I can adapt it to what I need to see for my observability. >> That's great. Mandy, I want to get your thoughts on this too, because as automation continues to scale, it's going to be a focus and people are at home and you guys had a lot of content online for you recorded every session in the DevNet Zone. Learning's going on, sometimes linearly and non linearly. You got the certifications, which is great. That's key, great success there. People are interested, but what other learnings are you seeing? What are people doing? What's the top top trends? >> Yeah. So what we're seeing is like you said, people are at home, they've got time. They want to advance their skillset. And just like any kind of learning, people want choice they want to be able to choose what matches their time that's available and their learning style. So we're seeing some people who want to dive into full online study groups with mentors leading them through a study plan. And we have two new expert-led study groups like that. We're also seeing whole teams at different companies who want to do an immersive learning experience together with projects and office hours and things like that. And we have a new offer that we've been putting together for people who want those kinds of team experiences called Automation Bootcamp. And then we're also seeing individuals who want to be able to, you know, dive into a topic, do a hands-on lab, get some skills, go to the rest of the day of do their work and then come back the next day. And so we have really modular self-driven hands-on learning through the DevNet Fundamentals course, which is available through DevNet. And then there's also people who are saying, "I just want to use the technology. "I like to experiment and then go, you know, "read the instructions, read the manual, "do the deeper learning." And so they're spending a lot of time in our DevNet sandbox, trying out different technologies, Cisco technologies with open source technologies, getting hands-on and building things. And three areas where we're seeing a lot of interest in specific technologies. One is around SD-WAN. There's a huge interest in people skilling up there because of all the reasons that we've been talking about. Security is a focus area where people are dealing with new scale, new kinds of threats, having to deal with them in new ways. and then automating their data center using infrastructure as code type principles. So those are three areas where we're seeing a lot of interest and you'll be hearing some more about that at DevNet Create. >> Awesome. Eric and Mandy, if you guys can wrap up this Accelerating Automation with DevNet package and virtual event here and also tee up DevNet Create because DevNet Create has been a very kind of grassroots, organically building momentum over the years. And again, it's super important cause it's now the app world coming together with networking, you know, end to end programmability and with everything as a service that you guys are doing, everything with APIs, I only can imagine the enablement that's going to create. >> Mandy: Yeah >> Can you share the summary real quick on Accelerating Automation with DevNet and tee up DevNet Create. Mandy, we'll start with you. >> Yes, I'll go first and then Eric can close this out. So just like we've been talking about with you at every DevNet event over the past years, you know, DevNet's bringing APIs across our whole portfolio, and up and down the stack and Accelerating Automation with DevNet , Susie mentioned the people aspect of that. The people skilling up and how that transforms teams, And I think that it's all connected in how businesses are being pushed on their transformation because of current events. That's also a great opportunity for people to advance their careers and take advantage of some of that quickly changing landscape. And so what I think about Accelerating Automation with DevNet, it's about the DevNet community. It's about people getting those new skills and all the creativity and problem solving that will be unleashed by that community with those new skills. >> Eric, take us home here, Accelerating Automation with DevNet and DevNet Create, a lot of developer action going on in Cloud Native right now, your thoughts. >> Absolutely. I think it's exciting. I mentioned the transition to virtual for DevNet Day this year, for Cisco Live and we're seeing, we're able to leverage it even further with Create this year. So, whereas it used to be, you know, confined by the walls that we were within for the event. Now we're actually able to do things like we're adding the Start Now track for people that want to be there. They want to be a developer, a network automation developer for instance, we've now got a track just for them where they can get started and start learning some of the skills they'll need, even if some of the other technical sessions were a little bit deeper than what they were ready for. So I love that we're able to bring that together with the experienced community that we usually do from across the industry bringing us all kinds of innovative talks, talking about ways that they're leveraging technology, leveraging the cloud to do new and interesting things to solve their business challenges. So I'm really excited to bring that whole mix together, as well as getting some of our business units together too and talk straight from their engineering departments. What are they doing? What are they seeing? What are they thinking about when they're building new APIs into their platforms? What problems are they hoping that customers will be able to solve with them? So I think together seeing all of that and then bringing the community together from all of our usual channels. So like I said, Cisco learning network, we've got a ton of community coming together, sharing their ideas and helping each other grow those skills. I see nothing but acceleration ahead of us for automation. >> Awesome. Thanks so much. >> I would >> Go ahead, Mandy. >> Can I add one more thing? >> Add one more thing. >> Yeah, I was just going to say the other really exciting thing about Create this year with the virtual nature of it is that it's happening in three regions and you know, we're so excited to see the people joining from all the different regions and content and speakers and the regions stepping up to have things personalized to their area, to their community. And so that's a whole new experience for DevNet Create that's going to be fantastic this year. >> Yeah, that's it. I was going to close out and just put the final bow on that by saying that you guys have always been successful with great content focused on the people in the community. I think now during, with this virtual DevNet, virtual DevNet create virtual theCUBE virtual, I think we're learning new things. People are working in teams and groups and sharing content, we're going to learn new things. We're going to try new things and ultimately people will rise up and will be resilient. And I think when you have this kind of opportunity, it's really fun. And we'll ride the wave with you guys. >> So thank you so much (Susie laughs) for taking the time to come on theCUBE and talk about your awesome Accelerating Automation and DevNet Create Looking forward to it, thank you. >> Thank you so much, >> All right, thanks a lot. >> Happy to be here. >> Okay, I'm John Furrier with theCUBE virtual here in Palo Alto studios doing the remote content and men, we stay virtual until we're face to face. Thank you so much for watching and we'll see you at DevNet Create. Thanks for watching. (upbeat outro) >> Controller: Okay John, Here we go, John. Here we go. John, we're coming to you in five, four, three, two. >> Hello, and welcome to theCUBE. I'm John Furrier, your host. We've got a great conversation and a virtual event, Accelerating Automation with DevNet, Cisco DevNet. And of course we got the Cisco brain trust here. Cube alumni, Susie Wee, Senior Vice President GM and also CTO at Cisco DevNet and Ecosystem Success CX, all that great stuff. Mandy Whaley, who's the Director, Senior Director of DevNet Certifications, and Eric Thiel, Director of Developer Advocacy. Susie, Mandy, Eric, great to see you. Thanks for coming on. >> Great to see you, John. So we're not in person. >> It's great to be here >> We don't, can't be at the DevNet zone. We can't be on site doing DevNet Create, all the great stuff we've been doing over the past few years. We're virtual, theCUBE virtual. Thanks for coming on. Susie, I got to ask you because you know, we've been talking years ago when you started this mission and just the success you had has been awesome. But DevNet Create has brought on a whole nother connective tissue to the DevNet community. This ties into the theme of Accelerating Automation with DevNet, because you said to me, I think four years ago, everything should be a service or XaaS as it's called. And automation plays (Susie laughs) a critical role. Could you please share your vision because this is really important and still only five to 10% of the enterprises have containerized things. So there's a huge growth curve coming with developing and programmability. What's your vision? >> Yeah, absolutely. I mean, what we know is that as more and more businesses are coming online as ,well I mean, they're all online, but as they're growing into the cloud, as they're growing in new areas, as we're dealing with security, as everyone's dealing with the pandemic, there's so many things going on, but what happens is there's an infrastructure that all of this is built on and that infrastructure has networking. It has security. It has all of your compute and everything that's in there. And what matters is how can you take a business application and tie it to that infrastructure? How can you take, you know, customer data? How can you take business applications? How can you connect up the world securely and then be able to, you know, really satisfy everything that businesses need. And in order to do that, you know, the whole new tool that we've always talked about is that the network is programmable. The infrastructure is programmable and you don't need just apps riding on top, but now they get to use all of that power of the infrastructure to perform even better. And in order to get there, what you need to do is automate everything. You can't configure networks manually. You can't be manually figuring out policies, but you want to use that agile infrastructure in which you can really use automation. You can rise to higher level business processes and tie all of that up and down the stack by leveraging automation. >> You know, I remember a few years ago when DevNet Create first started, I interviewed Todd Nightingale and we were talking about Meraki, you know, not to get in the weeds, but you know, switches and hubs and wireless. But if you look at what we were talking about then, this is kind of what's going on now. And we were just recently, I think our last physical event was Cisco Europe in Barcelona before all the COVID hit. And you had this massive cloud surge and scale happening going on right when the pandemic hit. And even now more than ever, the cloud scale, the modern apps, the momentum hasn't stopped because there's more pressure now to continue addressing more innovation at scale because the pressure to do that because the businesses need >> Absolutely. >> to stay alive. I just want to get your thoughts on what's going on in your world, because you were there in person now we're six months in scale is huge. >> We are. Yeah, absolutely. And what happened is, as all of our customers, as businesses around the world, as we ourselves all dealt with, how do we run a business from home? You know, how do we keep people safe? How do we keep people at home and how do we work? And then it turns out, you know, business keeps rolling, but we've had to automate even more because you have to go home and then figure out how from home, can I make sure that my IT infrastructure is automated? How from home can I make sure that every employee is out there and working safely and securely, you know, things like call center workers, which had to go into physical locations and be in kind of, you know, just, you know, blocked off rooms to really be secure with their company's information. They had to work from home. So we had to extend business applications to people's homes in countries like, you know, well around the world, but also in India where it was actually not, you know, not, they wouldn't let, they didn't have rules to let people work from home in these areas. So then what we had to do was automate everything and make sure that we could administer, you know, all of our customers could administer these systems from home. So that put extra stress on automation. It put extra stress on our customer's digital transformation and it just forced them to, you know, automate, digitally transform quicker. And they had to, because you couldn't just go into a server room and tweak your servers, you had to figure out how to automate all of that. And we're still all in that environment today. >> You know one of the hottest trends before the pandemic was observability, Kubernetes microservices. So those things, again, all DevOps and you know, you guys got some acquisitions, you bought ThousandEyes, you got a new one. You just bought recently PortShift to raise the game in security, Kuber and all these microservices. So observability is super hot, but then people go work at home as you mentioned. How do you observe, what are you observing? The network is under a huge pressure. I mean, it's crashing on people's Zooms and Web Ex's and education, huge amount of network pressure. How are people adapting to this in the app side? How are you guys looking at the, what's being programmed? What are some of the things that you're seeing with use cases around this programmability challenge and observability challenges? It's a huge deal. >> Yeah, absolutely. And you know, going back to Todd Nightingale, right? You know, back when we talked to Todd before he had Meraki and he had designed this simplicity, this ease of use, this cloud managed, you know, doing everything from one central place. And now he has Cisco's entire enterprise and cloud business. So he is now applying that at that bigger scale for Cisco and for our customers and he is building in the observability and the dashboards and the automation and the APIs into all of it. But when we take a look at what our customers needed is again, they had to build it all in. They had to build in. And what happened was how your network was doing, how secure your infrastructure was, how well you could enable people to work from home and how well you could reach customers. All of that used to be an IT conversation. It became a CEO and a board level conversation. So all of a sudden CEOs were actually, you know, calling on the heads of IT and the CIO and saying, you know, how's our VPN connectivity? Is everybody working from home. How many people are you know, connected and able to work and what's their productivity? So all of a sudden, all these things that were really infrastructure IT stuff became a board level conversation. And, you know once again, at first everybody was panicked and just figuring out how to get people working. But now what we've seen in all of our customers is that they are now building in automation and digital transformation and these architectures, and that gives them a chance to build in that observability, you know, looking for those events, the dashboards, you know, so it really has been fantastic to see what our customers are doing and what our partners are doing to really rise to that next level. >> Susie, I know you got to go, but real quick, describe what Accelerating Automation with DevNet means. >> (laughs) Well, you know, we've been working together on DevNet in the vision of the infrastructure programmability and everything for quite some time. And the thing that's really happened is yes, you need to automate, but yes, it takes people to do that and you need the right skill sets and the programmability. So a networker can't be a networker. A networker has to be a network automation developer. And so it is about people and it is about bringing infrastructure expertise together with software expertise and letting people run things. Our DevNet community has risen to this challenge. People have jumped in, they've gotten their certifications. We have thousands of people getting certified. You know, we have, you know, Cisco getting certified. We have individuals, we have partners, you know, they're just really rising to the occasion. So accelerating automation, while it is about going digital, it's also about people rising to the level of, you know, being able to put infrastructure and software expertise together to enable this next chapter of business applications, of you know, cloud directed businesses and cloud growth. So it actually is about people just as much as it is about automation and technology. >> And we got DevNet Create right around the corner virtual, unfortunately won't be in person, but will be virtual. Susie, thank you for your time. We're going to dig into those people challenges with Mandy and Eric. Thank you for coming on. I know got to go, but stay with us. We're going to dig in with Mandy and Eric. Thanks. >> Thank you so much. Have fun. >> Thank you. >> Thanks, John. >> Okay, Mandy, you heard Susie, it's about people. And one of the things that's close to your heart you've been driving is, as senior director of DevNet Certifications is getting people leveled up. I mean the demand for skills, cybersecurity, network programmability, automation, network design, solution architect, cloud multicloud design. These are new skills that are needed. Can you give us the update on what you're doing to help people get into the acceleration of automation game? >> Oh yes, absolutely. You know, what we've been seeing is a lot of those business drivers that Susie was mentioning. Those are what's accelerating a lot of the technology changes and that's creating new job roles or new needs on existing job roles where they need new skills. We are seeing customers, partners, people in our community really starting to look at, you know, things like DevSecOps engineer, network automation engineer, network automation developer which Susie mentioned, and looking at how these fit into their organization, the problems that they solve in their organization. And then how do people build the skills to be able to take on these new job roles or add that job role to their current scope and broaden out and take on new challenges. And this is why we created the DevNet certification. Several years ago, our DevNet community, who's been some of those engineers who have been coming into that software and infrastructure side and meeting. They ask us to help create a more defined pathway to create resources, training, all the things they would need to take all those steps to go after those new jobs. >> Eric, I want to go to you for a quick second on this piece of getting the certifications. First, before we get started, describe what your role is as Director of Developer Advocacy, because that's always changing and evolving. What's the state of it now because with COVID people are working at home, they have more time to contact Switch, and get some certifications and yet they can code more. What's your role >> Absolutely. So it's interesting. It definitely is changing a lot. A lot of our, historically a lot of focus for my team has been on those outward events. So going to the DevNet Creates, the Cisco Lives and helping the community connect and to help share technical information with them, doing hands-on workshops and really getting people into how do you really start solving these problems? So that's had to pivot quite a bit. Obviously Cisco Live US, we pivoted very quickly to a virtual event when conditions changed and we were able to actually connect as we found out with a much larger audience. So, you know, as opposed to in-person where you're bound by the parameters of you know, how big the convention center is. We were actually able to reach a worldwide audience with our DevNet Day that was kind of attached onto Cisco Live. And we got great feedback from the audience that now we were actually able to get that same enablement out to so many more people that otherwise might not have been able to make it, but to your broader question of, you know, what my team does. So that's one piece of it is getting that information out to the community. So as part of that, there's a lot of other things we do as well. We were always helping out build new sandboxes new learning labs, things like that, that they can come and get whenever they're looking for it out on the DevNet site. And then my team also looks after communities such as the Cisco Learning Network where there's a huge community that has historically been there to support people working on their Cisco certifications. And we've seen a huge shift now in that group that all of the people that have been there for years are now looking at the DevNet certifications and helping other people that are trying to get on board with programmability, they're taking a lot of those same community enablement skills and propping up the community with, you know, helping answer questions, helping provide content. They've moved now into the DevNet space as well, and are helping people with that set of certifications. So it's great seeing the community come along and really see that. >> Yeah, I mean, it's awesome, and first of all, you guys done a great job. I'm always impressed when we were at physical events in the DevNet Zone, just the learning, the outreach. Again, very open, collaborative, inclusive, and also, you know, you had one-on-one classes and talks to full blown advanced, (sneezes)Had to sneeze there >> Yeah, and that's the point. >> (laughs)That was coming out, got to cut that out. I love prerecords. >> Absolutely. >> That's never happened to me to live by the way. I've never sneezed live on a thousand--. (Eric laughs) >> You're allergic to me. >> We'll pick up. >> It happens. >> So Eric, so I got to ask you on the trends around automation, what skills and what developer patterns are you seeing with automation? Is there anything in particular? Obviously network automation has been around for a long time. Cisco has been a leader in that, but as you move up the stack, as modern applications are building, do you see any patterns or trends around what is accelerating automation? What are people learning? >> Yeah, absolutely. So you mentioned observability was big before COVID and we actually really saw that amplified during COVID. So a lot of people have come to us looking for insights. How can I get that better observability now that we need it while we're virtual. So that's actually been a huge uptick. And we've seen a lot of people that weren't necessarily out looking for things before that are now figuring out how can I do this at scale? And I think one good example that Susie was talking about the VPN example. And we actually had a number of SEs in the Cisco community that had customers dealing with that very thing where they very quickly had to ramp up. And one in particular actually wrote a bunch of automation to go out and measure all of the different parameters that IT departments might care about, about their firewalls, things that you didn't normally look at in the old days, you would size your firewalls based on, you know, assuming a certain number of people working from home. And when that number went to 100%, things like licensing started coming into play, where they needed to make sure they had the right capacity in their platforms that they weren't necessarily designed for. So one of the SEs actually wrote a bunch of code to go out, used some open source tooling to monitor and alert on these things and then published it, so the whole community could go out and get a copy of it, try it out in their own environment. And we saw a lot of interest around that in trying to figure out, okay, now I can take that and I can adapt it to what I need to see for my observability. >> That's huge and you know, you brought up this sharing concept. I mean, one of the things that's interesting is you've got more sharing going on. >> Controller: John, let's pause right here. Let's pause right here. I'm going to try and bring Eric and Mandy and everybody out. And then just start right from here to bring Eric and Mandy back in and close up. Stand by Eric just hold tight. >> All right, hold on >> Controller: just for one moment. Hold tight, we got Mandy back >> Controller: Standby. Standby. Standby. Standby, standby, standby. Hold hold hold.

>>don't talk mhm, >>Okay, thing is my presentation on coherent nonlinear dynamics and combinatorial optimization. This is going to be a talk to introduce an approach we're taking to the analysis of the performance of coherent using machines. So let me start with a brief introduction to easing optimization. The easing model represents a set of interacting magnetic moments or spins the total energy given by the expression shown at the bottom left of this slide. Here, the signal variables are meditate binary values. The Matrix element J. I. J. Represents the interaction, strength and signed between any pair of spins. I. J and A Chive represents a possible local magnetic field acting on each thing. The easing ground state problem is to find an assignment of binary spin values that achieves the lowest possible value of total energy. And an instance of the easing problem is specified by giving numerical values for the Matrix J in Vector H. Although the easy model originates in physics, we understand the ground state problem to correspond to what would be called quadratic binary optimization in the field of operations research and in fact, in terms of computational complexity theory, it could be established that the easing ground state problem is np complete. Qualitatively speaking, this makes the easing problem a representative sort of hard optimization problem, for which it is expected that the runtime required by any computational algorithm to find exact solutions should, as anatomically scale exponentially with the number of spends and for worst case instances at each end. Of course, there's no reason to believe that the problem instances that actually arrives in practical optimization scenarios are going to be worst case instances. And it's also not generally the case in practical optimization scenarios that we demand absolute optimum solutions. Usually we're more interested in just getting the best solution we can within an affordable cost, where costs may be measured in terms of time, service fees and or energy required for a computation. This focuses great interest on so called heuristic algorithms for the easing problem in other NP complete problems which generally get very good but not guaranteed optimum solutions and run much faster than algorithms that are designed to find absolute Optima. To get some feeling for present day numbers, we can consider the famous traveling salesman problem for which extensive compilations of benchmarking data may be found online. A recent study found that the best known TSP solver required median run times across the Library of Problem instances That scaled is a very steep route exponential for end up to approximately 4500. This gives some indication of the change in runtime scaling for generic as opposed the worst case problem instances. Some of the instances considered in this study were taken from a public library of T SPS derived from real world Veil aside design data. This feels I TSP Library includes instances within ranging from 131 to 744,710 instances from this library with end between 6880 13,584 were first solved just a few years ago in 2017 requiring days of run time and a 48 core to King hurts cluster, while instances with and greater than or equal to 14,233 remain unsolved exactly by any means. Approximate solutions, however, have been found by heuristic methods for all instances in the VLS i TSP library with, for example, a solution within 0.14% of a no lower bound, having been discovered, for instance, with an equal 19,289 requiring approximately two days of run time on a single core of 2.4 gigahertz. Now, if we simple mindedly extrapolate the root exponential scaling from the study up to an equal 4500, we might expect that an exact solver would require something more like a year of run time on the 48 core cluster used for the N equals 13,580 for instance, which shows how much a very small concession on the quality of the solution makes it possible to tackle much larger instances with much lower cost. At the extreme end, the largest TSP ever solved exactly has an equal 85,900. This is an instance derived from 19 eighties VLSI design, and it's required 136 CPU. Years of computation normalized to a single cord, 2.4 gigahertz. But the 24 larger so called world TSP benchmark instance within equals 1,904,711 has been solved approximately within ophthalmology. Gap bounded below 0.474%. Coming back to the general. Practical concerns have applied optimization. We may note that a recent meta study analyzed the performance of no fewer than 37 heuristic algorithms for Max cut and quadratic pioneer optimization problems and found the performance sort and found that different heuristics work best for different problem instances selected from a large scale heterogeneous test bed with some evidence but cryptic structure in terms of what types of problem instances were best solved by any given heuristic. Indeed, their their reasons to believe that these results from Mexico and quadratic binary optimization reflected general principle of performance complementarity among heuristic optimization algorithms in the practice of solving heart optimization problems there. The cerise is a critical pre processing issue of trying to guess which of a number of available good heuristic algorithms should be chosen to tackle a given problem. Instance, assuming that any one of them would incur high costs to run on a large problem, instances incidence, making an astute choice of heuristic is a crucial part of maximizing overall performance. Unfortunately, we still have very little conceptual insight about what makes a specific problem instance, good or bad for any given heuristic optimization algorithm. This has certainly been pinpointed by researchers in the field is a circumstance that must be addressed. So adding this all up, we see that a critical frontier for cutting edge academic research involves both the development of novel heuristic algorithms that deliver better performance, with lower cost on classes of problem instances that are underserved by existing approaches, as well as fundamental research to provide deep conceptual insight into what makes a given problem in, since easy or hard for such algorithms. In fact, these days, as we talk about the end of Moore's law and speculate about a so called second quantum revolution, it's natural to talk not only about novel algorithms for conventional CPUs but also about highly customized special purpose hardware architectures on which we may run entirely unconventional algorithms for combinatorial optimization such as easing problem. So against that backdrop, I'd like to use my remaining time to introduce our work on analysis of coherent using machine architectures and associate ID optimization algorithms. These machines, in general, are a novel class of information processing architectures for solving combinatorial optimization problems by embedding them in the dynamics of analog, physical or cyber physical systems, in contrast to both MAWR traditional engineering approaches that build using machines using conventional electron ICS and more radical proposals that would require large scale quantum entanglement. The emerging paradigm of coherent easing machines leverages coherent nonlinear dynamics in photonic or Opto electronic platforms to enable near term construction of large scale prototypes that leverage post Simoes information dynamics, the general structure of of current CM systems has shown in the figure on the right. The role of the easing spins is played by a train of optical pulses circulating around a fiber optical storage ring. A beam splitter inserted in the ring is used to periodically sample the amplitude of every optical pulse, and the measurement results are continually read into a refugee A, which uses them to compute perturbations to be applied to each pulse by a synchronized optical injections. These perturbations, air engineered to implement the spin, spin coupling and local magnetic field terms of the easing Hamiltonian, corresponding to a linear part of the CME Dynamics, a synchronously pumped parametric amplifier denoted here as PPL and Wave Guide adds a crucial nonlinear component to the CIA and Dynamics as well. In the basic CM algorithm, the pump power starts very low and has gradually increased at low pump powers. The amplitude of the easing spin pulses behaviors continuous, complex variables. Who Israel parts which can be positive or negative, play the role of play the role of soft or perhaps mean field spins once the pump, our crosses the threshold for parametric self oscillation. In the optical fiber ring, however, the attitudes of the easing spin pulses become effectively Qantas ized into binary values while the pump power is being ramped up. The F P J subsystem continuously applies its measurement based feedback. Implementation of the using Hamiltonian terms, the interplay of the linear rised using dynamics implemented by the F P G A and the threshold conversation dynamics provided by the sink pumped Parametric amplifier result in the final state of the optical optical pulse amplitude at the end of the pump ramp that could be read as a binary strain, giving a proposed solution of the easing ground state problem. This method of solving easing problem seems quite different from a conventional algorithm that runs entirely on a digital computer as a crucial aspect of the computation is performed physically by the analog, continuous, coherent, nonlinear dynamics of the optical degrees of freedom. In our efforts to analyze CIA and performance, we have therefore turned to the tools of dynamical systems theory, namely, a study of modifications, the evolution of critical points and apologies of hetero clinic orbits and basins of attraction. We conjecture that such analysis can provide fundamental insight into what makes certain optimization instances hard or easy for coherent using machines and hope that our approach can lead to both improvements of the course, the AM algorithm and a pre processing rubric for rapidly assessing the CME suitability of new instances. Okay, to provide a bit of intuition about how this all works, it may help to consider the threshold dynamics of just one or two optical parametric oscillators in the CME architecture just described. We can think of each of the pulse time slots circulating around the fiber ring, as are presenting an independent Opio. We can think of a single Opio degree of freedom as a single, resonant optical node that experiences linear dissipation, do toe out coupling loss and gain in a pump. Nonlinear crystal has shown in the diagram on the upper left of this slide as the pump power is increased from zero. As in the CME algorithm, the non linear game is initially to low toe overcome linear dissipation, and the Opio field remains in a near vacuum state at a critical threshold. Value gain. Equal participation in the Popeo undergoes a sort of lazing transition, and the study states of the OPIO above this threshold are essentially coherent states. There are actually two possible values of the Opio career in amplitude and any given above threshold pump power which are equal in magnitude but opposite in phase when the OPI across the special diet basically chooses one of the two possible phases randomly, resulting in the generation of a single bit of information. If we consider to uncoupled, Opio has shown in the upper right diagram pumped it exactly the same power at all times. Then, as the pump power has increased through threshold, each Opio will independently choose the phase and thus to random bits are generated for any number of uncoupled. Oppose the threshold power per opio is unchanged from the single Opio case. Now, however, consider a scenario in which the two appeals air, coupled to each other by a mutual injection of their out coupled fields has shown in the diagram on the lower right. One can imagine that depending on the sign of the coupling parameter Alfa, when one Opio is lazing, it will inject a perturbation into the other that may interfere either constructively or destructively, with the feel that it is trying to generate by its own lazing process. As a result, when came easily showed that for Alfa positive, there's an effective ferro magnetic coupling between the two Opio fields and their collective oscillation threshold is lowered from that of the independent Opio case. But on Lee for the two collective oscillation modes in which the two Opio phases are the same for Alfa Negative, the collective oscillation threshold is lowered on Lee for the configurations in which the Opio phases air opposite. So then, looking at how Alfa is related to the J. I. J matrix of the easing spin coupling Hamiltonian, it follows that we could use this simplistic to a p o. C. I am to solve the ground state problem of a fair magnetic or anti ferro magnetic ankles to easing model simply by increasing the pump power from zero and observing what phase relation occurs as the two appeals first start delays. Clearly, we can imagine generalizing this story toe larger, and however the story doesn't stay is clean and simple for all larger problem instances. And to find a more complicated example, we only need to go to n equals four for some choices of J J for n equals, for the story remains simple. Like the n equals two case. The figure on the upper left of this slide shows the energy of various critical points for a non frustrated and equals, for instance, in which the first bifurcated critical point that is the one that I forget to the lowest pump value a. Uh, this first bifurcated critical point flows as symptomatically into the lowest energy easing solution and the figure on the upper right. However, the first bifurcated critical point flows to a very good but sub optimal minimum at large pump power. The global minimum is actually given by a distinct critical critical point that first appears at a higher pump power and is not automatically connected to the origin. The basic C am algorithm is thus not able to find this global minimum. Such non ideal behaviors needs to become more confident. Larger end for the n equals 20 instance, showing the lower plots where the lower right plot is just a zoom into a region of the lower left lot. It can be seen that the global minimum corresponds to a critical point that first appears out of pump parameter, a around 0.16 at some distance from the idiomatic trajectory of the origin. That's curious to note that in both of these small and examples, however, the critical point corresponding to the global minimum appears relatively close to the idiomatic projector of the origin as compared to the most of the other local minima that appear. We're currently working to characterize the face portrait topology between the global minimum in the antibiotic trajectory of the origin, taking clues as to how the basic C am algorithm could be generalized to search for non idiomatic trajectories that jump to the global minimum during the pump ramp. Of course, n equals 20 is still too small to be of interest for practical optimization applications. But the advantage of beginning with the study of small instances is that we're able reliably to determine their global minima and to see how they relate to the 80 about trajectory of the origin in the basic C am algorithm. In the smaller and limit, we can also analyze fully quantum mechanical models of Syrian dynamics. But that's a topic for future talks. Um, existing large scale prototypes are pushing into the range of in equals 10 to the 4 10 to 5 to six. So our ultimate objective in theoretical analysis really has to be to try to say something about CIA and dynamics and regime of much larger in our initial approach to characterizing CIA and behavior in the large in regime relies on the use of random matrix theory, and this connects to prior research on spin classes, SK models and the tap equations etcetera. At present, we're focusing on statistical characterization of the CIA ingredient descent landscape, including the evolution of critical points in their Eigen value spectra. As the pump power is gradually increased. We're investigating, for example, whether there could be some way to exploit differences in the relative stability of the global minimum versus other local minima. We're also working to understand the deleterious or potentially beneficial effects of non ideologies, such as a symmetry in the implemented these and couplings. Looking one step ahead, we plan to move next in the direction of considering more realistic classes of problem instances such as quadratic, binary optimization with constraints. Eso In closing, I should acknowledge people who did the hard work on these things that I've shown eso. My group, including graduate students Ed winning, Daniel Wennberg, Tatsuya Nagamoto and Atsushi Yamamura, have been working in close collaboration with Syria Ganguly, Marty Fair and Amir Safarini Nini, all of us within the Department of Applied Physics at Stanford University. On also in collaboration with the Oshima Moto over at NTT 55 research labs, Onda should acknowledge funding support from the NSF by the Coherent Easing Machines Expedition in computing, also from NTT five research labs, Army Research Office and Exxon Mobil. Uh, that's it. Thanks very much. >>Mhm e >>t research and the Oshie for putting together this program and also the opportunity to speak here. My name is Al Gore ism or Andy and I'm from Caltech, and today I'm going to tell you about the work that we have been doing on networks off optical parametric oscillators and how we have been using them for icing machines and how we're pushing them toward Cornum photonics to acknowledge my team at Caltech, which is now eight graduate students and five researcher and postdocs as well as collaborators from all over the world, including entity research and also the funding from different places, including entity. So this talk is primarily about networks of resonate er's, and these networks are everywhere from nature. For instance, the brain, which is a network of oscillators all the way to optics and photonics and some of the biggest examples or metal materials, which is an array of small resonate er's. And we're recently the field of technological photonics, which is trying thio implement a lot of the technological behaviors of models in the condensed matter, physics in photonics and if you want to extend it even further, some of the implementations off quantum computing are technically networks of quantum oscillators. So we started thinking about these things in the context of icing machines, which is based on the icing problem, which is based on the icing model, which is the simple summation over the spins and spins can be their upward down and the couplings is given by the JJ. And the icing problem is, if you know J I J. What is the spin configuration that gives you the ground state? And this problem is shown to be an MP high problem. So it's computational e important because it's a representative of the MP problems on NPR. Problems are important because first, their heart and standard computers if you use a brute force algorithm and they're everywhere on the application side. That's why there is this demand for making a machine that can target these problems, and hopefully it can provide some meaningful computational benefit compared to the standard digital computers. So I've been building these icing machines based on this building block, which is a degenerate optical parametric. Oscillator on what it is is resonator with non linearity in it, and we pump these resonate er's and we generate the signal at half the frequency of the pump. One vote on a pump splits into two identical photons of signal, and they have some very interesting phase of frequency locking behaviors. And if you look at the phase locking behavior, you realize that you can actually have two possible phase states as the escalation result of these Opio which are off by pie, and that's one of the important characteristics of them. So I want to emphasize a little more on that and I have this mechanical analogy which are basically two simple pendulum. But there are parametric oscillators because I'm going to modulate the parameter of them in this video, which is the length of the string on by that modulation, which is that will make a pump. I'm gonna make a muscular. That'll make a signal which is half the frequency of the pump. And I have two of them to show you that they can acquire these face states so they're still facing frequency lock to the pump. But it can also lead in either the zero pie face states on. The idea is to use this binary phase to represent the binary icing spin. So each opio is going to represent spin, which can be either is your pie or up or down. And to implement the network of these resonate er's, we use the time off blood scheme, and the idea is that we put impulses in the cavity. These pulses air separated by the repetition period that you put in or t r. And you can think about these pulses in one resonator, xaz and temporarily separated synthetic resonate Er's if you want a couple of these resonator is to each other, and now you can introduce these delays, each of which is a multiple of TR. If you look at the shortest delay it couples resonator wanted to 2 to 3 and so on. If you look at the second delay, which is two times a rotation period, the couple's 123 and so on. And if you have and minus one delay lines, then you can have any potential couplings among these synthetic resonate er's. And if I can introduce these modulators in those delay lines so that I can strength, I can control the strength and the phase of these couplings at the right time. Then I can have a program will all toe all connected network in this time off like scheme, and the whole physical size of the system scales linearly with the number of pulses. So the idea of opium based icing machine is didn't having these o pos, each of them can be either zero pie and I can arbitrarily connect them to each other. And then I start with programming this machine to a given icing problem by just setting the couplings and setting the controllers in each of those delight lines. So now I have a network which represents an icing problem. Then the icing problem maps to finding the face state that satisfy maximum number of coupling constraints. And the way it happens is that the icing Hamiltonian maps to the linear loss of the network. And if I start adding gain by just putting pump into the network, then the OPI ohs are expected to oscillate in the lowest, lowest lost state. And, uh and we have been doing these in the past, uh, six or seven years and I'm just going to quickly show you the transition, especially what happened in the first implementation, which was using a free space optical system and then the guided wave implementation in 2016 and the measurement feedback idea which led to increasing the size and doing actual computation with these machines. So I just want to make this distinction here that, um, the first implementation was an all optical interaction. We also had an unequal 16 implementation. And then we transition to this measurement feedback idea, which I'll tell you quickly what it iss on. There's still a lot of ongoing work, especially on the entity side, to make larger machines using the measurement feedback. But I'm gonna mostly focused on the all optical networks and how we're using all optical networks to go beyond simulation of icing Hamiltonian both in the linear and non linear side and also how we're working on miniaturization of these Opio networks. So the first experiment, which was the four opium machine, it was a free space implementation and this is the actual picture off the machine and we implemented a small and it calls for Mexico problem on the machine. So one problem for one experiment and we ran the machine 1000 times, we looked at the state and we always saw it oscillate in one of these, um, ground states of the icing laboratoria. So then the measurement feedback idea was to replace those couplings and the controller with the simulator. So we basically simulated all those coherent interactions on on FB g. A. And we replicated the coherent pulse with respect to all those measurements. And then we injected it back into the cavity and on the near to you still remain. So it still is a non. They're dynamical system, but the linear side is all simulated. So there are lots of questions about if this system is preserving important information or not, or if it's gonna behave better. Computational wars. And that's still ah, lot of ongoing studies. But nevertheless, the reason that this implementation was very interesting is that you don't need the end minus one delight lines so you can just use one. Then you can implement a large machine, and then you can run several thousands of problems in the machine, and then you can compare the performance from the computational perspective Looks so I'm gonna split this idea of opium based icing machine into two parts. One is the linear part, which is if you take out the non linearity out of the resonator and just think about the connections. You can think about this as a simple matrix multiplication scheme. And that's basically what gives you the icing Hambletonian modeling. So the optical laws of this network corresponds to the icing Hamiltonian. And if I just want to show you the example of the n equals for experiment on all those face states and the history Graham that we saw, you can actually calculate the laws of each of those states because all those interferences in the beam splitters and the delay lines are going to give you a different losses. And then you will see that the ground states corresponds to the lowest laws of the actual optical network. If you add the non linearity, the simple way of thinking about what the non linearity does is that it provides to gain, and then you start bringing up the gain so that it hits the loss. Then you go through the game saturation or the threshold which is going to give you this phase bifurcation. So you go either to zero the pie face state. And the expectation is that Theis, the network oscillates in the lowest possible state, the lowest possible loss state. There are some challenges associated with this intensity Durban face transition, which I'm going to briefly talk about. I'm also going to tell you about other types of non aerodynamics that we're looking at on the non air side of these networks. So if you just think about the linear network, we're actually interested in looking at some technological behaviors in these networks. And the difference between looking at the technological behaviors and the icing uh, machine is that now, First of all, we're looking at the type of Hamilton Ian's that are a little different than the icing Hamilton. And one of the biggest difference is is that most of these technological Hamilton Ian's that require breaking the time reversal symmetry, meaning that you go from one spin to in the one side to another side and you get one phase. And if you go back where you get a different phase, and the other thing is that we're not just interested in finding the ground state, we're actually now interesting and looking at all sorts of states and looking at the dynamics and the behaviors of all these states in the network. So we started with the simplest implementation, of course, which is a one d chain of thes resonate, er's, which corresponds to a so called ssh model. In the technological work, we get the similar energy to los mapping and now we can actually look at the band structure on. This is an actual measurement that we get with this associate model and you see how it reasonably how How? Well, it actually follows the prediction and the theory. One of the interesting things about the time multiplexing implementation is that now you have the flexibility of changing the network as you are running the machine. And that's something unique about this time multiplex implementation so that we can actually look at the dynamics. And one example that we have looked at is we can actually go through the transition off going from top A logical to the to the standard nontrivial. I'm sorry to the trivial behavior of the network. You can then look at the edge states and you can also see the trivial and states and the technological at states actually showing up in this network. We have just recently implement on a two D, uh, network with Harper Hofstadter model and when you don't have the results here. But we're one of the other important characteristic of time multiplexing is that you can go to higher and higher dimensions and keeping that flexibility and dynamics, and we can also think about adding non linearity both in a classical and quantum regimes, which is going to give us a lot of exotic, no classical and quantum, non innate behaviors in these networks. Yeah, So I told you about the linear side. Mostly let me just switch gears and talk about the nonlinear side of the network. And the biggest thing that I talked about so far in the icing machine is this face transition that threshold. So the low threshold we have squeezed state in these. Oh, pios, if you increase the pump, we go through this intensity driven phase transition and then we got the face stays above threshold. And this is basically the mechanism off the computation in these O pos, which is through this phase transition below to above threshold. So one of the characteristics of this phase transition is that below threshold, you expect to see quantum states above threshold. You expect to see more classical states or coherent states, and that's basically corresponding to the intensity off the driving pump. So it's really hard to imagine that it can go above threshold. Or you can have this friends transition happen in the all in the quantum regime. And there are also some challenges associated with the intensity homogeneity off the network, which, for example, is if one opioid starts oscillating and then its intensity goes really high. Then it's going to ruin this collective decision making off the network because of the intensity driven face transition nature. So So the question is, can we look at other phase transitions? Can we utilize them for both computing? And also can we bring them to the quantum regime on? I'm going to specifically talk about the face transition in the spectral domain, which is the transition from the so called degenerate regime, which is what I mostly talked about to the non degenerate regime, which happens by just tuning the phase of the cavity. And what is interesting is that this phase transition corresponds to a distinct phase noise behavior. So in the degenerate regime, which we call it the order state, you're gonna have the phase being locked to the phase of the pump. As I talked about non degenerate regime. However, the phase is the phase is mostly dominated by the quantum diffusion. Off the off the phase, which is limited by the so called shallow towns limit, and you can see that transition from the general to non degenerate, which also has distinct symmetry differences. And this transition corresponds to a symmetry breaking in the non degenerate case. The signal can acquire any of those phases on the circle, so it has a you one symmetry. Okay, and if you go to the degenerate case, then that symmetry is broken and you only have zero pie face days I will look at. So now the question is can utilize this phase transition, which is a face driven phase transition, and can we use it for similar computational scheme? So that's one of the questions that were also thinking about. And it's not just this face transition is not just important for computing. It's also interesting from the sensing potentials and this face transition, you can easily bring it below threshold and just operated in the quantum regime. Either Gaussian or non Gaussian. If you make a network of Opio is now, we can see all sorts off more complicated and more interesting phase transitions in the spectral domain. One of them is the first order phase transition, which you get by just coupling to Opio, and that's a very abrupt face transition and compared to the to the single Opio phase transition. And if you do the couplings right, you can actually get a lot of non her mission dynamics and exceptional points, which are actually very interesting to explore both in the classical and quantum regime. And I should also mention that you can think about the cup links to be also nonlinear couplings. And that's another behavior that you can see, especially in the nonlinear in the non degenerate regime. So with that, I basically told you about these Opio networks, how we can think about the linear scheme and the linear behaviors and how we can think about the rich, nonlinear dynamics and non linear behaviors both in the classical and quantum regime. I want to switch gear and tell you a little bit about the miniaturization of these Opio networks. And of course, the motivation is if you look at the electron ICS and what we had 60 or 70 years ago with vacuum tube and how we transition from relatively small scale computers in the order of thousands of nonlinear elements to billions of non elements where we are now with the optics is probably very similar to 70 years ago, which is a table talk implementation. And the question is, how can we utilize nano photonics? I'm gonna just briefly show you the two directions on that which we're working on. One is based on lithium Diabate, and the other is based on even a smaller resonate er's could you? So the work on Nana Photonic lithium naive. It was started in collaboration with Harvard Marko Loncar, and also might affair at Stanford. And, uh, we could show that you can do the periodic polling in the phenomenon of it and get all sorts of very highly nonlinear processes happening in this net. Photonic periodically polls if, um Diabate. And now we're working on building. Opio was based on that kind of photonic the film Diabate. And these air some some examples of the devices that we have been building in the past few months, which I'm not gonna tell you more about. But the O. P. O. S. And the Opio Networks are in the works. And that's not the only way of making large networks. Um, but also I want to point out that The reason that these Nana photonic goblins are actually exciting is not just because you can make a large networks and it can make him compact in a in a small footprint. They also provide some opportunities in terms of the operation regime. On one of them is about making cat states and Opio, which is, can we have the quantum superposition of the zero pie states that I talked about and the Net a photonic within? I've It provides some opportunities to actually get closer to that regime because of the spatial temporal confinement that you can get in these wave guides. So we're doing some theory on that. We're confident that the type of non linearity two losses that it can get with these platforms are actually much higher than what you can get with other platform their existing platforms and to go even smaller. We have been asking the question off. What is the smallest possible Opio that you can make? Then you can think about really wavelength scale type, resonate er's and adding the chi to non linearity and see how and when you can get the Opio to operate. And recently, in collaboration with us see, we have been actually USC and Creole. We have demonstrated that you can use nano lasers and get some spin Hamilton and implementations on those networks. So if you can build the a P. O s, we know that there is a path for implementing Opio Networks on on such a nano scale. So we have looked at these calculations and we try to estimate the threshold of a pos. Let's say for me resonator and it turns out that it can actually be even lower than the type of bulk Pip Llano Pos that we have been building in the past 50 years or so. So we're working on the experiments and we're hoping that we can actually make even larger and larger scale Opio networks. So let me summarize the talk I told you about the opium networks and our work that has been going on on icing machines and the measurement feedback. And I told you about the ongoing work on the all optical implementations both on the linear side and also on the nonlinear behaviors. And I also told you a little bit about the efforts on miniaturization and going to the to the Nano scale. So with that, I would like Thio >>three from the University of Tokyo. Before I thought that would like to thank you showing all the stuff of entity for the invitation and the organization of this online meeting and also would like to say that it has been very exciting to see the growth of this new film lab. And I'm happy to share with you today of some of the recent works that have been done either by me or by character of Hong Kong. Honest Group indicates the title of my talk is a neuro more fic in silica simulator for the communities in machine. And here is the outline I would like to make the case that the simulation in digital Tektronix of the CME can be useful for the better understanding or improving its function principles by new job introducing some ideas from neural networks. This is what I will discuss in the first part and then it will show some proof of concept of the game and performance that can be obtained using dissimulation in the second part and the protection of the performance that can be achieved using a very large chaos simulator in the third part and finally talk about future plans. So first, let me start by comparing recently proposed izing machines using this table there is elected from recent natural tronics paper from the village Park hard people, and this comparison shows that there's always a trade off between energy efficiency, speed and scalability that depends on the physical implementation. So in red, here are the limitation of each of the servers hardware on, interestingly, the F p G, a based systems such as a producer, digital, another uh Toshiba beautification machine or a recently proposed restricted Bozeman machine, FPD A by a group in Berkeley. They offer a good compromise between speed and scalability. And this is why, despite the unique advantage that some of these older hardware have trust as the currency proposition in Fox, CBS or the energy efficiency off memory Sisters uh P. J. O are still an attractive platform for building large organizing machines in the near future. The reason for the good performance of Refugee A is not so much that they operate at the high frequency. No, there are particular in use, efficient, but rather that the physical wiring off its elements can be reconfigured in a way that limits the funding human bottleneck, larger, funny and phenols and the long propagation video information within the system. In this respect, the LPGA is They are interesting from the perspective off the physics off complex systems, but then the physics of the actions on the photos. So to put the performance of these various hardware and perspective, we can look at the competition of bringing the brain the brain complete, using billions of neurons using only 20 watts of power and operates. It's a very theoretically slow, if we can see and so this impressive characteristic, they motivate us to try to investigate. What kind of new inspired principles be useful for designing better izing machines? The idea of this research project in the future collaboration it's to temporary alleviates the limitations that are intrinsic to the realization of an optical cortex in machine shown in the top panel here. By designing a large care simulator in silicone in the bottom here that can be used for digesting the better organization principles of the CIA and this talk, I will talk about three neuro inspired principles that are the symmetry of connections, neural dynamics orphan chaotic because of symmetry, is interconnectivity the infrastructure? No. Next talks are not composed of the reputation of always the same types of non environments of the neurons, but there is a local structure that is repeated. So here's the schematic of the micro column in the cortex. And lastly, the Iraqi co organization of connectivity connectivity is organizing a tree structure in the brain. So here you see a representation of the Iraqi and organization of the monkey cerebral cortex. So how can these principles we used to improve the performance of the icing machines? And it's in sequence stimulation. So, first about the two of principles of the estimate Trian Rico structure. We know that the classical approximation of the car testing machine, which is the ground toe, the rate based on your networks. So in the case of the icing machines, uh, the okay, Scott approximation can be obtained using the trump active in your position, for example, so the times of both of the system they are, they can be described by the following ordinary differential equations on in which, in case of see, I am the X, I represent the in phase component of one GOP Oh, Theo f represents the monitor optical parts, the district optical Parametric amplification and some of the good I JoJo extra represent the coupling, which is done in the case of the measure of feedback coupling cm using oh, more than detection and refugee A and then injection off the cooking time and eso this dynamics in both cases of CNN in your networks, they can be written as the grand set of a potential function V, and this written here, and this potential functionally includes the rising Maccagnan. So this is why it's natural to use this type of, uh, dynamics to solve the icing problem in which the Omega I J or the eyes in coping and the H is the extension of the icing and attorney in India and expect so. Not that this potential function can only be defined if the Omega I j. R. A. Symmetric. So the well known problem of this approach is that this potential function V that we obtain is very non convicts at low temperature, and also one strategy is to gradually deformed this landscape, using so many in process. But there is no theorem. Unfortunately, that granted conventions to the global minimum of There's even Tony and using this approach. And so this is why we propose, uh, to introduce a macro structures of the system where one analog spin or one D O. P. O is replaced by a pair off one another spin and one error, according viable. And the addition of this chemical structure introduces a symmetry in the system, which in terms induces chaotic dynamics, a chaotic search rather than a learning process for searching for the ground state of the icing. Every 20 within this massacre structure the role of the er variable eyes to control the amplitude off the analog spins toe force. The amplitude of the expense toe become equal to certain target amplitude a uh and, uh, and this is done by modulating the strength off the icing complaints or see the the error variable E I multiply the icing complaint here in the dynamics off air d o p. O. On then the dynamics. The whole dynamics described by this coupled equations because the e I do not necessarily take away the same value for the different. I thesis introduces a symmetry in the system, which in turn creates security dynamics, which I'm sure here for solving certain current size off, um, escape problem, Uh, in which the X I are shown here and the i r from here and the value of the icing energy showing the bottom plots. You see this Celtics search that visit various local minima of the as Newtonian and eventually finds the global minimum? Um, it can be shown that this modulation off the target opportunity can be used to destabilize all the local minima off the icing evertonians so that we're gonna do not get stuck in any of them. On more over the other types of attractors I can eventually appear, such as limits I contractors, Okot contractors. They can also be destabilized using the motivation of the target and Batuta. And so we have proposed in the past two different moderation of the target amateur. The first one is a modulation that ensure the uh 100 reproduction rate of the system to become positive on this forbids the creation off any nontrivial tractors. And but in this work, I will talk about another moderation or arrested moderation which is given here. That works, uh, as well as this first uh, moderation, but is easy to be implemented on refugee. So this couple of the question that represent becoming the stimulation of the cortex in machine with some error correction they can be implemented especially efficiently on an F B. G. And here I show the time that it takes to simulate three system and also in red. You see, at the time that it takes to simulate the X I term the EI term, the dot product and the rising Hamiltonian for a system with 500 spins and Iraq Spain's equivalent to 500 g. O. P. S. So >>in >>f b d a. The nonlinear dynamics which, according to the digital optical Parametric amplification that the Opa off the CME can be computed in only 13 clock cycles at 300 yards. So which corresponds to about 0.1 microseconds. And this is Toby, uh, compared to what can be achieved in the measurements back O C. M. In which, if we want to get 500 timer chip Xia Pios with the one she got repetition rate through the obstacle nine narrative. Uh, then way would require 0.5 microseconds toe do this so the submission in F B J can be at least as fast as ah one g repression. Uh, replicate pulsed laser CIA Um, then the DOT product that appears in this differential equation can be completed in 43 clock cycles. That's to say, one microseconds at 15 years. So I pieced for pouring sizes that are larger than 500 speeds. The dot product becomes clearly the bottleneck, and this can be seen by looking at the the skating off the time the numbers of clock cycles a text to compute either the non in your optical parts or the dog products, respect to the problem size. And And if we had infinite amount of resources and PGA to simulate the dynamics, then the non illogical post can could be done in the old one. On the mattress Vector product could be done in the low carrot off, located off scales as a look at it off and and while the guide off end. Because computing the dot product involves assuming all the terms in the product, which is done by a nephew, GE by another tree, which heights scarce logarithmic any with the size of the system. But This is in the case if we had an infinite amount of resources on the LPGA food, but for dealing for larger problems off more than 100 spins. Usually we need to decompose the metrics into ah, smaller blocks with the block side that are not you here. And then the scaling becomes funny, non inner parts linear in the end, over you and for the products in the end of EU square eso typically for low NF pdf cheap PGA you the block size off this matrix is typically about 100. So clearly way want to make you as large as possible in order to maintain this scanning in a log event for the numbers of clock cycles needed to compute the product rather than this and square that occurs if we decompose the metrics into smaller blocks. But the difficulty in, uh, having this larger blocks eyes that having another tree very large Haider tree introduces a large finding and finance and long distance start a path within the refugee. So the solution to get higher performance for a simulator of the contest in machine eyes to get rid of this bottleneck for the dot product by increasing the size of this at the tree. And this can be done by organizing your critique the electrical components within the LPGA in order which is shown here in this, uh, right panel here in order to minimize the finding finance of the system and to minimize the long distance that a path in the in the fpt So I'm not going to the details of how this is implemented LPGA. But just to give you a idea off why the Iraqi Yahiko organization off the system becomes the extremely important toe get good performance for similar organizing machine. So instead of instead of getting into the details of the mpg implementation, I would like to give some few benchmark results off this simulator, uh, off the that that was used as a proof of concept for this idea which is can be found in this archive paper here and here. I should results for solving escape problems. Free connected person, randomly person minus one spring last problems and we sure, as we use as a metric the numbers of the mattress Victor products since it's the bottleneck of the computation, uh, to get the optimal solution of this escape problem with the Nina successful BT against the problem size here and and in red here, this propose FDJ implementation and in ah blue is the numbers of retrospective product that are necessary for the C. I am without error correction to solve this escape programs and in green here for noisy means in an evening which is, uh, behavior with similar to the Cartesian mission. Uh, and so clearly you see that the scaring off the numbers of matrix vector product necessary to solve this problem scales with a better exponents than this other approaches. So So So that's interesting feature of the system and next we can see what is the real time to solution to solve this SK instances eso in the last six years, the time institution in seconds to find a grand state of risk. Instances remain answers probability for different state of the art hardware. So in red is the F B g. A presentation proposing this paper and then the other curve represent Ah, brick a local search in in orange and silver lining in purple, for example. And so you see that the scaring off this purpose simulator is is rather good, and that for larger plant sizes we can get orders of magnitude faster than the state of the art approaches. Moreover, the relatively good scanning off the time to search in respect to problem size uh, they indicate that the FPD implementation would be faster than risk. Other recently proposed izing machine, such as the hope you know, natural complimented on memories distance that is very fast for small problem size in blue here, which is very fast for small problem size. But which scanning is not good on the same thing for the restricted Bosman machine. Implementing a PGA proposed by some group in Broken Recently Again, which is very fast for small parliament sizes but which canning is bad so that a dis worse than the proposed approach so that we can expect that for programs size is larger than 1000 spins. The proposed, of course, would be the faster one. Let me jump toe this other slide and another confirmation that the scheme scales well that you can find the maximum cut values off benchmark sets. The G sets better candidates that have been previously found by any other algorithms, so they are the best known could values to best of our knowledge. And, um or so which is shown in this paper table here in particular, the instances, uh, 14 and 15 of this G set can be We can find better converse than previously known, and we can find this can vary is 100 times faster than the state of the art algorithm and CP to do this which is a very common Kasich. It s not that getting this a good result on the G sets, they do not require ah, particular hard tuning of the parameters. So the tuning issuing here is very simple. It it just depends on the degree off connectivity within each graph. And so this good results on the set indicate that the proposed approach would be a good not only at solving escape problems in this problems, but all the types off graph sizing problems on Mexican province in communities. So given that the performance off the design depends on the height of this other tree, we can try to maximize the height of this other tree on a large F p g a onda and carefully routing the components within the P G A and and we can draw some projections of what type of performance we can achieve in the near future based on the, uh, implementation that we are currently working. So here you see projection for the time to solution way, then next property for solving this escape programs respect to the prime assize. And here, compared to different with such publicizing machines, particularly the digital. And, you know, 42 is shown in the green here, the green line without that's and, uh and we should two different, uh, hypothesis for this productions either that the time to solution scales as exponential off n or that the time of social skills as expression of square root off. So it seems, according to the data, that time solution scares more as an expression of square root of and also we can be sure on this and this production show that we probably can solve prime escape problem of science 2000 spins, uh, to find the rial ground state of this problem with 99 success ability in about 10 seconds, which is much faster than all the other proposed approaches. So one of the future plans for this current is in machine simulator. So the first thing is that we would like to make dissimulation closer to the rial, uh, GOP oh, optical system in particular for a first step to get closer to the system of a measurement back. See, I am. And to do this what is, uh, simulate Herbal on the p a is this quantum, uh, condoms Goshen model that is proposed described in this paper and proposed by people in the in the Entity group. And so the idea of this model is that instead of having the very simple or these and have shown previously, it includes paired all these that take into account on me the mean off the awesome leverage off the, uh, European face component, but also their violence s so that we can take into account more quantum effects off the g o p. O, such as the squeezing. And then we plan toe, make the simulator open access for the members to run their instances on the system. There will be a first version in September that will be just based on the simple common line access for the simulator and in which will have just a classic or approximation of the system. We don't know Sturm, binary weights and museum in term, but then will propose a second version that would extend the current arising machine to Iraq off F p g. A, in which we will add the more refined models truncated, ignoring the bottom Goshen model they just talked about on the support in which he valued waits for the rising problems and support the cement. So we will announce later when this is available and and far right is working >>hard comes from Universal down today in physics department, and I'd like to thank the organizers for their kind invitation to participate in this very interesting and promising workshop. Also like to say that I look forward to collaborations with with a file lab and Yoshi and collaborators on the topics of this world. So today I'll briefly talk about our attempt to understand the fundamental limits off another continues time computing, at least from the point off you off bullion satisfy ability, problem solving, using ordinary differential equations. But I think the issues that we raise, um, during this occasion actually apply to other other approaches on a log approaches as well and into other problems as well. I think everyone here knows what Dorien satisfy ability. Problems are, um, you have boolean variables. You have em clauses. Each of disjunction of collaterals literally is a variable, or it's, uh, negation. And the goal is to find an assignment to the variable, such that order clauses are true. This is a decision type problem from the MP class, which means you can checking polynomial time for satisfy ability off any assignment. And the three set is empty, complete with K three a larger, which means an efficient trees. That's over, uh, implies an efficient source for all the problems in the empty class, because all the problems in the empty class can be reduced in Polian on real time to reset. As a matter of fact, you can reduce the NP complete problems into each other. You can go from three set to set backing or two maximum dependent set, which is a set packing in graph theoretic notions or terms toe the icing graphs. A problem decision version. This is useful, and you're comparing different approaches, working on different kinds of problems when not all the closest can be satisfied. You're looking at the accusation version offset, uh called Max Set. And the goal here is to find assignment that satisfies the maximum number of clauses. And this is from the NPR class. In terms of applications. If we had inefficient sets over or np complete problems over, it was literally, positively influenced. Thousands off problems and applications in industry and and science. I'm not going to read this, but this this, of course, gives a strong motivation toe work on this kind of problems. Now our approach to set solving involves embedding the problem in a continuous space, and you use all the east to do that. So instead of working zeros and ones, we work with minus one across once, and we allow the corresponding variables toe change continuously between the two bounds. We formulate the problem with the help of a close metrics. If if a if a close, uh, does not contain a variable or its negation. The corresponding matrix element is zero. If it contains the variable in positive, for which one contains the variable in a gated for Mitt's negative one, and then we use this to formulate this products caused quote, close violation functions one for every clause, Uh, which really, continuously between zero and one. And they're zero if and only if the clause itself is true. Uh, then we form the define in order to define a dynamic such dynamics in this and dimensional hyper cube where the search happens and if they exist, solutions. They're sitting in some of the corners of this hyper cube. So we define this, uh, energy potential or landscape function shown here in a way that this is zero if and only if all the clauses all the kmc zero or the clauses off satisfied keeping these auxiliary variables a EMS always positive. And therefore, what you do here is a dynamics that is a essentially ingredient descend on this potential energy landscape. If you were to keep all the M's constant that it would get stuck in some local minimum. However, what we do here is we couple it with the dynamics we cooperated the clothes violation functions as shown here. And if he didn't have this am here just just the chaos. For example, you have essentially what case you have positive feedback. You have increasing variable. Uh, but in that case, you still get stuck would still behave will still find. So she is better than the constant version but still would get stuck only when you put here this a m which makes the dynamics in in this variable exponential like uh, only then it keeps searching until he finds a solution on deer is a reason for that. I'm not going toe talk about here, but essentially boils down toe performing a Grady and descend on a globally time barren landscape. And this is what works. Now I'm gonna talk about good or bad and maybe the ugly. Uh, this is, uh, this is What's good is that it's a hyperbolic dynamical system, which means that if you take any domain in the search space that doesn't have a solution in it or any socially than the number of trajectories in it decays exponentially quickly. And the decay rate is a characteristic in variant characteristic off the dynamics itself. Dynamical systems called the escape right the inverse off that is the time scale in which you find solutions by this by this dynamical system, and you can see here some song trajectories that are Kelty because it's it's no linear, but it's transient, chaotic. Give their sources, of course, because eventually knowledge to the solution. Now, in terms of performance here, what you show for a bunch off, um, constraint densities defined by M overran the ratio between closes toe variables for random, said Problems is random. Chris had problems, and they as its function off n And we look at money toward the wartime, the wall clock time and it behaves quite value behaves Azat party nominally until you actually he to reach the set on set transition where the hardest problems are found. But what's more interesting is if you monitor the continuous time t the performance in terms off the A narrow, continuous Time t because that seems to be a polynomial. And the way we show that is, we consider, uh, random case that random three set for a fixed constraint density Onda. We hear what you show here. Is that the right of the trash hold that it's really hard and, uh, the money through the fraction of problems that we have not been able to solve it. We select thousands of problems at that constraint ratio and resolve them without algorithm, and we monitor the fractional problems that have not yet been solved by continuous 90. And this, as you see these decays exponentially different. Educate rates for different system sizes, and in this spot shows that is dedicated behaves polynomial, or actually as a power law. So if you combine these two, you find that the time needed to solve all problems except maybe appear traction off them scales foreign or merely with the problem size. So you have paranormal, continuous time complexity. And this is also true for other types of very hard constraints and sexual problems such as exact cover, because you can always transform them into three set as we discussed before, Ramsey coloring and and on these problems, even algorithms like survey propagation will will fail. But this doesn't mean that P equals NP because what you have first of all, if you were toe implement these equations in a device whose behavior is described by these, uh, the keys. Then, of course, T the continue style variable becomes a physical work off. Time on that will be polynomial is scaling, but you have another other variables. Oxidative variables, which structured in an exponential manner. So if they represent currents or voltages in your realization and it would be an exponential cost Al Qaeda. But this is some kind of trade between time and energy, while I know how toe generate energy or I don't know how to generate time. But I know how to generate energy so it could use for it. But there's other issues as well, especially if you're trying toe do this son and digital machine but also happens. Problems happen appear. Other problems appear on in physical devices as well as we discuss later. So if you implement this in GPU, you can. Then you can get in order off to magnitude. Speed up. And you can also modify this to solve Max sad problems. Uh, quite efficiently. You are competitive with the best heuristic solvers. This is a weather problems. In 2016 Max set competition eso so this this is this is definitely this seems like a good approach, but there's off course interesting limitations, I would say interesting, because it kind of makes you think about what it means and how you can exploit this thes observations in understanding better on a low continues time complexity. If you monitored the discrete number the number of discrete steps. Don't buy the room, Dakota integrator. When you solve this on a digital machine, you're using some kind of integrator. Um and you're using the same approach. But now you measure the number off problems you haven't sold by given number of this kid, uh, steps taken by the integrator. You find out you have exponential, discrete time, complexity and, of course, thistles. A problem. And if you look closely, what happens even though the analog mathematical trajectory, that's the record here. If you monitor what happens in discrete time, uh, the integrator frustrates very little. So this is like, you know, third or for the disposition, but fluctuates like crazy. So it really is like the intervention frees us out. And this is because of the phenomenon of stiffness that are I'll talk a little bit a more about little bit layer eso. >>You know, it might look >>like an integration issue on digital machines that you could improve and could definitely improve. But actually issues bigger than that. It's It's deeper than that, because on a digital machine there is no time energy conversion. So the outside variables are efficiently representing a digital machine. So there's no exponential fluctuating current of wattage in your computer when you do this. Eso If it is not equal NP then the exponential time, complexity or exponential costs complexity has to hit you somewhere. And this is how um, but, you know, one would be tempted to think maybe this wouldn't be an issue in a analog device, and to some extent is true on our devices can be ordered to maintain faster, but they also suffer from their own problems because he not gonna be affect. That classes soldiers as well. So, indeed, if you look at other systems like Mirandizing machine measurement feedback, probably talk on the grass or selected networks. They're all hinge on some kind off our ability to control your variables in arbitrary, high precision and a certain networks you want toe read out across frequencies in case off CM's. You required identical and program because which is hard to keep, and they kind of fluctuate away from one another, shift away from one another. And if you control that, of course that you can control the performance. So actually one can ask if whether or not this is a universal bottleneck and it seems so aside, I will argue next. Um, we can recall a fundamental result by by showing harder in reaction Target from 1978. Who says that it's a purely computer science proof that if you are able toe, compute the addition multiplication division off riel variables with infinite precision, then you could solve any complete problems in polynomial time. It doesn't actually proposals all where he just chose mathematically that this would be the case. Now, of course, in Real warned, you have also precision. So the next question is, how does that affect the competition about problems? This is what you're after. Lots of precision means information also, or entropy production. Eso what you're really looking at the relationship between hardness and cost of computing off a problem. Uh, and according to Sean Hagar, there's this left branch which in principle could be polynomial time. But the question whether or not this is achievable that is not achievable, but something more cheerful. That's on the right hand side. There's always going to be some information loss, so mental degeneration that could keep you away from possibly from point normal time. So this is what we like to understand, and this information laws the source off. This is not just always I will argue, uh, in any physical system, but it's also off algorithm nature, so that is a questionable area or approach. But China gets results. Security theoretical. No, actual solar is proposed. So we can ask, you know, just theoretically get out off. Curiosity would in principle be such soldiers because it is not proposing a soldier with such properties. In principle, if if you want to look mathematically precisely what the solar does would have the right properties on, I argue. Yes, I don't have a mathematical proof, but I have some arguments that that would be the case. And this is the case for actually our city there solver that if you could calculate its trajectory in a loss this way, then it would be, uh, would solve epic complete problems in polynomial continuous time. Now, as a matter of fact, this a bit more difficult question, because time in all these can be re scared however you want. So what? Burns says that you actually have to measure the length of the trajectory, which is a new variant off the dynamical system or property dynamical system, not off its parameters ization. And we did that. So Suba Corral, my student did that first, improving on the stiffness off the problem off the integrations, using implicit solvers and some smart tricks such that you actually are closer to the actual trajectory and using the same approach. You know what fraction off problems you can solve? We did not give the length of the trajectory. You find that it is putting on nearly scaling the problem sites we have putting on your skin complexity. That means that our solar is both Polly length and, as it is, defined it also poorly time analog solver. But if you look at as a discreet algorithm, if you measure the discrete steps on a digital machine, it is an exponential solver. And the reason is because off all these stiffness, every integrator has tow truck it digitizing truncate the equations, and what it has to do is to keep the integration between the so called stability region for for that scheme, and you have to keep this product within a grimace of Jacoby in and the step size read in this region. If you use explicit methods. You want to stay within this region? Uh, but what happens that some off the Eigen values grow fast for Steve problems, and then you're you're forced to reduce that t so the product stays in this bonded domain, which means that now you have to you're forced to take smaller and smaller times, So you're you're freezing out the integration and what I will show you. That's the case. Now you can move to increase its soldiers, which is which is a tree. In this case, you have to make domain is actually on the outside. But what happens in this case is some of the Eigen values of the Jacobean, also, for six systems, start to move to zero. As they're moving to zero, they're going to enter this instability region, so your soul is going to try to keep it out, so it's going to increase the data T. But if you increase that to increase the truncation hours, so you get randomized, uh, in the large search space, so it's it's really not, uh, not going to work out. Now, one can sort off introduce a theory or language to discuss computational and are computational complexity, using the language from dynamical systems theory. But basically I I don't have time to go into this, but you have for heart problems. Security object the chaotic satellite Ouch! In the middle of the search space somewhere, and that dictates how the dynamics happens and variant properties off the dynamics. Of course, off that saddle is what the targets performance and many things, so a new, important measure that we find that it's also helpful in describing thesis. Another complexity is the so called called Makarov, or metric entropy and basically what this does in an intuitive A eyes, uh, to describe the rate at which the uncertainty containing the insignificant digits off a trajectory in the back, the flow towards the significant ones as you lose information because off arrows being, uh grown or are developed in tow. Larger errors in an exponential at an exponential rate because you have positively up north spawning. But this is an in variant property. It's the property of the set of all. This is not how you compute them, and it's really the interesting create off accuracy philosopher dynamical system. A zay said that you have in such a high dimensional that I'm consistent were positive and negatively upon of exponents. Aziz Many The total is the dimension of space and user dimension, the number off unstable manifold dimensions and as Saddam was stable, manifold direction. And there's an interesting and I think, important passion, equality, equality called the passion, equality that connect the information theoretic aspect the rate off information loss with the geometric rate of which trajectory separate minus kappa, which is the escape rate that I already talked about. Now one can actually prove a simple theorems like back off the envelope calculation. The idea here is that you know the rate at which the largest rated, which closely started trajectory separate from one another. So now you can say that, uh, that is fine, as long as my trajectory finds the solution before the projective separate too quickly. In that case, I can have the hope that if I start from some region off the face base, several close early started trajectories, they kind of go into the same solution orphaned and and that's that's That's this upper bound of this limit, and it is really showing that it has to be. It's an exponentially small number. What? It depends on the end dependence off the exponents right here, which combines information loss rate and the social time performance. So these, if this exponents here or that has a large independence or river linear independence, then you then you really have to start, uh, trajectories exponentially closer to one another in orderto end up in the same order. So this is sort off like the direction that you're going in tow, and this formulation is applicable toe all dynamical systems, uh, deterministic dynamical systems. And I think we can We can expand this further because, uh, there is, ah, way off getting the expression for the escaped rate in terms off n the number of variables from cycle expansions that I don't have time to talk about. What? It's kind of like a program that you can try toe pursuit, and this is it. So the conclusions I think of self explanatory I think there is a lot of future in in, uh, in an allo. Continue start computing. Um, they can be efficient by orders of magnitude and digital ones in solving empty heart problems because, first of all, many of the systems you like the phone line and bottleneck. There's parallelism involved, and and you can also have a large spectrum or continues time, time dynamical algorithms than discrete ones. And you know. But we also have to be mindful off. What are the possibility of what are the limits? And 11 open question is very important. Open question is, you know, what are these limits? Is there some kind off no go theory? And that tells you that you can never perform better than this limit or that limit? And I think that's that's the exciting part toe to derive thes thes this levian 10.

>>Hi everyone, This system A fellow from the University of Tokyo before I thought that would like to thank you she and all the stuff of entity for the invitation and the organization of this online meeting and also would like to say that it has been very exciting to see the growth of this new film lab. And I'm happy to share with you today or some of the recent works that have been done either by me or by character of Hong Kong Noise Group indicating the title of my talk is a neuro more fic in silica simulator for the commenters in machine. And here is the outline I would like to make the case that the simulation in digital Tektronix of the CME can be useful for the better understanding or improving its function principles by new job introducing some ideas from neural networks. This is what I will discuss in the first part and then I will show some proof of concept of the game in performance that can be obtained using dissimulation in the second part and the production of the performance that can be achieved using a very large chaos simulator in the third part and finally talk about future plans. So first, let me start by comparing recently proposed izing machines using this table there is adapted from a recent natural tronics paper from the Village Back hard People. And this comparison shows that there's always a trade off between energy efficiency, speed and scalability that depends on the physical implementation. So in red, here are the limitation of each of the servers hardware on, Interestingly, the F p G, a based systems such as a producer, digital, another uh Toshiba purification machine, or a recently proposed restricted Bozeman machine, FPD eight, by a group in Berkeley. They offer a good compromise between speed and scalability. And this is why, despite the unique advantage that some of these older hardware have trust as the currency proposition influx you beat or the energy efficiency off memory sisters uh P. J. O are still an attractive platform for building large theorizing machines in the near future. The reason for the good performance of Refugee A is not so much that they operate at the high frequency. No, there are particle in use, efficient, but rather that the physical wiring off its elements can be reconfigured in a way that limits the funding human bottleneck, larger, funny and phenols and the long propagation video information within the system in this respect, the f. D. A s. They are interesting from the perspective, off the physics off complex systems, but then the physics of the actions on the photos. So to put the performance of these various hardware and perspective, we can look at the competition of bringing the brain the brain complete, using billions of neurons using only 20 watts of power and operates. It's a very theoretically slow, if we can see. And so this impressive characteristic, they motivate us to try to investigate. What kind of new inspired principles be useful for designing better izing machines? The idea of this research project in the future collaboration it's to temporary alleviates the limitations that are intrinsic to the realization of an optical cortex in machine shown in the top panel here. By designing a large care simulator in silicone in the bottom here that can be used for suggesting the better organization principles of the CIA and this talk, I will talk about three neuro inspired principles that are the symmetry of connections, neural dynamics. Orphan, chaotic because of symmetry, is interconnectivity. The infrastructure. No neck talks are not composed of the reputation of always the same types of non environments of the neurons, but there is a local structure that is repeated. So here's a schematic of the micro column in the cortex. And lastly, the Iraqi co organization of connectivity connectivity is organizing a tree structure in the brain. So here you see a representation of the Iraqi and organization of the monkey cerebral cortex. So how can these principles we used to improve the performance of the icing machines? And it's in sequence stimulation. So, first about the two of principles of the estimate Trian Rico structure. We know that the classical approximation of the Cortes in machine, which is a growing toe the rate based on your networks. So in the case of the icing machines, uh, the okay, Scott approximation can be obtained using the trump active in your position, for example, so the times of both of the system they are, they can be described by the following ordinary differential equations on in which, in case of see, I am the X, I represent the in phase component of one GOP Oh, Theo F represents the monitor optical parts, the district optical parametric amplification and some of the good I JoJo extra represent the coupling, which is done in the case of the measure of feedback cooking cm using oh, more than detection and refugee A then injection off the cooking time and eso this dynamics in both cases of CME in your networks, they can be written as the grand set of a potential function V, and this written here, and this potential functionally includes the rising Maccagnan. So this is why it's natural to use this type of, uh, dynamics to solve the icing problem in which the Omega I J or the Eyes in coping and the H is the extension of the rising and attorney in India and expect so. >>Not that this potential function can only be defined if the Omega I j. R. A. Symmetric. So the well known problem of >>this approach is that this potential function V that we obtain is very non convicts at low temperature, and also one strategy is to gradually deformed this landscape, using so many in process. But there is no theorem. Unfortunately, that granted convergence to the global minimum of there's even 20 and using this approach. And so this is >>why we propose toe introduce a macro structure the system or where one analog spin or one D o. P. O is replaced by a pair off one and knock spin and one error on cutting. Viable. And the addition of this chemical structure introduces a symmetry in the system, which in terms induces chaotic dynamics, a chaotic search rather than a >>learning process for searching for the ground state of the icing. Every 20 >>within this massacre structure the role of the ER variable eyes to control the amplitude off the analog spins to force the amplitude of the expense toe, become equal to certain target amplitude. A Andi. This is known by moderating the strength off the icing complaints or see the the error variable e I multiply the icing complain here in the dynamics off UH, D o p o on Then the dynamics. The whole dynamics described by this coupled equations because the e I do not necessarily take away the same value for the different, I think introduces a >>symmetry in the system, which in turn creates chaotic dynamics, which I'm showing here for solving certain current size off, um, escape problem, Uh, in which the exiled from here in the i r. From here and the value of the icing energy is shown in the bottom plots. And you see this Celtics search that visit various local minima of the as Newtonian and eventually finds the local minima Um, >>it can be shown that this modulation off the target opportunity can be used to destabilize all the local minima off the icing hamiltonian so that we're gonna do not get stuck in any of them. On more over the other types of attractors, I can eventually appear, such as the limits of contractors or quality contractors. They can also be destabilized using a moderation of the target amplitude. And so we have proposed in the past two different motivation of the target constitute the first one is a moderation that ensure the 100 >>reproduction rate of the system to become positive on this forbids the creation of any non tree retractors. And but in this work I will talk about another modulation or Uresti moderation, which is given here that works, uh, as well as this first, uh, moderation, but is easy to be implemented on refugee. >>So this couple of the question that represent the current the stimulation of the cortex in machine with some error correction, they can be implemented especially efficiently on an F B G. And here I show the time that it takes to simulate three system and eso in red. You see, at the time that it takes to simulate the X, I term the EI term, the dot product and the rising everything. Yet for a system with 500 spins analog Spain's equivalent to 500 g. O. P. S. So in f b d a. The nonlinear dynamics which, according to the digital optical Parametric amplification that the Opa off the CME can be computed in only 13 clock cycles at 300 yards. So which corresponds to about 0.1 microseconds. And this is Toby, uh, compared to what can be achieved in the measurements tobacco cm in which, if we want to get 500 timer chip Xia Pios with the one she got repetition rate through the obstacle nine narrative. Uh, then way would require 0.5 microseconds toe do this so the submission in F B J can be at least as fast as, ah one gear repression to replicate the post phaser CIA. Um, then the DOT product that appears in this differential equation can be completed in 43 clock cycles. That's to say, one microseconds at 15 years. So I pieced for pouring sizes that are larger than 500 speeds. The dot product becomes clearly the bottleneck, and this can be seen by looking at the the skating off the time the numbers of clock cycles a text to compute either the non in your optical parts, all the dog products, respect to the problem size. And and if we had a new infinite amount of resources and PGA to simulate the dynamics, then the non in optical post can could be done in the old one. On the mattress Vector product could be done in the low carrot off, located off scales as a low carrot off end and while the kite off end. Because computing the dot product involves the summing, all the terms in the products, which is done by a nephew, Jay by another tree, which heights scares a logarithmic any with the size of the system. But this is in the case if we had an infinite amount of resources on the LPGA food but for dealing for larger problems off more than 100 spins, usually we need to decompose the metrics into ah smaller blocks with the block side that are not you here. And then the scaling becomes funny non inner parts linear in the and over you and for the products in the end of you square eso typically for low NF pdf cheap P a. You know you the block size off this matrix is typically about 100. So clearly way want to make you as large as possible in order to maintain this scanning in a log event for the numbers of clock cycles needed to compute the product rather than this and square that occurs if we decompose the metrics into smaller blocks. But the difficulty in, uh, having this larger blocks eyes that having another tree very large Haider tree introduces a large finding and finance and long distance started path within the refugee. So the solution to get higher performance for a simulator of the contest in machine eyes to get rid of this bottleneck for the dot product. By increasing the size of this at the tree and this can be done by organizing Yeah, click the extra co components within the F p G A in order which is shown here in this right panel here in order to minimize the finding finance of the system and to minimize the long distance that the path in the in the fpt So I'm not going to the details of how this is implemented the PGA. But just to give you a new idea off why the Iraqi Yahiko organization off the system becomes extremely important toe get good performance for simulator organizing mission. So instead of instead of getting into the details of the mpg implementation, I would like to give some few benchmark results off this simulator, uh, off the that that was used as a proof of concept for this idea which is can be found in this archive paper here and here. I should result for solving escape problems, free connected person, randomly person minus one, spin last problems and we sure, as we use as a metric the numbers >>of the mattress Victor products since it's the bottleneck of the computation, uh, to get the optimal solution of this escape problem with Nina successful BT against the problem size here and and in red here there's propose F B J implementation and in ah blue is the numbers of retrospective product that are necessary for the C. I am without error correction to solve this escape programs and in green here for noisy means in an evening which is, uh, behavior. It's similar to the car testing machine >>and security. You see that the scaling off the numbers of metrics victor product necessary to solve this problem scales with a better exponents than this other approaches. So so So that's interesting feature of the system and next we can see what is the real time to solution. To solve this, SK instances eso in the last six years, the time institution in seconds >>to find a grand state of risk. Instances remain answers is possibility for different state of the art hardware. So in red is the F B G. A presentation proposing this paper and then the other curve represent ah, brick, a local search in in orange and center dining in purple, for example, and So you see that the scaring off this purpose simulator is is rather good and that for larger politicizes, we can get orders of magnitude faster than the state of the other approaches. >>Moreover, the relatively good scanning off the time to search in respect to problem size uh, they indicate that the FBT implementation would be faster than risk Other recently proposed izing machine, such as the Hope you know network implemented on Memory Sisters. That is very fast for small problem size in blue here, which is very fast for small problem size. But which scanning is not good on the same thing for the >>restricted Bosman machine implemented a PGA proposed by some group in Brooklyn recently again, which is very fast for small promise sizes. But which canning is bad So that, uh, this worse than the purpose approach so that we can expect that for promise sizes larger than, let's say, 1000 spins. The purpose, of course, would be the faster one. >>Let me jump toe this other slide and another confirmation that the scheme scales well that you can find the maximum cut values off benchmark sets. The G sets better cut values that have been previously found by any other >>algorithms. So they are the best known could values to best of our knowledge. And, um, or so which is shown in this paper table here in particular, the instances, Uh, 14 and 15 of this G set can be We can find better converse than previously >>known, and we can find this can vary is 100 times >>faster than the state of the art algorithm and cp to do this which is a recount. Kasich, it s not that getting this a good result on the G sets, they do not require ah, particular hard tuning of the parameters. So the tuning issuing here is very simple. It it just depends on the degree off connectivity within each graph. And so this good results on the set indicate that the proposed approach would be a good not only at solving escape problems in this problems, but all the types off graph sizing problems on Mexican province in communities. >>So given that the performance off the design depends on the height of this other tree, we can try to maximize the height of this other tree on a large F p g A onda and carefully routing the trickle components within the P G A. And and we can draw some projections of what type of performance we can achieve in >>the near future based on the, uh, implementation that we are currently working. So here you see projection for the time to solution way, then next property for solving this escape problems respect to the prime assize. And here, compared to different with such publicizing machines, particularly the digital and, you know, free to is shown in the green here, the green >>line without that's and, uh and we should two different, uh, prosthesis for this productions either that the time to solution scales as exponential off n or that >>the time of social skills as expression of square root off. So it seems according to the data, that time solution scares more as an expression of square root of and also we can be sure >>on this and this production showed that we probably can solve Prime Escape Program of Science 2000 spins to find the rial ground state of this problem with 99 success ability in about 10 seconds, which is much faster than all the other proposed approaches. So one of the future plans for this current is in machine simulator. So the first thing is that we would like to make dissimulation closer to the rial, uh, GOP or optical system in particular for a first step to get closer to the system of a measurement back. See, I am. And to do this, what is, uh, simulate Herbal on the p a is this quantum, uh, condoms Goshen model that is proposed described in this paper and proposed by people in the in the Entity group. And so the idea of this model is that instead of having the very simple or these and have shown previously, it includes paired all these that take into account out on me the mean off the awesome leverage off the, uh, European face component, but also their violence s so that we can take into account more quantum effects off the g o p. O, such as the squeezing. And then we plan toe, make the simulator open access for the members to run their instances on the system. There will be a first version in September that will >>be just based on the simple common line access for the simulator and in which will have just a classical approximation of the system. We don't know Sturm, binary weights and Museum in >>term, but then will propose a second version that would extend the current arising machine to Iraq off eight f p g. A. In which we will add the more refined models truncated bigger in the bottom question model that just talked about on the supports in which he valued waits for the rising problems and support the cement. So we will announce >>later when this is available, and Farah is working hard to get the first version available sometime in September. Thank you all, and we'll be happy to answer any questions that you have.