(upbeat music) (upbeat music) >> Hi everybody, welcome back to our coverage of the Cloud Native Security Con. I'm Dave Vellante, here in our Boston studio. We're connecting today with Palo Alto, with John Furrier and Lisa Martin. We're also live from the show floor in Seattle. But right now, I'm here with Andy Thurai who's from Constellation Research, friend of theCUBE, and we're going to discuss the intersection of AI and security, the potential of AI, the risks and the future. Andy, welcome, good to see you again. >> Good to be here again. >> Hey, so let's get into it, can you talk a little bit about, I know this is a passion of yours, the ethical considerations surrounding AI. I mean, it's front and center in the news, and you've got accountability, privacy, security, biases. Should we be worried about AI from a security perspective? >> Absolutely, man, you should be worried. See the problem is, people don't realize this, right? I mean, the ChatGPT being a new shiny object, it's all the craze that's about. But the problem is, most of the content that's produced either by ChatGPT or even by others, it's an access, no warranties, no accountability, no whatsoever. Particularly, if it is content, it's okay. But if it is something like a code that you use for example, one of their site projects that GitHub's co-pilot, which is actually, open AI + Microsoft + GitHub's combo, they allow you to produce code, AI writes code basically, right? But when you write code, problem with that is, it's not exactly stolen, but the models are created by using the GitHub code. Actually, they're getting sued for that, saying that, "You can't use our code". Actually there's a guy, Tim Davidson, I think he's named the professor, he actually demonstrated how AI produces exact copy of the code that he has written. So right now, it's a lot of security, accountability, privacy issues. Use it either to train or to learn. But in my view, it's not ready for enterprise grade yet. >> So, Brian Behlendorf today in his keynotes said he's really worried about ChatGPT being used to automate spearfishing. So I'm like, okay, so let's unpack that a little bit. Is the concern there that it just, the ChatGPT writes such compelling phishing content, it's going to increase the probability of somebody clicking on it, or are there other dimensions? >> It could, it's not necessarily just ChatGPT for that matter, right? AI can, actually, the hackers are using it to an extent already, can use to individualize content. For example, one of the things that you are able to easily identify when you're looking at the emails that are coming in, the phishing attack is, you look at some of the key elements in it, whether it's a human or even if it's an automated AI based system. They look at certain things and they say, "Okay, this is phishing". But if you were to read an email that looks exact copy of what I would've sent to you saying that, "Hey Dave, are you on for tomorrow? Or click on this link to do whatever. It could individualize the message. That's where the volume at scale to individual to masses, that can be done using AI, which is what scares me. >> Is there a flip side to AI? How is it being utilized to help cybersecurity? And maybe you could talk about some of the more successful examples of AI in security. Like, are there use cases or are there companies out there, Andy, that you find, I know you're close to a lot of firms that are leading in this area. You and I have talked about CrowdStrike, I know Palo Alto Network, so is there a positive side to this story? >> Yeah, I mean, absolutely right. Those are some of the good companies you mentioned, CrowdStrike, Palo Alto, Darktrace is another one that I closely follow, which is a good company as well, that they're using AI for security purposes. So, here's the thing, right, when people say, when they're using malware detection systems, most of the malware detection systems that are in today's security and malware systems, use some sort of a signature and pattern scanning in the malware. You know how many identified malwares are there today in the repository, in the library? More than a billion, a billion. So, if you are to check for every malware in your repository, that's not going to work. The pattern based recognition is not going to work. So, you got to figure out a different way of identification of pattern of usage, not just a signature in a malware, right? Or there are other areas you could use, things like the usage patterns. For example, if Andy is coming in to work at a certain time, you could combine a facial recognition saying, that should he be in here at that time, and should he be doing things, what he is supposed to be doing. There are a lot of things you could do using that, right? And the AIOps use cases, which is one of my favorite areas that I work, do a lot of work, right? That it has use cases for detecting things that are anomaly, that are not supposed to be done in a way that's supposed to be, reducing the noise so it can escalate only the things what you're supposed to. So, AIOps is a great use case to use in security areas which they're not using it to an extent yet. Incident management is another area. >> So, in your malware example, you're saying, okay, known malware, pretty much anybody can deal with that now. That's sort of yesterday's problem. >> The unknown is the problem. >> It's the unknown malware really trying to understand the patterns, and the patterns are going to change. It's not like you're saying a common signature 'cause they're going to use AI to change things up at scale. >> So, here's the problem, right? The malware writers are also using AI now, right? So, they're not going to write the old malware, send it to you. They are actually creating malware on the fly. It is possible entirely in today's world that they can create a malware, drop in your systems and it'll it look for the, let me get that name right. It's called, what are we using here? It's called the TTPs, Tactics, Techniques and procedures. It'll look for that to figure out, okay, am I doing the right pattern? And then malware can sense it saying that, okay, that's the one they're detecting. I'm going to change it on the fly. So, AI can code itself on the fly, rather malware can code itself on the fly, which is going to be hard to detect. >> Well, and when you talk about TTP, when you talk to folks like Kevin Mandia of Mandiant, recently purchased by Google or other of those, the ones that have the big observation space, they'll talk about the most malicious hacks that they see, involve lateral movement. So, that's obviously something that people are looking for, AI's looking for that. And of course, the hackers are going to try to mask that lateral movement, living off the land and other things. How do you see AI impacting the future of cyber? We talked about the risks and the good. One of the things that Brian Behlendorf also mentioned is that, he pointed out that in the early days of the internet, the protocols had an inherent element of trust involved. So, things like SMTP, they didn't have security built in. So, they built up a lot of technical debt. Do you see AI being able to help with that? What steps do you see being taken to ensure that AI based systems are secure? >> So, the major difference between the older systems and the newer systems is the older systems, sadly even today, a lot of them are rules-based. If it's a rules-based systems, you are dead in the water and not able, right? So, the AI-based systems can somewhat learn from the patterns as I was talking about, for example... >> When you say rules-based systems, you mean here's the policy, here's the rule, if it's not followed but then you're saying, AI will blow that away, >> AI will blow that away, you don't have to necessarily codify things saying that, okay, if this, then do this. You don't have to necessarily do that. AI can somewhat to an extent self-learn saying that, okay, if that doesn't happen, if this is not a pattern that I know which is supposed to happen, who should I escalate this to? Who does this system belong to? And the other thing, the AIOps use case we talked about, right, the anomalies. When an anomaly happens, then the system can closely look at, saying that, okay, this is not normal behavior or usage. Is that because system's being overused or is it because somebody's trying to access something, could look at the anomaly detection, anomaly prevention or even prediction to an extent. And that's where AI could be very useful. >> So, how about the developer angle? 'Cause CNCF, the event in Seattle is all around developers, how can AI be integrated? We did a lot of talk at the conference about shift-left, we talked about shift-left and protect right. Meaning, protect the run time. So, both are important, so what steps should be taken to ensure that the AI systems are being developed in a secure and ethically sound way? What's the role of developers in that regard? >> How long do you got? (Both laughing) I think it could go for base on that. So, here's the problem, right? Lot of these companies are trying to see, I mean, you might have seen that in the news that Buzzfeed is trying to hire all of the writers to create the thing that ChatGPT is creating, a lot of enterprises... >> How, they're going to fire their writers? >> Yeah, they replace the writers. >> It's like automated automated vehicles and automated Uber drivers. >> So, the problem is a lot of enterprises still haven't done that, at least the ones I'm speaking to, are thinking about saying, "Hey, you know what, can I replace my developers because they are so expensive? Can I replace them with AI generated code?" There are a few issues with that. One, AI generated code is based on some sort of a snippet of a code that has been already available. So, you get into copyright issues, that's issue number one, right? Issue number two, if AI creates code and if something were to go wrong, who's responsible for that? There's no accountability right now. Or you as a company that's creating a system that's responsible, or is it ChatGPT, Microsoft is responsible. >> Or is the developer? >> Or the developer. >> The individual developer might be. So, they're going to be cautious about that liability. >> Well, so one of the areas where I'm seeing a lot of enterprises using this is they are using it to teach developers to learn things. You know what, if you're to code, this is a good way to code. That area, it's okay because you are just teaching them. But if you are to put an actual production code, this is what I advise companies, look, if somebody's using even to create a code, whether with or without your permission, make sure that once the code is committed, you validate that the 100%, whether it's a code or a model, or even make sure that the data what you're feeding in it is completely out of bias or no bias, right? Because at the end of the day, it doesn't matter who, what, when did that, if you put out a service or a system out there, it is involving your company liability and system, and code in place. You're going to be screwed regardless of what, if something were to go wrong, you are the first person who's liable for it. >> Andy, when you think about the dangers of AI, and what keeps you up at night if you're a security professional AI and security professional. We talked about ChatGPT doing things, we don't even, the hackers are going to get creative. But what worries you the most when you think about this topic? >> A lot, a lot, right? Let's start off with an example, actually, I don't know if you had a chance to see that or not. The hackers used a bank of Hong Kong, used a defect mechanism to fool Bank of Hong Kong to transfer $35 million to a fake account, the money is gone, right? And the problem that is, what they did was, they interacted with a manager and they learned this executive who can control a big account and cloned his voice, and clone his patterns on how he calls and what he talks and the whole name he has, after learning that, they call the branch manager or bank manager and say, "Hey, you know what, hey, move this much money to whatever." So, that's one way of kind of phishing, kind of deep fake that can come. So, that's just one example. Imagine whether business is conducted by just using voice or phone calls itself. That's an area of concern if you were to do that. And imagine this became an uproar a few years back when deepfakes put out the video of Tom Cruise and others we talked about in the past, right? And Tom Cruise looked at the video, he said that he couldn't distinguish that he didn't do it. It is so close, that close, right? And they are doing things like they're using gems... >> Awesome Instagram account by the way, the guy's hilarious, right? >> So, they they're using a lot of this fake videos and fake stuff. As long as it's only for entertainment purposes, good. But imagine doing... >> That's right there but... >> But during the election season when people were to put out saying that, okay, this current president or ex-president, he said what? And the masses believe right now whatever they're seeing in TV, that's unfortunate thing. I mean, there's no fact checking involved, and you could change governments and elections using that, which is scary shit, right? >> When you think about 2016, that was when we really first saw, the weaponization of social, the heavy use of social and then 2020 was like, wow. >> To the next level. >> It was crazy. The polarization, 2024, would deepfakes... >> Could be the next level, yeah. >> I mean, it's just going to escalate. What about public policy? I want to pick your brain on this because I I've seen situations where the EU, for example, is going to restrict the ability to ship certain code if it's involved with critical infrastructure. So, let's say, example, you're running a nuclear facility and you've got the code that protects that facility, and it can be useful against some other malware that's outside of that country, but you're restricted from sending that for whatever reason, data sovereignty. Is public policy, is it aligned with the objectives in this new world? Or, I mean, normally they have to catch up. Is that going to be a problem in your view? >> It is because, when it comes to laws it's always miles behind when a new innovation happens. It's not just for AI, right? I mean, the same thing happened with IOT. Same thing happened with whatever else new emerging tech you have. The laws have to understand if there's an issue and they have to see a continued pattern of misuse of the technology, then they'll come up with that. Use in ways they are ahead of things. So, they put a lot of restrictions in place and about what AI can or cannot do, US is way behind on that, right? But California has done some things, for example, if you are talking to a chat bot, then you have to basically disclose that to the customer, saying that you're talking to a chat bot, not to a human. And that's just a very basic rule that they have in place. I mean, there are times that when a decision is made by the, problem is, AI is a black box now. The decision making is also a black box now, and we don't tell people. And the problem is if you tell people, you'll get sued immediately because every single time, we talked about that last time, there are cases involving AI making decisions, it gets thrown out the window all the time. If you can't substantiate that. So, the bottom line is that, yes, AI can assist and help you in making decisions but just use that as a assistant mechanism. A human has to be always in all the loop, right? >> Will AI help with, in your view, with supply chain, the software supply chain security or is it, it's always a balance, right? I mean, I feel like the attackers are more advanced in some ways, it's like they're on offense, let's say, right? So, when you're calling the plays, you know where you're going, the defense has to respond to it. So in that sense, the hackers have an advantage. So, what's the balance with software supply chain? Are the hackers have the advantage because they can use AI to accelerate their penetration of the software supply chain? Or will AI in your view be a good defensive mechanism? >> It could be but the problem is, the velocity and veracity of things can be done using AI, whether it's fishing, or malware, or other security and the vulnerability scanning the whole nine yards. It's scary because the hackers have a full advantage right now. And actually, I think ChatGPT recently put out two things. One is, it's able to direct the code if it is generated by ChatGPT. So basically, if you're trying to fake because a lot of schools were complaining about it, that's why they came up with the mechanism. So, if you're trying to create a fake, there's a mechanism for them to identify. But that's a step behind still, right? And the hackers are using things to their advantage. Actually ChatGPT made a rule, if you go there and read the terms and conditions, it's basically honor rule suggesting, you can't use this for certain purposes, to create a model where it creates a security threat, as that people are going to listen. So, if there's a way or mechanism to restrict hackers from using these technologies, that would be great. But I don't see that happening. So, know that these guys have an advantage, know that they're using AI, and you have to do things to be prepared. One thing I was mentioning about is, if somebody writes a code, if somebody commits a code right now, the problem is with the agile methodologies. If somebody writes a code, if they commit a code, you assume that's right and legit, you immediately push it out into production because need for speed is there, right? But if you continue to do that with the AI produced code, you're screwed. >> So, bottom line is, AI's going to speed us up in a security context or is it going to slow us down? >> Well, in the current version, the AI systems are flawed because even the ChatGPT, if you look at the the large language models, you look at the core piece of data that's available in the world as of today and then train them using that model, using the data, right? But people are forgetting that's based on today's data. The data changes on a second basis or on a minute basis. So, if I want to do something based on tomorrow or a day after, you have to retrain the models. So, the data already have a stale. So, that in itself is stale and the cost for retraining is going to be a problem too. So overall, AI is a good first step. Use that with a caution, is what I want to say. The system is flawed now, if you use it as is, you'll be screwed, it's dangerous. >> Andy, you got to go, thanks so much for coming in, appreciate it. >> Thanks for having me. >> You're very welcome, so we're going wall to wall with our coverage of the Cloud Native Security Con. I'm Dave Vellante in the Boston Studio, John Furrier, Lisa Martin and Palo Alto. We're going to be live on the show floor as well, bringing in keynote speakers and others on the ground. Keep it right there for more coverage on theCUBE. (upbeat music) (upbeat music) (upbeat music) (upbeat music)

(upbeat music) >> Hey, everyone, welcome back to Las Vegas, "theCube" is on our fourth day of covering AWS re:Invent, live from the Venetian Expo Center. This week has been amazing. We've created a ton of content, as you know, 'cause you've been watching. But, there's been north of 55,000 people here, hundreds of thousands online. We've had amazing conversations across the AWS ecosystem. Lisa Martin, Paul Gillan. Paul, what's your, kind of, take on day four of the conference? It's still highly packed. >> Oh, there's lots of people here. (laughs) >> Yep. Unusual for the final day of a conference. I think Werner Vogels, if I'm pronouncing it right kicked things off today when he talked about asymmetry and how the world is, you know, asymmetric. We build symmetric software, because it's convenient to do so, but asymmetric software actually scales and evolves much better. And I think that that was a conversation starter for a lot of what people are talking about here today, which is how the cloud changes the way we think about building software. >> Absolutely does. >> Our next guest, Holger Mueller, that's one of his key areas of focus. And Holger, welcome, thanks for joining us on the "theCube". >> Thanks for having me. >> What did you take away from the keynote this morning? >> Well, how do you feel on the final day of the marathon, right? We're like 23, 24 miles. Hit the ball yesterday, right? >> We are going strong Holger. And, of course, >> Yeah. >> you guys, we can either talk about business transformation with cloud or the World Cup. >> Or we can do both. >> The World Cup, hands down. World Cup. (Lisa laughs) Germany's out, I'm unbiased now. They just got eliminated. >> Spain is out now. >> What will the U.S. do against Netherlands tomorrow? >> They're going to win. What's your forecast? U.S. will win? >> They're going to win 2 to 1. >> What do you say, 2:1? >> I'm optimistic, but realistic. >> 3? >> I think Netherlands. >> Netherlands will win? >> 2 to nothing. >> Okay, I'll vote for the U.S.. >> Okay, okay >> 3:1 for the U.S.. >> Be optimistic. >> Root for the U.S.. >> Okay, I like that. >> Hope for the best wherever you work. >> Tomorrow you'll see how much soccer experts we are. >> If your prediction was right. (laughs) >> (laughs) Ja, ja. Or yours was right, right, so. Cool, no, but the event, I think the event is great to have 50,000 people. Biggest event of the year again, right? Not yet the 70,000 we had in 2019. But it's great to have the energy. I've never seen the show floor going all the way down like this, right? >> I haven't either. >> I've never seen that. I think it's a record. Often vendors get the space here and they have the keynote area, and the entertainment area, >> Yeah. >> and the food area, and then there's an exposition, right? This is packed. >> It's packed. >> Maybe it'll pay off. >> You don't see the big empty booths that you often see. >> Oh no. >> Exactly, exactly. You know, the white spaces and so on. >> No. >> Right. >> Which is a good thing. >> There's lots of energy, which is great. And today's, of course, the developer day, like you said before, right now Vogels' a rockstar in the developer community, right. Revered visionary on what has been built, right? And he's becoming a little professorial is my feeling, right. He had these moments before too, when it was justifying how AWS moved off the Oracle database about the importance of data warehouses and structures and why DynamoDB is better and so on. But, he had a large part of this too, and this coming right across the keynotes, right? Adam Selipsky talking about Antarctica, right? Scott against almonds and what went wrong. He didn't tell us, by the way, which often the tech winners forget. Scott banked on technology. He had motorized sleds, which failed after three miles. So, that's not the story to tell the technology. Let everything down. Everybody went back to ponies and horses and dogs. >> Maybe goes back to these asynchronous behavior. >> Yeah. >> The way of nature. >> And, yesterday, Swami talking about the bridges, right? The root bridges, right? >> Right. >> So, how could Werner pick up with his video at the beginning. >> Yeah. >> And then talk about space and other things? So I think it's important to educate about event-based architecture, right? And we see this massive transformation. Modern software has to be event based, right? Because, that's how things work and we didn't think like this before. I see this massive transformation in my other research area in other platforms about the HR space, where payrolls are being rebuilt completely. And payroll used to be one of the three peaks of ERP, right? You would size your ERP machine before the cloud to financial close, to run the payroll, and to do an MRP manufacturing run if you're manufacturing. God forbid you run those three at the same time. Your machine wouldn't be able to do that, right? So it was like start the engine, start the boosters, we are running payroll. And now the modern payroll designs like you see from ADP or from Ceridian, they're taking every payroll relevant event. You check in time wise, right? You go overtime, you take a day of vacation and right away they trigger and run the payroll, so it's up to date for you, up to date for you, which, in this economy, is super important, because we have more gig workers, we have more contractors, we have employees who are leaving suddenly, right? The great resignation, which is happening. So, from that perspective, it's the modern way of building software. So it's great to see Werner showing that. The dirty little secrets though is that is more efficient software for the cloud platform vendor too. Takes less resources, gets less committed things, so it's a much more scalable architecture. You can move the events, you can work asynchronously much better. And the biggest showcase, right? What's the biggest transactional showcase for an eventually consistent asynchronous transactional application? I know it's a mouthful, but we at Amazon, AWS, Amazon, right? You buy something on Amazon they tell you it's going to come tomorrow. >> Yep. >> They don't know it's going to come tomorrow by that time, because it's not transactionally consistent, right? We're just making every ERP vendor, who lives in transactional work, having nightmares of course, (Lisa laughs) but for them it's like, yes we have the delivery to promise, a promise to do that, right? But they come back to you and say, "Sorry, we couldn't make it, delivery didn't work and so on. It's going to be a new date. We are out of the product.", right? So these kind of event base asynchronous things are more and more what's going to scale around the world. It's going to be efficient for everybody, it's going to be better customer experience, better employee experience, ultimately better user experience, it's going to be better for the enterprise to build, but we have to learn to build it. So big announcement was to build our environment to build better eventful applications from today. >> Talk about... This is the first re:Invent... Well, actually, I'm sorry, it's the second re:Invent under Adam Selipsky. >> Right. Adam Selipsky, yep. >> But his first year. >> Right >> We're hearing a lot of momentum. What's your takeaway with what he delivered with the direction Amazon is going, their vision? >> Ja, I think compared to the Jassy times, right, we didn't see the hockey stick slide, right? With a number of innovations and releases. That was done in 2019 too, right? So I think it's a more pedestrian pace, which, ultimately, is good for everybody, because it means that when software vendors go slower, they do less width, but more depth. >> Yeah. >> And depth is what customers need. So Amazon's building more on the depth side, which is good news. I also think, and that's not official, right, but Adam Selipsky came from Tableau, right? >> Yeah. So he is a BI analytics guy. So it's no surprise we have three data lake offerings, right? Security data lake, we have a healthcare data lake and we have a supply chain data lake, right? Where all, again, the epigonos mentioned them I was like, "Oh, my god, Amazon's coming to supply chain.", but it's actually data lakes, which is an interesting part. But, I think it's not a surprise that someone who comes heavily out of the analytics BI world, it's off ringside, if I was pitching internally to him maybe I'd do something which he's is familiar with and I think that's what we see in the major announcement of his keynote on Tuesday. >> I mean, speaking of analytics, one of the big announcements early on was Amazon is trying to bridge the gap between Aurora. >> Yep. >> And Redshift. >> Right. >> And setting up for continuous pipelines, continuous integration. >> Right. >> Seems to be a trend that is common to all database players. I mean, Oracle is doing the same thing. SAP is doing the same thing. MariaDB. Do you see the distinction between transactional and analytical databases going away? >> It's coming together, right? Certainly coming together, from that perspective, but there's a fundamental different starting point, right? And with the big idea part, right? The universal database, which does everything for you in one system, whereas the suite of specialized databases, right? Oracle is in the classic Oracle database in the universal database camp. On the other side you have Amazon, which built a database. This is one of the first few Amazon re:Invents. It's my 10th where there was no new database announced. Right? >> No. >> So it was always add another one specially- >> I think they have enough. >> It's a great approach. They have enough, right? So it's a great approach to build something quick, which Amazon is all about. It's not so great when customers want to leverage things. And, ultimately, which I think with Selipsky, AWS is waking up to the enterprise saying, "I have all this different database and what is in them matters to me." >> Yeah. >> "So how can I get this better?" So no surprise between the two most popular database, Aurora and RDS. They're bring together the data with some out of the box parts. I think it's kind of, like, silly when Swami's saying, "Hey, no ETL.". (chuckles) Right? >> Yeah. >> There shouldn't be an ETL from the same vendor, right? There should be data pipes from that perspective anyway. So it looks like, on the overall value proposition database side, AWS is moving closer to the universal database on the Oracle side, right? Because, if you lift, of course, the universal database, under the hood, you see, well, there's different database there, different part there, you do something there, you have to configure stuff, which is also the case but it's one part of it, right, so. >> With that shift, talk about the value that's going to be in it for customers regardless of industry. >> Well, the value for customers is great, because when software vendors, or platform vendors, go in depth, you get more functionality, you get more maturity you get easier ways of setting up the whole things. You get ways of maintaining things. And you, ultimately, get lower TCO to build them, which is super important for enterprise. Because, here, this is the developer cloud, right? Developers love AWS. Developers are scarce, expensive. Might not be want to work for you, right? So developer velocity getting more done with same amount of developers, getting less done, less developers getting more done, is super crucial, super important. So this is all good news for enterprise banking on AWS and then providing them more efficiency, more automation, out of the box. >> Some of your customer conversations this week, talk to us about some of the feedback. What's the common denominator amongst customers right now? >> Customers are excited. First of all, like, first event, again in person, large, right? >> Yeah. >> People can travel, people meet each other, meet in person. They have a good handle around the complexity, which used to be a huge challenge in the past, because people say, "Do I do this?" I know so many CXOs saying, "Yeah, I want to build, say, something in IoT with AWS. The first reference built it like this, the next reference built it completely different. The third one built it completely different again. So now I'm doubting if my team has the skills to build things successfully, because will they be smart enough, like your teams, because there's no repetitiveness and that repetitiveness is going to be very important for AWS to come up with some higher packaging and version numbers.", right? But customers like that message. They like that things are working better together. They're not missing the big announcement, right? One of the traditional things of AWS would be, and they made it even proud, as a system, Jassy was saying, "If we look at the IT spend and we see something which is, like, high margin for us and not served well and we announced something there, right?" So Quick Start, Workspaces, where all liaisons where AWS went after traditional IT spend and had an offering. We haven't had this in 2019, we don't have them in 2020. Last year and didn't have it now. So something is changing on the AWS side. It's a little bit too early to figure out what, but they're not chewing off as many big things as they used in the past. >> Right. >> Yep. >> Did you get the sense that... Keith Townsend, from "The CTO Advisor", was on earlier. >> Yep. >> And he said he's been to many re:Invents, as you have, and he said that he got the sense that this is Amazon's chance to do a victory lap, as he called it. That this is a way for Amazon to reinforce the leadership cloud. >> Ja. >> And really, kind of, establish that nobody can come close to them, nobody can compete with them. >> You don't think that- >> I don't think that's at all... I mean, love Keith, he's a great guy, but I don't think that's the mindset at all, right? So, I mean, Jassy was always saying, "It's still the morning of the day in the cloud.", right? They're far away from being done. They're obsessed over being right. They do more work with the analysts. We think we got something right. And I like the passion, from that perspective. So I think Amazon's far from being complacent and the area, which is the biggest bit, right, the biggest. The only thing where Amazon truly has floundered, always floundered, is the AI space, right? So, 2018, Werner Vogels was doing more technical stuff that "Oh, this is all about linear regression.", right? And Amazon didn't start to put algorithms on silicon, right? And they have a three four trail and they didn't announce anything new here, behind Google who's been doing this for much, much longer than TPU platform, so. >> But they have now. >> They're keen aware. >> Yep. >> They now have three, or they own two of their own hardware platforms for AI. >> Right. >> They support the Intel platform. They seem to be catching up in that area. >> It's very hard to catch up on hardware, right? Because, there's release cycles, right? And just the volume that, just talking about the largest models that we have right now, to do with the language models, and Google is just doing a side note of saying, "Oh, we supported 50 less or 30 less, not little spoken languages, which I've never even heard of, because they're under banked and under supported and here's the language model, right? And I think it's all about little bit the organizational DNA of a company. I'm a strong believer in that. And, you have to remember AWS comes from the retail side, right? >> Yeah. >> Their roll out of data centers follows their retail strategy. Open secret, right? But, the same thing as the scale of the AI is very very different than if you take a look over at Google where it makes sense of the internet, right? The scale right away >> Right. >> is a solution, which is a good solution for some of the DNA of AWS. Also, Microsoft Azure is good. There has no chance to even get off the ship of that at Google, right? And these leaders with Google and it's not getting smaller, right? We didn't hear anything. I mean so much focused on data. Why do they focus so much on data? Because, data is the first step for AI. If AWS was doing a victory lap, data would've been done. They would own data, right? They would have a competitor to BigQuery Omni from the Google side to get data from the different clouds. There's crickets on that topic, right? So I think they know that they're catching up on the AI side, but it's really, really hard. It's not like in software where you can't acquire someone they could acquire in video. >> Not at Core Donovan. >> Might play a game, but that's not a good idea, right? So you can't, there's no shortcuts on the hardware side. As much as I'm a software guy and love software and don't like hardware, it's always a pain, right? There's no shortcuts there and there's nothing, which I think, has a new Artanium instance, of course, certainly, but they're not catching up. The distance is the same, yep. >> One of the things is funny, one of our guests, I think it was Tuesday, it was, it was right after Adam's keynote. >> Sure. >> Said that Adam Selipsky stood up on stage and talked about data for 52 minutes. >> Yeah. Right. >> It was timed, 52 minutes. >> Right. >> Huge emphasis on that. One of the things that Adam said to John Furrier when they were able to sit down >> Yeah >> a week or so ago at an event preview, was that CIOs and CEOs are not coming to Adam to talk about technology. They want to talk about transformation. They want to talk about business transformation. >> Sure, yes, yes. >> Talk to me in our last couple of minutes about what CEOs and CIOs are coming to you saying, "Holger, help us figure this out. We have to transform the business." >> Right. So we advise, I'm going quote our friends at Gartner, once the type A company. So we'll use technology aggressively, right? So take everything in the audience with a grain of salt, followers are the laggards, and so on. So for them, it's really the cusp of doing AI, right? Getting that data together. It has to be in the cloud. We live in the air of infinite computing. The cloud makes computing infinite, both from a storage, from a compute perspective, from an AI perspective, and then define new business models and create new best practices on top of that. Because, in the past, everything was fine out on premise, right? We talked about the (indistinct) size. Now in the cloud, it's just the business model to say, "Do I want to have a little more AI? Do I want a to run a little more? Will it give me the insight in the business?". So, that's the transformation that is happening, really. So, bringing your data together, this live conversation data, but not for bringing the data together. There's often the big win for the business for the first time to see the data. AWS is banking on that. The supply chain product, as an example. So many disparate systems, bring them them together. Big win for the business. But, the win for the business, ultimately, is when you change the paradigm from the user showing up to do something, to software doing stuff for us, right? >> Right. >> We have too much in this operator paradigm. If the user doesn't show up, doesn't find the click, doesn't find where to go, nothing happens. It can't be done in the 21st century, right? Software has to look over your shoulder. >> Good point. >> Understand one for you, autonomous self-driving systems. That's what CXOs, who're future looking, will be talked to come to AWS and all the other cloud vendors. >> Got it, last question for you. We're making a sizzle reel on Instagram. >> Yeah. >> If you had, like, a phrase, like, or a 30 second pitch that would describe re:Invent 2022 in the direction the company's going. What would that elevator pitch say? >> 30 second pitch? >> Yeah. >> All right, just timing. AWS is doing well. It's providing more depth, less breadth. Making things work together. It's catching up in some areas, has some interesting offerings, like the healthcare offering, the security data lake offering, which might change some things in the industry. It's staying the course and it's going strong. >> Ah, beautifully said, Holger. Thank you so much for joining Paul and me. >> Might have been too short. I don't know. (laughs) >> About 10 seconds left over. >> It was perfect, absolutely perfect. >> Thanks for having me. >> Perfect sizzle reel. >> Appreciate it. >> We appreciate your insights, what you're seeing this week, and the direction the company is going. We can't wait to see what happens in the next year. And, yeah. >> Thanks for having me. >> And of course, we've been on so many times. We know we're going to have you back. (laughs) >> Looking forward to it, thank you. >> All right, for Holger Mueller and Paul Gillan, I'm Lisa Martin. You're watching "theCube", the leader in live enterprise and emerging tech coverage. (upbeat music)

>>Hey guys. Welcome back to the Cubes coverage of Ansible Fast 2022. This is day two of our wall to wall coverage. Lisa Martin here with John Ferer. John, we're seeing this world where companies are saying if we can't automate it, we need to, The automation market is transforming. There's been a lot of buzz about that. A lot of technical chops here at Ansible Fest. >>Yeah, I mean, we've got a great guest here coming on Cuba alumni, Dean Newman, future room. He travels every event he's got. He's got his nose to the grindstone ear to the ground. Great analysis. I mean, we're gonna get into why it's important. How does Ansible fit into the big picture? It's really gonna be a great segment. The >>Board do it well, John just did my job for me about, I'll introduce him again. Daniel Newman, one of our alumni is Back Principal Analyst at Future and Research. Great to have you back on the cube. >>Yeah, it's good to join you. Excited to be back in Chicago. I don't know if you guys knew this, but for 40 years, this was my hometown. Now I don't necessarily brag about that anymore. I'm, I live in Austin now. I'm a proud Texan, but I did grow up here actually out in the west suburbs. I got off the plane, I felt the cold air, and I almost turned around and said, Does this thing go back? Yeah. Cause I'm, I've, I've grown thin skin. It did not take me long. I, I like the warm, Come on, >>I'm the saying, I'm from California and I got off the plane Monday. I went, Whoa, I need a coat. And I was in Miami a week ago and it was 85. >>Oh goodness. >>Crazy. So you just flew in. Talk about what's going on, your take on, on Ansible. We've talked a lot with the community, with partners, with customers, a lot of momentum. The flywheel of the community is going around and round and round. What are some of your perspectives that you see? >>Yeah, absolutely. Well, let's you know, I'm gonna take a quick step back. We're entering an era where companies are gonna have to figure out how to do more with less. Okay? We've got exponential data growth, we've got more architectural complexity than ever before. Companies are trying to discern how to deal with many different environments. And just at a macro level, Red Hat is one of the companies that is almost certainly gonna be part of this multi-cloud hybrid cloud era. So that should initially give a lot of confidence to the buying group that are looking at how to automate their environments. You're automating workflows, but really with, with Ansible, we're focused on automating it, automating the network. So as companies are kind of dig out, we're entering this recessionary period, Okay, we're gonna call it what it is. The first thing that they're gonna look at is how do we tech our way out of it? >>I had a wonderful one-on-one conversation with ServiceNow ceo, Bill McDermott, and we saw ServiceNow was in focus this morning in the initial opening session. This is the integration, right? Ansible integrating with ServiceNow. What we need to see is infrastructure automation, layers and applications working in concert to basically enable enterprises to be up and running all the time. Let's first fix the problems that are most common. Let's, let's automate 'em, let's script them. And then at some point, let's have them self resolving, which we saw at the end with Project Wisdom. So as I see it, automation is that layer that enterprises, boards, technologists, all can agree upon are basically here's something that can make our business more efficient, more profitable, and it's gonna deal with this short term downturn in a way that tech is actually gonna be the answer. Just like Bill and I said, let's tech our way out of it. >>If you look at the Red Hat being bought by ibm, you see Project Wisdom Project, not a product, it's a project. Project Wisdom is the confluence of research and practitioners kind of coming together with ai. So bringing AI power to the Ansible is interesting. Red Hat, Linux, Rel OpenShift, I mean, Red Hat's kind of position, isn't it? Kind of be in that right spot where a puck might be coming maybe. I mean, what do you think? >>Yeah, as analysts, we're really good at predicting the, the recent past. It's a joke I always like to make, but Red Hat's been building toward the future. I think for some time. Project Wisdom, first of all, I was very encouraged with it. One of the things that many people in the market probably have commented on is how close is IBM in Red Hat? Now, again, it's a $34 billion acquisition that was made, but boy, the cultures of these two companies couldn't be more different. And of course, Red Hat kind of carries this, this sort of middle ground layer where they provide a lot of value in services to companies that maybe don't use IBM at, at, for the public cloud especially. This was a great indication of how you can take the power of IBM's research, which of course has some of the world's most prolific data scientists, engineers, building things for the future. >>You know, you see things like yesterday they launched a, you know, an AI solution. You know, they're building chips, semiconductors, and technologies that are gonna power the future. They're building quantum. Long story short, they have these really brilliant technologists here that could be adding value to Red Hat. And I don't know that the, the world has fully been able to appreciate that. So when, when they got on stage and they kind of say, Here's how IBM is gonna help power the next generation, I was immediately very encouraged by the fact that the two companies are starting to show signs of how they can collaborate to offer value to their customers. Because of course, as John kind of started off with, his question is, they've kind of been where the puck is going. Open source, Linux hybrid cloud, This is the future. In the future. Every company's multi-cloud. And I said in a one-on-one meeting this morning, every company is going to probably have workloads on every cloud, especially large enterprises. >>Yeah. And I think that the secret's gonna be how do you make that evolve? And one of the things that's coming out of the industry over the years, and looking back as historians, we would say, gotta have standards. Well, with cloud, now people standards might slow things down. So you're gonna start to figure out how does the community and the developers are thinking it'll be the canary in the coal mine. And I'd love to get your reaction on that, because we got Cuban next week. You're seeing people kind of align and try to win the developers, which, you know, I always laugh cuz like, you don't wanna win, you want, you want them on your team, but you don't wanna win them. It's like a, it's like, so developers will decide, >>Well, I, I think what's happening is there are multiple forces that are driving product adoption. And John, getting the developers to support the utilization and adoption of any sort of stack goes a long way. We've seen how sticky it can be, how sticky it is with many of the public cloud pro providers, how sticky it is with certain applications. And it's gonna be sticky here in these interim layers like open source automation. And Red Hat does have a very compelling developer ecosystem. I mean, if you sat in the keynote this morning, I said, you know, if you're not a developer, some of this stuff would've been fairly difficult to understand. But as a developer you saw them laughing at jokes because, you know, what was it the whole part about, you know, it didn't actually, the ping wasn't a success, right? And everybody started laughing and you know, I, I was sitting next to someone who wasn't technical and, and you know, she kinda goes, What, what was so funny? >>I'm like, well, he said it worked. Do you see that? It said zero data trans or whatever that was. So, but if I may just really quickly, one, one other thing I did wanna say about Project Wisdom, John, that the low code and no code to the full stack developer is a continuum that every technology company is gonna have to think deeply about as we go to the future. Because the people that tend to know the process that needs to be automated tend to not be able to code it. And so we've seen every automation company on the planet sort of figuring out and how to address this low code, no code environment. I think the power of this partnership between IBM Research and Red Hat is that they have an incredibly deep bench of capabilities to do things like, like self-training. Okay, you've got so much data, such significant size models and accuracy is a problem, but we need systems that can self teach. They need to be able self-teach, self learn, self-heal so that we can actually get to the crux of what automation is supposed to do for us. And that's supposed to take the mundane out and enable those humans that know how to code to work on the really difficult and hard stuff because the automation's not gonna replace any of that stuff anytime soon. >>So where do you think looking at, at the partnership and the evolution of it between IBM research and Red Hat, and you're saying, you know, they're, they're, they're finally getting this synergy together. How is it gonna affect the future of automation and how is it poised to give them a competitive advantage in the market? >>Yeah, I think the future or the, the competitive space is that, that is, is ecosystems and integration. So yesterday you heard, you know, Red Hat Ansible focusing on a partnership with aws. You know, this week I was at Oracle Cloud world and they're talking about running their database in aws. And, and so I'm kind of going around to get to the answer to your question, but I think collaboration is sort of the future of growth and innovation. You need multiple companies working towards the same goal to put gobs of resources, that's the technical term, gobs of resources towards doing really hard things. And so Ansible has been very successful in automating and securing and focusing on very certain specific workloads that need to be automated, but we need more and there's gonna be more data created. The proliferation, especially the edge. So you saw all this stuff about Rockwell, How do you really automate the edge at scale? You need large models that are able to look and consume a ton of data that are gonna be continuously learning, and then eventually they're gonna be able to deliver value to these companies at scale. IBM plus Red Hat have really great resources to drive this kind of automation. Having said that, I see those partnerships with aws, with Microsoft, with ibm, with ServiceNow. It's not one player coming to the table. It's a lot of players. They >>Gotta be Switzerland. I mean they have the Switzerland. I mean, but the thing about the Amazon deal is like that marketplace integration essentially puts Ansible once a client's in on, on marketplace and you get the central on the same bill. I mean, that's gonna be a money maker for Ansible. I >>Couldn't agree more, John. I think being part of these public cloud marketplaces is gonna be so critical and having Ansible land and of course AWS largest public cloud by volume, largest marketplace today. And my opinion is that partnership will be extensible to the other public clouds over time. That just makes sense. And so you start, you know, I think we've learned this, John, you've done enough of these interviews that, you know, you start with the biggest, with the highest distribution and probability rates, which in this case right now is aws, but it'll land on in Azure, it'll land in Google and it'll continue to, to grow. And that kind of adoption, streamlining make it consumption more consumable. That's >>Always, I think, Red Hat and Ansible, you nailed it on that whole point about multicloud, because what happens then is why would I want to alienate a marketplace audience to use my product when it could span multiple environments, right? So you saw, you heard that Stephanie yesterday talk about they, they didn't say multiple clouds, multiple environments. And I think that is where I think I see this layer coming in because some companies just have to work on all clouds. That's the way it has to be. Why wouldn't you? >>Yeah. Well every, every company will probably end up with some workloads in every cloud. I just think that is the fate. Whether it's how we consume our SaaS, which a lot of people don't think about, but it always tends to be running on another hyperscale public cloud. Most companies tend to be consuming some workloads from every cloud. It's not always direct. So they might have a single control plane that they tend to lead the way with, but that is only gonna continue to change. And every public cloud company seems to be working on figuring out what their niche is. What is the one thing that sort of drives whether, you know, it is, you know, traditional, we know the commoditization of traditional storage network compute. So now you're seeing things like ai, things like automation, things like the edge collaboration tools, software being put into the, to the forefront because it's a different consumption model, it's a different margin and economic model. And then of course it gives competitive advantages. And we've seen that, you know, I came back from Google Cloud next and at Google Cloud next, you know, you can see they're leaning into the data AI cloud. I mean, that is their focus, like data ai. This is how we get people to come in and start using Google, who in most cases, they're probably using AWS or Microsoft today. >>It's a great specialty cloud right there. That's a big use case. I can run data on Google and run something on aws. >>And then of course you've got all kinds of, and this is a little off topic, but you got sovereignty, compliance, regulatory that tends to drive different clouds over, you know, global clouds like Tencent and Alibaba. You know, if your workloads are in China, >>Well, this comes back down at least to the whole complexity issue. I mean, it has to get complex before it gets easier. And I think that's what we're seeing companies opportunities like Ansible to be like, Okay, tame, tame the complexity. >>Yeah. Yeah, I totally agree with you. I mean, look, when I was watching the demonstrations today, my take is there's so many kind of simple, repeatable and mundane tasks in everyday life that enterprises need to, to automate. Do that first, you know? Then the second thing is working on how do you create self-healing, self-teaching, self-learning, You know, and, and I realize I'm a little broken of a broken record at this, but these are those first things to fix. You know, I know we want to jump to the future where we automate every task and we have multi-term conversational AI that is booking our calendars and driving our cars for us. But in the first place, we just need to say, Hey, the network's down. Like, let's make sure that we can quickly get access back to that network again. Let's make sure that we're able to reach our different zones and locations. Let's make sure that robotic arm is continually doing the thing it's supposed to be doing on the schedule that it's been committed to. That's first. And then we can get to some of these really intensive deep metaverse state of automation that we talk about. Self-learning, data replication, synthetic data. I'm just gonna throw terms around. So I sound super smart. >>In your customer conversations though, from an looking at the automation journey, are you finding most of them, or some percentage is, is wanting to go directly into those really complex projects rather than starting with the basics? >>I don't know that you're, you're finding that the customers want to do that? I think it's the architecture that often ends up being a problem is we as, as the vendor side, will tend to talk about the most complex problems that they're able to solve before companies have really started solving the, the immediate problems that are before them. You know, it's, we talk about, you know, the metaphor of the cloud is a great one, but we talk about the cloud, like it's ubiquitous. Yeah. But less than 30% of our workloads are in the public cloud. Automation is still in very early days and in many industries it's fairly nascent. And doing things like self-healing networks is still something that hasn't even been able to be deployed on an enterprise-wide basis, let alone at the industrial layer. Maybe at the company's on manufacturing PLAs or in oil fields. Like these are places that have difficult to reach infrastructure that needs to be running all the time. We need to build systems and leverage the power of automation to keep that stuff up and running. That's, that's just business value, which by the way is what makes the world go running. Yeah. Awesome. >>A lot of customers and users are struggling to find what's the value in automating certain process, What's the ROI in it? How do you help them get there so that they understand how to start, but truly to make it a journey that is a success. >>ROI tends to be a little bit nebulous. It's one of those things I think a lot of analysts do. Things like TCO analysis Yeah. Is an ROI analysis. I think the businesses actually tend to know what the ROI is gonna be because they can basically look at something like, you know, when you have an msa, here's the downtime, right? Business can typically tell you, you know, I guarantee you Amazon could say, Look for every second of downtime, this is how much commerce it costs us. Yeah. A company can generally say, if it was, you know, we had the energy, the windmills company, like they could say every minute that windmill isn't running, we're creating, you know, X amount less energy. So there's a, there's a time value proposition that companies can determine. Now the question is, is about the deployment. You know, we, I've seen it more nascent, like cybersecurity can tend to be nascent. >>Like what does a breach cost us? Well there's, you know, specific costs of actually getting the breach cured or paying for the cybersecurity services. And then there's the actual, you know, ephemeral costs of brand damage and of risks and customer, you know, negative customer sentiment that potentially comes out of it. With automation, I think it's actually pretty well understood. They can look at, hey, if we can do this many more cycles, if we can keep our uptime at this rate, if we can reduce specific workforce, and I'm always very careful about this because I don't believe automation is about replacement or displacement, but I do think it is about up-leveling and it is about helping people work on things that are complex problems that machines can't solve. I mean, said that if you don't need to put as many bodies on something that can be immediately returned to the organization's bottom line, or those resources can be used for something more innovative. So all those things are pretty well understood. Getting the automation to full deployment at scale, though, I think what often, it's not that roi, it's the timeline that gets misunderstood. Like all it projects, they tend to take longer. And even when things are made really easy, like with what Project Wisdom is trying to do, semantically enable through low code, no code and the ability to get more accuracy, it just never tends to happen quite as fast. So, but that's not an automation problem, That's just the crux of it. >>Okay. What are some of the, the next things on your plate? You're quite a, a busy guy. We, you, you were at Google, you were at Oracle, you're here today. What are some of the next things that we can expect from Daniel Newman? >>Oh boy, I moved Really, I do move really quickly and thank you for that. Well, I'm very excited. I'm taking a couple of work personal days. I don't know if you're a fan, but F1 is this weekend. I'm the US Grand Prix. Oh, you're gonna Austin. So I will be, I live in Austin. Oh. So I will be in Austin. I will be at the Grand Prix. It is work because it, you know, I'm going with a number of our clients that have, have sponsorships there. So I'll be spending time figuring out how the data that comes off of these really fun cars is meaningfully gonna change the world. I'll actually be talking to Splunk CEO at the, at the race on Saturday morning. But yeah, I got a lot of great things. I got a, a conversation coming up with the CEO of Twilio next week. We got a huge week of earnings ahead and so I do a lot of work on that. So I'll be on Bloomberg next week with Emily Chang talking about Microsoft and Google. Love talking to Emily, but just as much love being here on, on the queue with you >>Guys. Well we like to hear that. Who you're rooting for F one's your favorite driver. I, >>I, I like Lando. Do you? I'm Norris. I know it's not necessarily a fan favorite, but I'm a bit of a McLaren guy. I mean obviously I have clients with Oracle and Red Bull with Ball Common Ferrari. I've got Cly Splunk and so I have clients in all. So I'm cheering for all of 'em. And on Sunday I'm actually gonna be in the Williams Paddock. So I don't, I don't know if that's gonna gimme me a chance to really root for anything, but I'm always, always a big fan of the underdog. So maybe Latifi. >>There you go. And the data that comes off the how many central unbeliev, the car, it's crazy's. Such a scientific sport. Believable. >>We could have Christian, I was with Christian Horner yesterday, the team principal from Reside. Oh yeah, yeah. He was at the Oracle event and we did a q and a with him and with the CMO of, it's so much fun. F1 has been unbelievable to watch the momentum and what a great, you know, transitional conversation to to, to CX and automation of experiences for fans as the fan has grown by hundreds of percent. But just to circle back full way, I was very encouraged with what I saw today. Red Hat, Ansible, IBM Strong partnership. I like what they're doing in their expanded ecosystem. And automation, by the way, is gonna be one of the most robust investment areas over the next few years, even as other parts of tech continue to struggle that in cyber security. >>You heard it here. First guys, investment in automation and cyber security straight from two analysts. I got to sit between. For our guests and John Furrier, I'm Lisa Martin, you're watching The Cube Live from Chicago, Ansible Fest 22. John and I will be back after a short break. SO'S stick around.

The Cube Presents UI Path Forward five. Brought to you by UI Path. >>I Ready, Dave Ante with David Nicholson. We're back at UI Path forward. Five. We're getting ready for the big guns to come in, the two co CEOs, but we have a really special analyst panel now. We're excited to have Daniel Newman here. He's the Principal analyst at Future and Research. And Andy Dai, who's the Vice president and Principal Analyst at Constellation Research. Guys, good to see you. Thanks for making some time to come on the queue. >>Glad to be here. Always >>Good. So, >>Andy, you're deep into ai. You and I have been talking about having you come to our maor office. I'm, I'm really excited that we're able to meet here. What have you seen at the show so far? What are your big takeaways? You know, day one and a half? >>Yeah, well, so first of all, I'm d AI because my last name has AI and I >>Already talk about, >>So, but, but all jokes aside, there are a lot of good things I heard from the conference, right? I mean, one is the last two years because of the pandemic, the growth has been phenomenal for, for a lot of those robotic automation intelligent automation companies, right? So because the low hanging through position making processes have been already taken care of where they going to find the next growth spot, right? That was the question I was looking answers to. And they have some inverse, one good acquisition. They had intelligent document processing, but more importantly they're trying to move from detrimental rules based RPA automation into AI based, more probabilistic subjective decision making areas. That's a huge market, tons of money involved in it, but it's going to be a harder problem to solve. Love to see the execut. >>Well, it's also a big pivot for the, for the company. It started out as sort of a a point product and now is moving to, to platform. But to end of the macro is not in UI pass favor. It's not really in any, you know, tech company's favor, but especially, you know, a company that's going into a transition transitioning to go to market cetera. What are you seeing, what's your take on the macro? I mean, I know you follow the financial markets very closely. There's a lot of negative sentiment right now. Are you as negative as the sentiment? >>Well, the, the broad sentiment comes with some pretty good historical data, right? We've had probably one of the worst market years in multiple decades. And of course we're coming into a situation where all the, the factors are really not in our favor. You've got in interest rates climbing, you've got wildly high inflation, you've had a, you know, helicopters dumping money on the economy for a period of time. And we're, we're gonna get into this great reset is what I keep talking about. But, you know, I had the opportunity to talk to Bill McDermott recently on one of my shows and Bill's CEO of ServiceNow, in case anybody there doesn't know, but >>Former, >>Yeah, really well spoken guy. But you know, him and I kind of went back and forth and we came up with this kind of concept that we were gonna have to tech our way out of what's about to come. You can almost be certain recession is gonna come. But for companies like UiPath, I actually think there's a tremendous opportunity because the bottom line is companies are gonna be looking at their bottom line. A year ago it was all about growth a deal, like the Adobe Figma deal would've been, been lauded, people would've been excited. Now everybody's looking at going, how are they paying that price? Everybody's discounting the future growth. They're looking at the situation, say, what's gonna happen next? Well, bottom line is now they're looking at that. How profitable are we? Are you making money? Are you growing that bottom line? Are you creating earnings? We're >>Gonna come in >>Era, we're gonna come into an era where companies are gonna say, you know what? People are expensive. The inflationary cost of hiring is expensive. You know, what's less expensive? Investing in the cloud, investing in ai, investing in workflow and automation and things that actually enable businesses to expand, keep costs somewhat contained fixed costs, and scale their businesses and get themselves in a good position for when the economy turns to return to >>Grow. So since prior to the pandemic cloud containers, m l and RPA slash automation have been the big four that from a spending data standpoint have been above the line above all kind of the rest in terms of spending momentum up until last quarter, AI and RPA slash automation declined. So my question is, are those two areas discretionary or more discretionary than other technology investments you heard? >>Well, I, I think we're in a, a period where companies are, I won't say they've stopped spending, but you listened to Mark Benioff, you talked about the elongated sales cycle, right? I think companies right now are being very reflective and they're doing a lot of introspection. They're looking at their business and saying, We hired a lot of people. We hired really fast. Do we need to cut? Do we need to freeze? We've made investments in technology, are we getting a return on 'em? We all know that the analytics, whether it's you know, digital adoption platforms or just analytics in the business, say, What is all this money we've been spending doing for us and how productive are we? But I will tell you universally, the companies are looking at workflow automations that enable things. Whether that's onboarding customers, whether that's delivering experiences, whether that's, you know, full, you know, price to quote technologies, automate, automate, automate. By doing that, they're gonna bring down the cost, they're gonna control themselves as best as possible in a tough macro. And then when they come out of it, these processes are gonna be beneficiary in a, in a growth environment even more so, >>Andy UiPath rocketed to a leadership position, largely due to the, the product and the simplicity of the product relative to the competition. And then as you well know, they expanded into, you know, platform. So how do you see the competitive environment? A UI path is again focusing on that platform play Automation Anywhere couldn't get to public market. They had turnover at the go to market level. Chris Riley joined a lot of, lot of hope left Microsoft joined into the fray, obviously is having an impact that you're certainly seeing spending momentum around Microsoft. Then SAP service Now Salesforce, every software company the planet thinks they should get every dollar spent on software. You know, they, they see UI pass momentum and they say, Hey, we can, we can take some of that off the table. How do you see the competitive environment right now? >>So first of all, in in my mind, UI path is slightly better because of a couple of reasons. One, as you said, it's ease of use. >>They're able to customize it variable to what they want. So that's a real easy development advantage. And then the, when you develop the bots and equal, it takes on an average anywhere between two to maybe six weeks, generally speaking, in some industries regulated government might take more so that it's faster, quicker, easier than others in a sense. So people love using that. The second advantage of what they have in my mind is that not only they are available as a managed SA solution on, on cloud, on Azure Cloud, but also they have this version that you can install, maintain, manage any way you want, whether it's a public cloud or, or your own data center and so on so forth. That's not available with almost, not all of them have it, Few have it, but not all of the competitors have it. So they have an advantage there as well. Where it could become useful would be one of the areas that they haven't even expanded is the government. >>Government is the what, >>Sorry? The government. Yeah, related solutions, right? Defense, government, all of those areas when you go, which haven't even started for various reasons. For example, they're worried about laying off people, worried about cost, worried about automating things. There's a lot of hurdles to overcome. But once you overcome that, if you want to go there, nobody's going to use, or most of them will be very of using something on the cloud. So they have a solution for version variation of that. So they are set up to come to that next level. I mean, I don't know if you guys were at the keynote, the CEO talked about how their plans to go from 1 billion to 5 billion in ar. So they're set up to capture the market. But again, as you said, every big software company saw their momentum, they want to get into it, they want to compete with them. So >>Well, to get to 5 billion, they've gotta accelerate growth. I mean, if you do 20% cer over the next, you know, through the end of the decade, they don't quite get there. So they're gonna have to, you know, they lowered their forecast out of the high 20 or mid twenties to 18%. They're gonna have to accelerate that. And we've seen that before. We see it in cloud where cloud, you know, accelerates growth even though you got the lower large numbers. Go ahead Dave. >>Yeah, so Daniel, then how do we, how do we think of this market? How do we measure the TAM for total addressable market for automation? I mean, you know, what's that? What's that metric that shows how unautomated are we, how inefficient are we? Is there a, is there a 5% efficiency that can be gained? Is there a 40% efficiency that can be gained? Because if you're talking about, you know, how much much of the market can UI path capture, first of all, how big is the market? And then is UI path poised to take advantage of that compared to the actual purveyors of the software that people are interacting with? I'm interacting with an E R p, an ER P system that has built into it the ability to automate processes. Then why do I need 'EM UI path? So first, how do you evaluate TAM? Second, how do you evaluate whether UI Path is gonna have a chance in this market where RPAs built into the applications that we actually use? Yeah, >>I think that TAM is evolving, and I don't have it in front of me right now, but what I'll tell you about the TAM is there's sort of the legacy RPA tam and then there's what I would sort of evolve to call the IPA and workflow automation tam that is being addressed by many of these software companies that you asked in the competitive equation. In the, in the, in the question, what we're seeing is a world where companies are gonna say, if we can automate it, we will automate it. That's, it's actually non-negotiable. Now, the process in the ability to a arrive at automation at scale has long been a battle front within the nor every organization. We've been able to automate things for a long time. Why has it more been done? It's the same thing with analytics. There's been numerous studies in analytics that have basically shown companies that have been able to embrace, adopt, and implement analytics, have significantly better performances, better performances on revenue growth, better performances and operational cost management, better performances with customer experience. >>Guess what? Not everybody, every company can get to this. Now there's a couple of things behind this and I'm gonna, I'm gonna try to close my answer out cause I'm getting a little long winded here. But the first thing is automation is a cultural challenge in most organizations. We've done endless research on companies digitally transforming and automating their business. And what we've found is largely the technology are somewhat comparable. Meaning, you know, I, I've heard what he is saying about some of the advantages of partnership with Microsoft, very compelling. But you know what, all these companies that have automation offerings, whether it's you know, through a Salesforce, Microsoft, whether it's a specialized rpa like an Automation Anywhere or a UI path, their solutions can be deployed and successful. The company's ability to take the investment, implement it successfully and get buy in across the organization tends to always be the hurdle. An old CIO stat, 50% of IT projects fail. That stat is still almost accurate today. It's not 50% of technology is bad, but those failures are because the culture doesn't get behind it. And automation's a tricky one because there's a lot of people that feel on the outside rather than the inside of an automation transformation. >>So, Andy, so how do you think about the, to Dave's question, the SAPs the service nows trying to, you know, at least take some red crumbs off the table. They, they're gonna, they're gonna create these automation stove pipes, but in Automation Anywhere or, or UI path is a horizontal play, are they not? And so how do you think about that progression? Well, so >>First of all, all of this other companies, when they, they, whether it's a build, acquire, what have you, these guys already have what, five, seven years on them. So it's gonna be difficult for them to catch up with the Center of Excellence knowledge on the use cases, what they got to catch up with them. That's gonna be a lot of catch up. Just to give you an idea, Microsoft Power Automate has been there for a while, right? They're supposedly doing well as well, but they still choose to partner with the UiPath as well to get them to the next level. So there's going to be competition coming from all areas, but it's, it's about, you know, highlights. >>So, so who is the competition? Is it Microsoft chipping away an individual productivity? Is it a service now? Who's got a platform play? Is it themselves just being able to execute >>All plus also, but I think the, the most, I wouldn't say competition, but it's more people are not aware of what areas need to be automated, right? For example, one of the things I was talking about with a couple of customers is, so they have a automation hub where you can put the, the process and and task that need to be automated and then you prioritize and start working on it. And, and almost all of them that I speak to, they keep saying that most of the process and task identification that they need to do for automation, it's manual right now. So, which means it's limited, you have to go and execute it. When people find out and tell you that's what need to be fixed, you try to go and fix that. But imagine if there is a way, I mean the have solutions they're showcasing now if it becomes popular, if you're able to identify tasks that are very inefficient or or process that's very inefficient, automatically score them up saying that, you know what, this is what is going to be ROI and you execute on it. That's going to be huge. So >>I think ts right, there's no shortage of, of a market. I would, I would agree with you Rob Sland this morning talked about the progression. He sort of compared it to e R P of the early days. I sort of have a love hate with E R P cuz of the complexity of the implementation and the, and the cost. However, first of all, a couple points and I love to get your thoughts for you. If you went back, I know 25 years, you, you wouldn't have been able to pick SAP out of a lineup and say that's gonna be the leader in E R P and they ended up, you know, doing really, really well. But the more interesting angle is if you could have figured out the customers that were implementing e r p in, in a really high quality fashion, those are the companies that really did well. You buy their stocks, they really took off cuz they were killing their other industry competitors. So, fast forward to automation. Will automation live up to its hype and your opinion, will it be as transformative and will the, the practitioners of automation see the same type of uplift in their markets, in their market caps, in their competitiveness as did sort of the early adopters and the excellent adopters of brp? What are your thoughts? Well, >>I think it's an interesting comparison. Maybe answer it slightly different way. I think the future is that automation is a non-negotiable in every enterprise organization. I think if you're a large organization, we have absolutely filled our, our organizations with waste too much overhead, too much expense, too much technical debt and automation is an answer. This is the way we want to interact, right? We want a chat bot that actually gives us good answers that can answer on a Tuesday at 11:00 PM at night when we want to know if the right dog food, you know, and I'm saying that, you know, that's what we want. That's the outcome we want. And businesses have to be driven by the outcome. Here's what I'm not sure about, Dave, is we have an era where over the last three to five years, a lot of products have become companies and a lot of 'EM products became companies ended up in public markets. >>And so the RPA space is one of those areas that got this explosive amount of growth. And you look at it and there's two ways. Is this horizontally a business rpa or is this going to be something that's gonna be a target of those Microsofts and those SAPs and say, Look, we need hyper automation to be deeply integrated at the E R P crm, hcm SCM level. We're gonna build by this or we're gonna build this. And you're already hearing it in the partnerships, but this is how I think the story ends. I I think either the companies like UiPath get much bigger, they get much more rounded in their, in their offerings. Or you're gonna have a large company like a Microsoft come in and say, you know what? Buy it rather >>Than build can they can, they can, can this company, maybe not so much here, but can a company like Automation Anywhere stay acquisition? Well, >>I use the, I use the Service now as an, as a parallel because they're a company that I thought would always end up inside of a bigger company and now you're like, I think they're too big. I think they've they've dropped >>That, that chart. Yeah, they're acquisition proof. I would agree. But these guys aren't yet Nora's automation. They work for >>A while and it's not necessarily a bad thing. Sometimes getting bit bought is good, but what I mean is it's gonna be core and these big companies know it cuz they're all talking >>About, but as independent analysts, we want to see independent companies. >>I wanna see the right thing. >>It just makes it fun. >>The right thing >>Customers. Yeah, but you know, okay, Oracle buy more customers, more >>Customers. >>I'm kidding. Yeah, I guess it's the right thing. It just makes it more fun when you have really good independent competitors that >>We >>Absolutely so, and, and spend way more on r and d than these big companies who spend a lot more on stock buyback. But I know you gotta go. Thanks so much for spending some time, making time for Cube Andy. Great to see you. Good to see as well. All right, we are wrapping up day one, Dave Blan and Dave Nicholson live. You can hear the action behind us, forward in five on the Cube, right back.

(upbeat music) >> Okay, welcome back everyone. CUBE's coverage of re:MARS, here in Las Vegas, in person. I'm John Furrier, host of theCUBE. This is the analyst panel wrap up analysis of the keynote, the show, past one and a half days. We got two great guests here. We got Andy Thurai, Vice President, Principal Consultant, Constellation Research. Larry Carvalho, Principal Consultant at RobustCloud LLC. Congratulations going out on your own. >> Thank you. >> Andy, great to see you. >> Great to see you as well. >> Guys, thanks for coming out. So this is the session where we break down and analyze, you guys are analysts, industry analysts, you go to all the shows, we see each other. You guys are analyzing the landscape. What does this show mean to you guys? 'Cause this is not obvious to the normal tech follower. The insiders see the confluence of robotics, space, automation and machine learning. Obviously, it's IoTs, industrials, it's a bunch of things. But there's some dots to connect. Let's start with you, Larry. What do you see here happening at this show? >> So you got to see how Amazon started, right? When AWS started. When AWS started, it primarily took the compute storage, networking of Amazon.com and put it as a cloud service, as a service, and started selling the heck out of it. This is a stage later now that Amazon.com has done a lot of physical activity, and using AIML and the robotics, et cetera, it's now the second phase of innovation, which is beyond digital transformation of back office processes, to the transformation of physical processes where people are now actually delivering remotely and it's an amazing area. >> So back office's IT data center kind of vibe. >> Yeah. >> You're saying front end, industrial life. >> Yes. >> Life as we know it. >> Right, right. I mean, I just stopped at a booth here and they have something that helps anybody who's stuck in the house who cannot move around. But with Alexa, order some water to bring them wherever they are in the house where they're stuck in their bed. But look at the innovation that's going on there right at the edge. So I think those are... >> John: And you got the Lunar, got the sex appeal of the space, Lunar Outpost interview, >> Yes. >> those guys. They got Rover on Mars. They're going to have be colonizing the moon. >> Yes. >> I made a joke, I'm like, "Well, I left a part back on earth, I'll be right back." (Larry and Andy laugh) >> You can't drive back to the office. So a lot of challenges. Andy, what's your take of the show? Take us your analysis. What's the vibe, what's your analysis so far? >> It's a great show. So, as Larry was saying, one of the thing was that when Amazon started, right? So they were more about cloud computing. So, which means is they try to commoditize more of data center components or compute components. So that was working really well for what I call it as a compute economy, right? >> John: Mm hmm. >> And I call the newer economy as more of a AIML-based data economy. So when you move from a compute economy into a data economy, there are things that come into the forefront that never existed before, never popular before. Things like your AIML model creation, model training, model movement, model influencing, all of the above, right? And then of course the robotics has come long way since then. And then some of what they do at the store, or the charging, the whole nine yards. So, the whole concept of all of these components, when you put them on re:Invent, such a big show, it was getting lost. So that's why they don't have it for a couple of years. They had it one year. And now all of a sudden they woke up and say, "You know what? We got to do this!" >> John: Yeah. >> To bring out this critical components that we have, that's ripe, mature for the world to next component. So that's why- I think they're pretty good stuff. And some of the robotics things I saw in there, like one of them I posted on my Twitter, it's about the robot dog, sniffing out the robot rover, which I thought was pretty hilarious. (All laugh) >> Yeah, this is the thing. You're seeing like the pandemic put everything on hold on the last re:Mars, and then the whole world was upside down. But a lot of stuff pulled forward. You saw the call center stuff booming. You saw the Zoomification of our workplace. And I think a lot of people got to the realization that this hybrid, steady-state's here. And so, okay. That settles that. But the digital transformation of actually physical work? >> Andy: Yeah. >> Location, the walk in and out store right over here we've seen that's the ghost store in Seattle. We've all been there. In fact, I was kind of challenged, try to steal something. I'm like, okay- (Larry laughs) I'm pulling all my best New Jersey moves on everyone. You know? >> Andy: You'll get charged for it. >> I couldn't get away with it. Two double packs, drop it, it's smart as hell. Can't beat the system. But, you bring that to where the AI machine learning, and the robotics meet, robots. I mean, we had robots here on theCUBE. So, I think this robotics piece is a huge IoT, 'cause we've been covering industrial IoT for how many years, guys? And you could know what's going on there. Huge cyber threats. >> Mm hmm. >> Huge challenges, old antiquated OT technology. So I see a confluence in the collision between that OT getting decimated, to your point. And so, do you guys see that? I mean, am I just kind of seeing mirage? >> I don't see it'll get decimated, it'll get replaced with a newer- >> John: Dave would call me out on that. (Larry laughs) >> Decimated- >> Microsoft's going to get killed. >> I think it's going to have to be reworked. And just right now, you want do anything in a shop floor, you have to have a physical wire connected to it. Now you think about 5G coming in, and without a wire, you get minute details, you get low latency, high bandwidth. And the possibilities are endless at the edge. And I think with AWS, they got Outposts, they got Snowcone. >> John: There's a threat to them at the edge. Outpost is not doing well. You talk to anyone out there, it's like, you can't find success stories. >> Larry: Yeah. >> I'm going to get hammered by Amazon people, "Oh, what're you're saying that?" You know, EKS for example, with serverless is kicking ass too. So, I mean I'm not saying Outpost was wrong answer, it was a right at the time, what, four years ago that came out? >> Yeah. >> Okay, so, but that doesn't mean it's just theirs. You got Dell Technologies want some edge action. >> Yeah. >> So does HPE. >> Yes. >> So you got a competitive edge situation. >> I agree with that and I think that's definitely not Amazon's strong point, but like everything, they try to make it easy to use. >> John: Yeah. >> You know, you look at the AIML and they got Canvas. So Canvas says, hey, anybody can do AIML. If they can do that for the physical robotic processes, or even like with Outpost and Snowcone, that'll be good. I don't think they're there yet, and they don't have the presence in the market, >> John: Yeah. >> like HPE and, >> John: Well, let me ask you guys this question, because I think this brings up the next point. Will the best technology win or will the best solution win? Because if cloud's a platform and all software's open source, which you can make those assumptions, you then say, hey, they got this killer robotics thing going on with Artemis and Moonshot, they're trying to colonize the moon, but oh, they discovered a killer way to solve a big problem. Does something fall out of this kind of re:Mars environment, that cracks the code and radically changes and disrupts the IoT game? That's my open question. I don't know the answer. I'd love to get your take on what might be possible, what wild card's out there around, disrupting the edge. >> So one thing I see the way, so when IoT came into the world of play, it's when you're digitizing the physical world, it's IoT that does digitalization part of that actually, right? >> But then it has its own set of problems. >> John: Yeah. >> You're talking about you installing sensor everywhere, right? And not only installing your own sensor, but also you're installing competitor sensors. So in a given square feet how many sensors can you accommodate? So there are physical limitations on liabilities of bandwidth and networking all of that. >> John: And integration. >> As well. >> John: Your point. >> Right? So when that became an issue, this is where I was talking to the robotic guys here, a couple of companies, and one of the use cases they were talking about, which I thought was pretty cool, is, rather than going the sensor route, you go the robot route. So if you have either a factor that you want to map out, you put as many sensors on your robot, whatever that is, and then you make it go around, map the whole thing, and then you also do a surveillance in the whole nine yards. So, you can either have a fixed sensors or you can have moving sensors. So you can have three or four robots. So initially, when I was asking them about the price of it, when they were saying about a hundred thousand dollars, I was like, "Who would buy that?" (John and Larry laugh) >> When they then explained that, this is the use case, oh, that makes sense, because if you had to install, entire factory floor sensors, you're talking about millions of dollars. >> John: Yeah. >> But if you do the moveable sensors in this way, it's a lot cheaper. >> John: Yeah, yeah. >> So it's based on your use case, what are your use cases? What are you trying to achieve? >> The general purpose is over. >> Yeah. >> Which you're getting at, and that the enablement, this is again, this is the cloud scale open question- >> Yep. >> it's, okay, the differentiations isn't going to be open source software. That's open. >> It's going to be in the, how you configure it. >> Yes. >> What workflows you might have, the data streams. >> I think, John, you're bringing up a very good point about general purpose versus special purpose. Yesterday Zoox was on the stage and when they talked about their vehicle, it's made just for self-driving. You walk around in Vegas, over here, you see a bunch of old fashioned cars, whether they're Ford or GM- >> and they put all these devices around it, but you're still driving the same car. >> John: Yeah, exactly. >> You can retrofit those, but I don't think that kind of IoT is going to work. But if you redo the whole thing, we are going to see a significant change in how IoT delivers value all the way from the industrial to home, to healthcare, mining, agriculture, it's going to have to redo. I'll go back to the OT question. There are some OT guys, I know Rockwell and Siemens, some of them are innovating faster. The ones who innovate faster to keep up with the IT side, as well as the MLAI model are going to be the winners on that one. >> John: Yeah, I agree. Andy, your thoughts on manufacturing, you brought up the sensor thing. Robotics ultimately is, end of the day, an opportunity there. Obviously machine learning, we know what that does. As we move into these more autonomous builds, what does that look like? And is Amazon positioned well there? Obviously they have big manufacturers. Some are saying that they might want to get out of that business too, that Jassy's evaluating that some are saying. So, where does this all lead for that robotics manufacturing lifestyle, walk in, grab my food? 'Cause it's all robotics and AI at the end of the day, I got sensors, I got cameras, I got non-humans moving heavy lifting stuff, fixing the moon will be done by robots, not humans. So it's all coming. What's your analysis? >> Well, so, the point about robotics is on how far it has come, it is unbelievable, right? Couple of examples. One was that I was just talking to somebody, was explaining to them, to see that robot dog over there at the Boston Dynamics one- >> John: Yeah. >> climbing up and down the stairs. >> Larry: Yeah. >> That's more like the dinosaur movie opening the doors scene. (John and Larry laugh) It's like that for me, because the coordinated things, it is able to go walk up and down, that's unbelievable. But okay, it does that, and then there was also another video which is going on viral on the internet. This guy kicks the dog, robot dog, and then it falls down and it gets back up, and the sentiment that people were feeling for the dog, (Larry laughs) >> you can't, it's a robot, but people, it just comes at that level- >> John: Empathy, for a non-human. >> Yeah. >> But you see him, hey you, get off my lawn, you know? It's like, where are we? >> It has come to that level that people are able to kind of not look at that as a robot, but as more like a functioning, almost like a pet-level, human-level being. >> John: Yeah. >> And you saw that the human-like walking robot there as well. But to an extent, in my view, they are all still in an experimentation, innovation phase. It doesn't made it in the industrial terms yet. >> John: Yeah, not yet, it's coming. >> But, the problem- >> John: It's coming fast. That's what I'm trying to figure out is where you guys see Amazon and the industry relative to what from the fantasy coming reality- >> Right. >> of space in Mars, which is, it's intoxicating, let's face it. People love this. The nerds are all here. The geeks are all here. It's a celebration. James Hamilton's here- >> Yep. >> trying to get him on theCUBE. And he's here as a civilian. Jeff Barr, same thing. I'm here, not for Amazon, I bought a ticket. No, you didn't buy a ticket. (Larry laughs) >> I'm going to check on that. But, he's geeking out. >> Yeah. >> They're there because they want to be here. >> Yeah. >> Not because they have to work here. >> Well, I mean, the thing is, the innovation velocity has increased, because, in the past, remember, the smaller companies couldn't innovate because they don't have the platform. Now Compute is a platform available at the scale you want, AI is available at the scale. Every one of them is available at the scale you want. So if you have an idea, it's easy to innovate. The innovation velocity is high. But where I see most of the companies failing, whether startup or big company, is that you don't find the appropriate use case to solve, and then don't sell it to the right people to buy that. So if you don't find the right use case or don't sell the right value proposition to the actual buyer, >> John: Mm hmm. >> then why are you here? What are you doing? (John laughs) I mean, you're not just an invention, >> John: Eh, yeah. >> like a telephone kind of thing. >> Now, let's get into next talk track. I want to get your thoughts on the experience here at re:Mars. Obviously AWS and the Amazon people kind of combined effort between their teams. The event team does a great job. I thought the event, personally, was first class. The coffee didn't come in late today, I was complaining about that, (Larry laughs) >> people complaining out there, at CUBE reviews. But world class, high bar on the quality of the event. But you guys were involved in the analyst program. You've been through the walkthrough, some of the briefings. I couldn't do that 'cause I'm doing theCUBE interviews. What would you guys learn? What were some of the key walkaways, impressions? Amazon's putting all new teams together, seems on the analyst relations. >> Larry: Yeah. >> They got their mojo booming. They got three shows now, re:Mars, re:inforce, re:invent. >> Andy: Yeah. >> Which will be at theCUBE at all three. Now we got that coverage going, what's it like? What was the experience like? Did you feel it was good? Where do they need to improve? How would you grade the Amazon team? >> I think they did a great job over here in just bringing all the physical elements of the show. Even on the stage, where they had robots in there. It made it real and it's not just fake stuff. And every, or most of the booths out there are actually having- >> John: High quality demos. >> high quality demos. (John laughs) >> John: Not vaporware. >> Yeah, exactly. Not vaporware. >> John: I won't say the name of the company. (all laugh) >> And even the sessions were very good. They went through details. One thing that stood out, which is good, and I cover Low Code/No Code, and Low Code/No Code goes across everything. You know, you got DevOps No Low-Code Low-Code. You got AI Low Code/No Code. You got application development Low Code/No Code. What they have done with AI with Low Code/No Code is very powerful with Canvas. And I think that has really grown the adoption of AI. Because you don't have to go and train people what to do. And then, people are just saying, Hey, let me kick the tires, let me use it. Let me try it. >> John: It's going to be very interesting to see how Amazon, on that point, handles this, AWS handles this data tsunami. It's cause of Snowflake. Snowflake especially running the table >> Larry: Yeah. >> on the old Hadoop world. I think Dave had a great analysis with other colleagues last week at Snowflake Summit. But still, just scratching the surface. >> Larry: Yeah. >> The question is, how shared that ecosystem, how will that morph? 'Cause right now you've got Data Bricks, you've got Snowflake and a handful of others. Teradata's got some new chops going on there and a bunch of other folks. Some are going to win and lose in this downturn, but still, the scale that's needed is massive. >> So you got data growing so much, you were talking earlier about the growth of data and they were talking about the growth. That is a big pie and the pie can be shared by a lot of folks. I don't think- >> John: And snowflake pays AWS, remember that? >> Right, I get it. (John laughs) >> I get it. But they got very unique capabilities, just like Netflix has very unique capabilities. >> John: Yeah. >> They also pay AWS. >> John: Yeah. >> Right? But they're competing on prime. So I really think the cooperation is going to be there. >> John: Yeah. >> The pie is so big >> John: Yeah. >> that there's not going to be losers, but everybody could be winners. >> John: I'd be interested to follow up with you guys after next time we have an event together, we'll get you back on and figure out how do you measure this transitions? You went to IDC, so they had all kinds of ways to measure shipments. >> Larry: Yep. >> Even Gartner had fumbled for years, the Magic Quadrant on IaaS and PaaS when they had the market share. (Larry laughs) And then they finally bundled PaaS and IaaS together after years of my suggesting, thank you very much Gartner. (Larry laughs) But that just performs as the landscape changes so does the scoreboard. >> Yep. >> Right so, how do you measure who's winning and who's losing? How can we be critical of Amazon so they can get better? I mean, Andy Jassy always said to me, and Adam Salassi same way, we want to hear how bad we're doing so we can get better. >> Yeah. >> So they're open-minded to feedback. I mean, not (beep) posting on them, but they're open to critical feedback. What do you guys, what feedback would you give Amazon? Are they winning? I see them number one clearly over Azure, by miles. And even though Azure's kicking ass and taking names, getting back in the game, Microsoft's still behind, by a long ways, in some areas. >> Andy: Yes. In some ways. >> So, the scoreboard's changing. What's your thoughts on that? >> So, look, I mean, at the end of the day, when it comes to compute, right, Amazon is a clear winner. I mean, there are others who are catching up to it, but still, they are the established leader. And it comes with its own advantages because when you're trying to do innovation, when you're trying to do anything else, whether it's a data collection, we were talking about the data sensors, the amount of data they are collecting, whether it's the store, that self-serving store or other innovation projects, what they have going on. The storage compute and process of that requires a ton of compute. And they have that advantage with them. And, as I mentioned in my last article, one of my articles, when it comes to AIML and data programs, there is a rich and there is a poor. And the rich always gets richer because they, they have one leg up already. >> John: Yeah. >> I mean the amount of model training they have done, the billion or trillion dollar trillion parametrization, fine tuning of the model training and everything. They could do it faster. >> John: Yeah. >> Which means they have a leg up to begin with. So unless you are given an opportunity as a smaller, mid-size company to compete at them at the same level, you're going to start at the negative level to begin with. You have a lot of catch up to do. So, the other thing about Amazon is that they, when it comes to a lot of areas, they admit that they have to improve in certain areas and they're open and willing and listen to the people. >> Where are you, let's get critical. Let's do some critical analysis. Where does Amazon Websters need to get better? In your opinion, what criticism would you, in a constructive way, share? >> I think on the open source side, they need to be more proactive in, they are already, but they got to get even better than what they are. They got to engage with the community. They got to be able to talk on the open source side, hey, what are we doing? Maybe on the hardware side, can they do some open-sourcing of that? They got graviton. They got a lot of stuff. Will they be able to share the wealth with other folks, other than just being on an Amazon site, on the edge with their partners. >> John: Got it. >> If they can now take that, like you said, compute with what they have with a very end-to-end solution, the full stack. And if they can extend it, that's going to be really beneficial for them. >> Awesome. Andy, final word here. >> So one area where I think they could improve, which would be a game changer would be, right now, if you look at all of their solutions, if you look at the way they suggest implementation, the innovations, everything that comes out, comes out across very techy-oriented. The persona is very techy-oriented. Very rarely their solutions are built to the business audience or to the decision makers. So if I'm, say, an analyst, if I want to build, a business analyst rather, if I want to build a model, and then I want to deploy that or do some sort of application, mobile application, or what have you, it's a little bit hard. It's more techy-oriented. >> John: Yeah, yeah. >> So, if they could appeal or build a higher level abstraction of how to build and deploy applications for business users, or even build something industry specific, that's where a lot of the legacy companies succeeded. >> John: Yeah. >> Go after manufacturing specific or education. >> Well, we coined the term 'Supercloud' last re:Invent, and that's what we see. And Jerry Chen at Greylock calls it Castles in the Cloud, you can create these moats >> Yep. >> on top of the CapEx >> Yep. >> of Amazon. >> Exactly. >> And ride their back. >> Yep. >> And the difference in what you're paying and what you're charging, if you're good, like a Snowflake or a Mongo. I mean, Mongo's, they're just as big as Snow, if not bigger on Amazon than Snowflake is. 'Cause they use a lot of compute. No one turns off their database. (John laughs) >> Snowflake a little bit different, a little nuanced point, but, this is the new thing. You see Goldman Sachs, you got Capital One. They're building their own kind of, I call them sub clouds, but Dave Vellante says it's a Supercloud. And that essentially is the model. And then once you have a Supercloud, you say, great, I'm going to make sure it works on Azure and Google. >> Andy: Yep. >> And Alibaba if I have to. So, we're kind of seeing a playbook. >> Andy: Mm hmm. >> But you can't get it wrong 'cause it scales. >> Larry: Yeah, yeah. >> You can't scale the wrong answer. >> Andy: Yeah. >> So that seems to be what I'm watching is, who gets it right? Product market fit. Then if they roll it out to the cloud, then it becomes a Supercloud, and that's pure product market fit. So I think that's something that I've seen some people trying to figure out. And then, are you a supplier to the Superclouds? Like a Dell? Or you become an enabler? >> Andy: Yeah. >> You know, what's Dell Technologies do? >> Larry: Yeah. >> I mean, how do the box movers compete? >> Larry: I, the whole thing is now hybrid and you're going to have to see just, you said. (Larry laughs) >> John: Hybrid's a steady-state. I don't need to. >> Andy: I mean, >> By the way we're (indistinct), we can't get the chips, cause Broadcom and Apple bought 'em all. (Larry laughs) I mean there's a huge chip problem going on. >> Yes. I agree. >> Right now. >> I agree. >> I mean all these problems when you attract to a much higher level, a lot of those problems go away because you don't care about what they're using underlying as long as you deliver my solution. >> Larry: Yes. >> Yeah, it could be significantly, a little bit faster than what it used to be. But at the end of the day, are you solving my specific use case? >> John: Yeah. >> Then I'm willing to wait a little bit longer. >> John: Yeah. Time's on our side and now they're getting the right answers. Larry, Andy, thanks for coming on. This great analyst session turned into more of a podcast vibe, but you know what? (Larry laughs) To chill here at re:Mars, thanks for coming on, and we unpacked a lot. Thanks for sharing. >> Both: Thank you. >> Appreciate it. We'll get you back on. We'll get you in the rotation. We'll take it virtual. Do a panel. Do a panel, do some panels around this. >> Larry: Absolutely. >> Andy: Oh this not virtual, this physical. >> No we're live right now! (all laugh) We get back to Palo Alto. You guys are influencers. Thanks for coming on. You guys are moving the market, congratulations. Take a minute, quick minute each to plug any work you're doing for the people watching. Larry, what are you working on? Andy? You go after Larry, what you're working on. >> Yeah. So since I started my company, RobustCloud, since I left IDC about a year ago, I'm focused on edge computing, cloud-native technologies, and Low Code/No Code. And basically I help companies put their business value together. >> All right, Andy, what are you working on? >> I do a lot of work on the AIML areas. Particularly, last few of my reports are in the AI Ops incident management and ML Ops areas of how to generally improve your operations. >> John: Got it, yeah. >> In other words, how do you use the AIML to improve your IT operations? How do you use IT Ops to improve your AIML efficiency? So those are the- >> John: The real hardcore business transformation. >> Yep. >> All right. Guys, thanks so much for coming on the analyst session. We do keynote review, breaking down re:Mars after day two. We got a full day tomorrow. I'm John Furrier with theCUBE. See you next time. (pleasant music)

>>Yeah. Hello and welcome to the Cubes Presentation of Women in text. Global event Celebrating International Women's Day I'm John for a host of the Cube were with Sally E. Senior Policy Advisor Global Foundation for Cyber Studies and Research. Sally, great to see you. Thanks for coming on the cue for International Women's Day. Appreciate it. >>Pleasure, John. Great speech again. >>Love your title. Global Foundation for Cyber Studies. Um, global is a big part of the theme this year. Uh, cyber studies. We're seeing a lot of cyber activity all around the world, networks, communities coming together, the role of data. I mean, everything is touching our lives. There are no boundaries anymore. What does it all mean? There's so much to talk about your in the middle of it before we get into it. Tell us about your career and your history. How you got interested in tech and what you're working on. >>Absolutely. I love it. Kind of this age of convergence coming together right now, isn't it? That's how I would describe it. And that's kind of a bit like my career. I think in many ways as well. So for the audience, really great to be here and share about that today, and I kind of say, three main palace, so one would be emergent technologies. So, you know, I started off right through from coding to advisory to CTO type roles as well also change management. And now I'm more advisors right across from a I to five G to to Iot and security, for example as well. Also passionate about education checking education for me. They always go hand in hand, some a professor at a number of universities and in my non for profit, we really do a lot of outreach around educational opportunities as well. And that third pillar opponent hinted at it already will be social impact. So really passionate about how we can use tech as a force for good things around sustainability right at the heart of that, but also around diversity equity and inclusion. So we do a lot of pro project your locally and globally around kind of reframing what a tech career looks like, giving people more democratised access. Those tech opportunities outside of that a bit like yourself, you know, podcast host and writer and speaker and things as well, so very much going to building that community around key tech topics. >>Well, folks watching should check it out on Twitter. She's that great content you mentioned Mobile World Congress. Before we get on camera, you mentioned convergence. I mean, we're at a time now. I got to ask you while I got you here before we get into the whole schools and career tech thing, we've seen this movie before, but never at this scale. The convergence and the confluence of education and scale of cloud computing, the ability to level up and get, um, I won't say democratised. That's kind of overused. But I'm just talking about like with cloud computing could be educated and in market with a job instantly. Um, the barriers just seem to be moving away because of the the openings and the roles are changing. So, more than ever, this whole new tech scene comes together in a way. Can you share your thoughts and vision because to me, we're seeing this happening at such a scale unprecedented in my career? >>It is. And that's one of those words that the part had been overused, unprecedented, but right now it really, really is. It's not just a speed of change. I think it's a scale of change as well. You know, I think previously we've talked about disciplines in silos to a certain extent. Haven't we know in terms of like, an AI special is, um or five g one or other disciplines as well? But really, now that convergence about what one tech enables another, it really is that smart technology coming together for more and more different use cases, but that residents around how important education is alongside that alongside process alongside culture and shared values as well it really is. It's kind of holistic integration of everything that matters at the moment. And it's evolving business models as well. You know, shared values rights centre stage around that MWC just come back from that, And the key topics there weren't just by G, it was the importance of ecosystem collaboration. For example, there are less tracks that were isolated on one technology. It was more this conflation of these different technologies coming together and what we can achieve from that from business but also for society so really exciting focus areas now things that maybe once or a few years ago, more than periphery. They're now absolutely centre stage. So it's good to see that progress in that area. And I love to advocate around that. >>And the education piece is so important, and we always stay here in Cuba. It's a data problem, right? Everything's a data problem when you look at schools and education is structured and unstructured data kind of our our systems right, So structured as schools, institutions, those kinds of career paths or education pathways. And then you haven't structured freeform communities, seeing a lot more education going on within groups. Um, off structured environments like schools, Can you and you do a lot with schools? Can you share more how you're doing? Um uh, work with schools specifically on the structured side to get girls into careers faster and tech? And then can you also comment on the other side? What's going on in the communities because it's it's kind of going on in parallel, but they're not mutually exclusive. >>No, absolutely community, absolutely key word that I love that, and I think when we're talking about diversity and technology, it's not just what we're doing now with what we're looking at is looking ahead, but also looking at future pipeline as well. So for me, I use this express a little bit. But change the narrative. That's what springs to mind for me when we're talking about that, and particularly for girls going into technology but also more broadly, diversity of experience. More broadly, we do have these drop offs, so UK is one example, but it is really representative of the global trends that we're seeing. Now. We get a drop off of girls in particular, taking ice subjects at GCSE level so kind of that subject choice choice at 12 to 14, that kind of area. We get the same thing at a level that's equivalent of 16 to 18 and then even safer university or even apprenticeships, whichever both equally valid. But even if people are taking those types of skills, they're not then choosing to apply them in their careers. So we're seeing these kind of three pillars where we need to intervene earlier. So for me, the more that we can do things you know from dedicated educational offers, but equally partnering with tech companies to do outreach around this area. We need to go in younger and younger is so important to address that. Why? Why are people thinking they can't? Why is his career not for me, for example, so addressing that is huge. And that's one of the things we do with my nonprofit that's called aspirational futures. We go into schools and two universities, but equally do things with older adults and re Skilling and up Skilling as well. Because again, we can't leave that behind either. There's something for all different kind of age groups and backgrounds here, but specifically, I think, in terms of getting people interested in this career, curiosity matters. You know, I think it's an underrated skills. So it's changing the narrative again. And what the tech career actually is, what skills are valid? You know, I mentioned, I have a coding background as a starter. But not all tech careers involve coding, particularly the rise of low code or no code, for example as well. So really valued skill. But so many other skills are valid as well, you know, creativity or emotional intelligence problem solving skills. So for me, I like to drive forward. All those skills can make a difference as an individual, as a team, so your you know your tech career. All those skills are valid and you can make a huge difference. And I also think, you know, just kind of really bringing to the fore what different types of projects you can be involved in in tech as well. And I found really resonating when you can talk about tech for good projects and show how you're making a difference about some of those big challenges. Um, that's kind of really kind of resonating responsible people as well. So again, the more we can show tangible projects where you can make a difference and the whole range of skills that are involved in that it really helps people to think differently and gain that skills confidence. So it's like, >>Well, that's awesome insight. I want to just double click on that for a second, because one the drop off. Can you just repeat the ages where you see the drop off with the drop offs are >>absolutely yeah, no problem, John. So it's kind of when you're making your first choices around your first kind of qualifications. Between that 12 to 14 age group, 16 to 18 and then 18 to 21 I think we've really got to tackle that So again the earlier we can go in the better and again supporting people within organisations as well. So I do a lot of work like internally, with organisations as well people looking to up skill and re skill. You mentioned about data and the importance of data literacy earlier on in the conversation as well. For example, going into organisations and really helping to support people in all roles, not just tech facing roles develop that skills, confidence as well. So for me it's access to skills really bringing forward the difference. You can make that holistic range of skills that makes a difference, but also the confidence to apply them as well. You know, we talk about agility, of organisations, a lot areas, one of those kind of words in the last 12 months. But maybe we don't talk about personal agility and team agility as well. So I kind of talked about it. This little toolbox, if we can give people more and more things to draw from it, the only constant is this rate of change. If you've got more things in your armoury to cope with that and be an agile to that. It takes that fear away about what happens next because you feel you've got more skills to dip into it and to apply. So for me, it's that that confidence, not just the access to the skills >>and the other thing, too, I thought was insightful. I want to just reiterate and bring to the surface again as skills, right? So you don't have to be a coder. And I see I have two daughters just with my family. Yeah, I do python. They kind of put their toe in the water cause it's cool. Maybe that's a path, and they kind of don't like, maybe get into it. But it's not about coding anymore because you said low code, no code. Certainly. Maybe AI writes the code. We all see that happening. It's problem solving. It's you could be in health care and you could be nerd native, as we say, as on some of the other interviews of that year at the problem, solving the aperture of skills is much broader now. Can >>you share more than >>more than because with your with your programme and your nonprofit, I know you're in the middle of it, and this is important to get that out there. >>Absolutely so skills. You know, I think we need to change the focus on what skills make a difference if you see what I mean. I think you're absolutely right. There's some misconceptions about, you know, you want to go into tech, you need to be a coda. And you're right with the upscale around low Skilling. Sorry, Low code and the code opportunities. Um, I think the niches around being a specialist. Koda. We're gonna get more roles in that area, but in other areas, we need to look at different skills gap. So I'm advising people to look at where the gaps are now. So cyber security is a key example of that testing architecture. Those gaps are getting bigger. Their amazing skills, opportunities. They're so focused on a particular discipline. But it's all those skills that surround that that make a difference as well. So as I mentioned, you know, e Q creativity, communication skills, because it's not just about having the skills to build the future, knew that imagination to refocus about what that could even be. You know, that was one of the MWC 20 to refrain, reimagine and I love to kind of galvanise that spirit and people that you can be part of that, you know, wherever you are now. And I actually run a little series called 365, and you mentioned something right at the start of our conversation about International Women's Day being such an important focus area. But also we need to think about this beyond that as well. So hence that's the title of the series that I run because it's a focus on that every single day of the year. You know, I interviewed people that could be a C suite roles, but equally I've had some amazing interviews with 12 to 14 year olds, even younger, the youngest of the seven year old. He's doing like an amazing project in their kitchen with a three D printer working with local school or a hospice doing something around Ukraine. Another project we're doing at the moment, actually, and it's so resonating it's trying to show people wherever you are now, wherever you want to be, there's somebody relatable that you can make. You can see whatever sector, in whatever age, whatever background, and I think it's to give that inspiration. Hey, you know what I can do that that can be me. So visibility of role models, it really matters. And to really broaden out what role model looks like, you know? >>And then I think people out there you see yourself. I mean, this is what we been >>proven right? >>It's proven I want to get into the aspirational futures thing that you have going on, and I know this is important to you, but also something else you said was, is that there's more jobs open and say cybersecurity than ever before. And you're seeing this trend where all these new roles are emerging because of the tech that weren't around years ago, right? And so we've been having conversations in the Cube saying, Hey, all these roles are new, but also problems are new to these New new problems are surfacing because of the this new environment we're in. So these new roles still have to solve problems, so we need people to solve those problems. This is the future. This is the conversation that people are trying to get zero in on misinformation, cybersecurity, you name it. Society is changing with >>new. You >>have new new problems and new opportunities. Could you share your aspirational future? How you vector into that? >>Yeah, absolutely. And for me it's just again that we're convergence around people in technology and partnership, and that's what we aim to do. We do projects at a very local level, but equally we do them at national and international level as well. And one of our kind of people assume I'm talking pillars a lot, but I like it as a framework. So one of those esteem learning. So putting an equal value on the arts as well as science, technology, engineering, mathematics because I think they are. You know, as I mentioned before, hand that imagination, creativity, curiosity, collaboration, skills. They're equally valid as a different types of tech skills as well. We need an equal value and all of them. I think that's hugely important, important today. I think over the last 5 to 10 years, maybe there's been less of a focus within curriculums on the arts area than the other areas. So for me, putting that equal focus back is hugely important to navigate change, you know, I think that's that's that's absolutely key. So we focus on that area and we do a whole range of tech for good projects, and that's the way we help people to learn, you know, for example, data 90% at the moment of data isn't touched again when it's archived after three months. How can we turn that into a learning opportunity? For example? Some of the projects we use some of this is not going to be used again. We do it in a very safe, secure way, but we use that as one of our training aids, and then we apply them for local projects. We have initiatives from hackathons and ideation right through to very tangible hubs that we've actually built out where people can go, learn up skill and kind of learn through play and experimentation as well. Because again, I think that sometimes under explored that type of value and that freedom to be able to do that. And we also do things, change management skills. We talk about agile learning, agile technology need agile change management as well. So it's a very holistic skills. Look at what you need to navigate that future and have the confidence to apply them. So steam is very much our focus, applying them for tech for good projects and doing that externally, but also within organisations as well. So that very much is shared value approach to good business, but good for society as well. So yes, that this toolbox, that technology I applied earlier we really try and give people that support. To be able to do that, to move forward with confidence and optimism. >>I think adding the aid to stem really for steam is really smart because entrepreneurship or any problem solving creativity is the spark of innovation. >>And that's a super >>important skill. And we've seen it, whether it's startup or in a big company or in society, so super, super insightful. So I got to ask you, as a policy senior policy advisor on cyber studies globally, what are the core issues you're looking at right now? What are you shutting the light on and what's the most important thing you're working on? And then what's the most important thing you're working that people aren't talking about, that people should pay attention to >>Absolutely so. One of my key roles of the foundation is is kind of share of global trust. Essentially, um, and again trust is that one of the key issues of our time? One thing that people are talking about so much that relates with that actually is there's there's research from a group called The Woman. They've been looking at this for about 17 years or so. The research that came out most recently and I've got some original research that kind of support this as well is that for the first time ever, consumers are looking at organisations like tech organisations and other large organisations, in particular the enterprise level, really, as the bastions of trust to a bigger extent than NGOs or even governments. And that's the first time we've seen it at that level. So trust really really matters. It's one of the biggest differentiators of our time, so we're trying to help people. How do you establish trust? How do you build transparency, commitment and accountability, particularly in areas where there's currently confusion, so as one example going back Security zero Trust That phrase is used an awful lot, isn't it? But it's sometimes causing some confusion. Actually, it against what it's trying to deliver if you see what to me. So now I just do something recently with SMB s in particular and there is a confusion that effectively, you know, you could You could buy off the shelf and it's once and done. Um, And then we're sorted for the zero Trust security. And obviously it's not like that. It's an ongoing journey, and there's so many different constituent parts. So there's some things I'm seeing at the moment in the market with there's confusion around around certain language, for example. So again it goes back to backing things up with the technology but also research and awareness so we can see where those skills gaps are. You can see where there's awareness gaps are we can help to fill them. So that's an important part of that particular role bringing the technology in the culture and the education hand in hand together. So it's something I'm really passionate about, and for me sort of related to this, Um, I do a lot of work around S G, um, to the sustainable development goals. In particular, environmental and social governance is something that's becoming much more of a bigger kind of centre stage conversation. I'm an action point in a moment which is fantastic because this is something I've been involved in kind as long as I can remember. So I work directly with organisations like, um Unesco, lots of different professional bodies. It's kind of a huge driver for me. So one thing to kind of look out for that's coming very soon. I'm seeing an issue around around measurement in this area. You know, we're seeing consumers becoming more and more conscious and employees, you know you want to work for by from advocate organisations that have that same value alignment that you have personally and professionally, hugely important. We're seeing some great reports coming out around better e S g measurement. But it can be hard to compare between different organisations, so we are getting more transparency. But it's difficult sometimes to make fare comparisons. Um, so what I'm trying to do a lot of work on at the moment is how you go beyond that transparency to commitment to accountability and that deeper level and that comparability. So I would say kind of to the audience moment, Look out for a bit of a new index. It's going to help people, I think, make those conscious choices make informed choices. So it's something I'm super, super passionate about. I want to try and take that to next level in terms of its actualisation. >>That's awesome. And certainly we'll link to it on our site. All the work you're doing on interviews will put links there as well. We'll make sure we'll follow up on that. Great to have you on. You're such an inspiration. Amazing work, cutting edge work. And I'm I'm super impressed with the cyber studies, and I think this is really important. I have to ask you a final question because you're in the middle of it again with covid and the unfortunate situations we've been living with Covid. And now, obviously with this Ukraine situation that the cyber has been pulled to the front of the agenda and you're seeing a cultural shift. You certainly got Web three. Cyber is now part of everyone's life, and they can see it. They've been seeing it living it. Everything's been pulled forward as a cultural shift happening, okay, and and it's really interesting right now, and I want to get your thoughts because this now people are now aware what cyberwar means cyber security cyber. At home, I have remote work. Cyber has become front and centre or digital. However you want to call it in our lives pulled forward. >>So I'm not even sure in some >>cases, maybe rightfully so, and others. What's your view on this whole cultural cyber being pulled forward? >>It is. It's really, really interesting. And so one of the things I do is I am now ready to a Cyber Insights magazine as well. So we're developing a lot of content pieces around this and lots of things I'm seeing here. So your covid point, I think one of the most interesting things there is around literacy. For example, you remember when we went back to 18 months ago? We're having daily briefings, whether that's from from UK Parliament or the U. S. Equivalent. And different phrases were coming into everyday language driven by the curve or driven by the data. And they're coming into everyday life and people family kitchen table. It was something that hasn't been spoken about before, but suddenly it was driving everyday decision making and what you could and couldn't do. And that's raised awareness. And I think it helped people to ask better questions and to challenge things that they're seeing. And where has that data come from? How has it been presented to have seen that there? I think similarly, where we're having that same understanding and raise of questioning around what we're hearing around cyber as well. You're looking at where that source has come from, and how can we look at that in a different way? So again, I think it's raising that awareness, which is really, really crucial, >>the >>other thing as well around cyber security in particular. And again, I don't think this is talked about as much. When we talk about aspects around inclusion, we talk about diversity equity. Um, I'll see inclusion. I talk about belonging a lot as well. I think there's other aspects around sustainability that Inter relate as well, because when we find, for example, communities that are not included, they tend to be more adversely affected by, for example, climate factors as well. There's an interrelation. They're equally We find that people that haven't got, for example, the same level of cybersecurity protection are also in that same. There's an interrelation across all those elements were not talking about that either. So that's the other thing. I want to kind of bring attention to their again. They aren't separate conversations is a huge crossover between these different conversations and actions that we can do to make a difference. So there's some positive aspects about things that have happened over the last period of time and also some challenges that if we're aware of them, we can work together again, that collaboration piece to be able to overcome them. You know, I've got I've got a book coming out, all for charity called Tech for Good and one of my kind of tag lines. There is around contagion of positive change. Again, let's reframe the language around what's been happening. And let's kind of put that together is something that's far more positive. >>Language is super important, great >>content here. So >>thanks so much for coming. I really appreciate all the great insight and taking the time out of your busy day to to join us here in the Cube. Women in tech Global Event. Thank you so much. >>My absolute pleasure. Thank you. Thank you all for watching. >>Okay. The cubes presentation of women in text. Global event Celebrating International Women's Day. I'm John for a host of the Cube. Thanks for watching

(upbeat music) >> Welcome to this Cube conversation sponsored by Citrix. This is the third and final installment in the Citrix launchpad series. We're going to be talking about the launchpad series for work. Lisa Martin here with Dion Hinchcliffe, VP and principal analyst at Constellation research. Dion, welcome to the program. >> No, thanks Lisa. Great to be here. >> So we have seen a tremendous amount of change in the last 18, 19 months. You know, we saw this massive scatter to work from home a year and a half ago. Now we're in this sort of distributed environment. That's been persisting for a long time. Talk to me about, we're going to be talking about some of the things that Citrix is seeing and some of the things that they're doing to help individuals and teams, but give me your lens from Constellation's perspective. What are some of the major challenges with this distributed environment that you've seen? >> Sure. Well, so we've gone from this, you know, the world of work, the way that it was now, we're all very decentralized, you know, work from anywhere. Remote work is really dominating, you know, white collar types of activities in the workplace and workplaces that in our homes for most of us even today. But that started to change. Some people are going back. Although I just recently spoke to a panel of CIOs that says they have no plans anytime soon, but they're very aware that they need to have workable plans for when we start sending people back to the office and there's this big divide. How are we going to make sure that we have one common culture? We have a collaborative organization when, you know, a good percentage of our workers are in the office, but also maybe as much as half the organization is at home. And so, how to make processes seamless, how to make people collaborate and make sure there's equity and inclusion so that the people at home aren't left out and then people in the office, maybe you don't have an unfair advantage. So those are all the conversations. And of course, because this is a technology revolution, remote work was enabled by technology. We're literally looking at it again for this hybrid work, this, you know, this divided organization that we're going to have. >> You mentioned culture that's incredibly important, but also challenging to do with this distribution. I was looking at some research that Citrix provided, asking individuals from a productivity perspective, and two thirds said, hey, for our organizations that have given us more tools for collaboration and communication, yes, we are absolutely more productive. But the kicker is, the same amount of people, about two thirds that answered the survey said, we've now got about ten tools. So complexity is more challenging. It's harder to work individually. It's harder to work in teams. And so Citrix is really coming to the table here with the launchpad series for work, saying let's help these individuals and these teams, because as we, we think, and I'm sure you have insight Dion on this as well, this hybrid model that we're starting to see emerge is going to be persistent for a while. >> Yeah. For the foreseeable future. Cause we don't know what the future holds. So we'll have to hold the hybrid model as the primary model. And we may eventually go back to the way that we were. But for the next several years, there's going to be that. And so we're trying to wrap our arms around that. And I think that we're seeing with things like the Citrix announcements, a wave of responses saying, all right, let's really design properly for these changes. You know, we kind of just adapted quickly when everyone went to remote last year and now we're actually adding features to streamline, to reduce the friction, to simplify remote work, which does use, you have to use more applications. You have to switch between different things. You have to, you know, your employee experience in the digital world is just more cluttered and complicated, but it doesn't have to be. And so I, you know, we can look to some of these announcements for last year, I think address some of that. >> Let's break some of that down because to your point, it doesn't have to be complex complicated. It shouldn't be. Initially this scatter was, let's do everything we can to ensure that our teams and our people can be productive, can communicate, can collaborate. And now, since this is going to be persistent for quite some time, to your point, let's design for this distributed environment, this hybrid workforce of the future. Talk to me about the, one of the things that Citrix is doing with Citrix workspace, the app personalization, I can imagine as an individual contributor, but also as a team leader, the ability to customize this to the way that I work best is critical. >> And it really is, especially when you know, you have workers, you know, 18 or 19 months worth of new hires that you've never met. They don't really feel like, you know, this is maybe their organization. But if you allow them to shape it a little bit, make it contextual for them. So they don't just come into this cookie cutter digital experience that actually is kind of more meaningful for them. It makes it easier for them to get their job done and things are the way that they want them and where they want them. I think that makes a lot of sense. And so the app personalization announcements is important for remote workers in particular, but all workers to say, hey, can I start tailoring, you know, parts of my employee experience? So they make more sense for me. And I feel like I belong a little bit more. I think it's significant. >> It is. Let's talk about it from a security perspective though. We've seen massive changes in the security landscape in the last year and a half. We've seen some Citrix data that I was looking at, said between 2019 and 2020, ransomware up 435%, malware up 358%. And of course the weakest link being humans. Talk to me from a Citrix workspace perspective about some of the things that they've done to ensure that those security policies can be applied. >> Well, and the part that I really liked about the launchpad announcements around work in terms of security was this much more intelligent analysis. You know, one of the most frustrating things is you're trying to get work done remotely and maybe you're you're in crunch mode and all of a sudden the security system clamps down because they think you're doing something that, you know, you might be sharing information you shouldn't be and now you can't, get your deadline met. I really liked how the analytics inside the new security features really try to make sure they're applying intelligent analysis of behavior. And only when it's clear that a bad actor is in there doing something, then they can restrict access, protect information. And so I have no doubt they'll continue to evolve the product so that it's even even more effective in terms of how it can include or exclude bad actors from doing things inside your system. And so this is the kind of intelligence security increasingly based on AI type technologies that I think that will keep our workers productive, but clamp down on the much higher rate of that activity we see out there. Because we do have so many more endpoints there's a thousand or more times more endpoints in today's organizations because of remote work. >> Right. And one of the things that we've seen with ransomware, I mentioned those numbers that Citrix was sharing. It's gotten so much more personalized, so it's harder and harder to catch these things. One of the things that I found interesting, Dion, that from a secure collaboration perspective, that Citrix is saying is that, you know, we need to go, security needs to go beyond the devices and the endpoints and the apps that an employee is using, which of which we said, there are at least 10 apps that are being used today and it needs to actually be applied at a content level, the content creation level. Talk to me about your thoughts about that. >> I think that's exactly right. So if you know the profile of that worker and the types of things they normally do, and you see unusual behavior that is uncharacteristic to that worker, because you know their patterns, the types of content, the locations of that content that they might normally have access to. And if they're just accessing things, you know, periodically, that's usually not a problem. When they suddenly access a large volume of information and appear to be downloading it, those are the types of issues and especially of content they don't normally use for their work. Then you can intervene and take more intelligent actions as opposed to just trying to limit all content for example. So that knowledge workers can actually get access to all that great information in your IT systems. You can now give them access to it, but when clearly something, something bad is happening, the system automatically does it and steps in. >> I was looking at some of the data with respect to updates to Citrix analytics that it can now auto change permissions on shared files to read only, I think you alluded to this earlier, when it detects that excess sharing is going on. >> And, inappropriate access sharing. So sometimes it's okay for a worker to access, you know, documents. But the big fear is that a bad actor gets access. They get a USB key and they download a bunch of files and they get a whole bunch of IP or important knowledge. Well, when you have a system that's continually monitoring and you know, the unblinking gaze of Citrix security capabilities are looking at the patterns, not just the content alone or just the device alone, but at the, at the usage patterns and saying, I can make this read only because that's clearly the, you know, we don't want them to be able to download this because this activity is completely out of bounds or very unusual. >> Right. One of the things also that Citrix is doing is integrating with Microsoft teams. I was listening to a fun quiz show the other day that said, what were the top two apps downloaded in 2020? And I guessed one of them correctly, Tiktok though. I still don't know how to use it. And the second one was Zoom, and I'm sure Microsoft teams is way up there. I was looking at some stats that said, I think as of the spring of 2020, there were 145 million daily users of Microsoft teams. So that, from a collaboration perspective, something that a lot of folks are dependent on during the pandemic. And now within Teams, I can access Microsoft workspace? Citrix workspace. >> Yes. Well, and it's more significant than it sounds because there's a real hunger to find a center of gravity for the employee experience. What do I put that? Where should they be spending most of their time? Where should I be training them to focus most of their attention? And obviously workers collaborate a lot and Teams as part of Office 365, is a juggernaut? You know, the rise of it during the pandemic has been incredible. And just to show this, I have a digital workplace advisory board. Its companies who are heading, are the farthest along in designing digital employee experiences, and 31% of them said, this January, they're planning on centralizing the employee experience in Teams. Now, if you're a Citrix customer, you have workspace you go, how do I, I don't want to be left out. This announcement allows you to say, you can have the goodness of teams and its capabilities and the power of Citrix workspace, and you have them in one place and really creating a true center of gravity and simplifying and streamlining the employee experience. You don't have this fragmented pieces. Everything's right there in one place, in one pane of glass. And so I like this announcement. It brings Citrix up to parody with a lot of their competitors and actually eclipses several of them as well. So I really like to see this. >> So then from within teams, I can access Citrix workspace. I can share documents with team members and collaborate as well as that kind of the idea. >> Yes. That is the idea, and of course, they'll continue to evolve that, but now you can do your work in Citrix workspace and when documents are involved and you want to bring your team in, they're already right there inside that experience. >> That ability to streamline things, so critical, given the fact that we're still in this distributed environment, I'm sure families are still dealing with some, some amount of remote learning, or there's still distractions from the, do I live at work, do I work from home environment? One of the grips I really felt for when this happened, Dion, was the contact center. I thought these poor people, more people now with shorter and shorter fuses trying to get updates on whatever it was that they were, if they had something ordered and of course all the shipping delays. And the contact center of course went (blowing sound) scattered as well. And we've got people working from home, trying to do their jobs. Talk to me about some of those things that Citrix is doing to enable with Google, those contact center workers to have a good experience so that ultimately the employee experience is good, so is the customer experience? >> The contact center worker has the toughest of all of the different employee profiles I've seen, they have the most they have to learn, the most number of applications. They're typically not highly skilled workers. So they might only just have a, you know, high school education. Yet, they're being asked to cram all of these technologies, each one with a different employee experience, and they don't stay very long as a result of that. You might train them for two months before they're effective and they only stay for six months on average. And so, both businesses really want to be able to streamline onboarding and provisioning a and getting them set up and effective. And they want it too, if you want happy contact center workers making your customers happy and staying around. And so this announcements really allows you to deploy pre-configured Citrix workspaces on, on Chrome OS so that, you know, if you need to field a whole bunch of workers or you have a big dose say you're a relief company and you have a lot of disaster care workers. You can certainly this issue that these devices very easily, they're ready to go with their employee experience and all the right things in place so they can be effective with the least amount of effort. So I guess, it's a big step forward for a worker that is often neglected and underserved. >> Right. Definitely often neglected. And you, you brought up a good point there. And one of the things that, that peaked in my mind, as you talked about, you know, the onboarding experience, the retention, well, these contact center folks are the front lines to the customer. So from a brand reputation perspective, that's on the line, for companies in every industry where people with short fuses are dealing with contact center folks. So the ability to onboard them to give them a much more seamless experience is critical for the brand reputation, customer retention for every industry, I would imagine. >> Absolutely. Especially when you're setting up a contact center or you have a new product launching and you want, you know, you've got to bring, onboard all these new workers, you can do it, and they are going to have the least challenges. They're going to be ready to go right out of the box, be able to receive their package, with their device and their Citrix employee experience, ready to go. You know, just turn the machine on and they're off to the races. And that's the vision and that's the right one. So I was glad to see that as well. >> Yeah. Fantastic. One of the things also that Citrix did, the Citrix workspace app builder, so that Citrix workspace can now be a system of record for certain things like collaboration, surveys, maybe even COVID-19 information, that system of record. Talk to me about why that's so critical for the distributed worker. >> So we've had this, this longstanding challenge in that we've had our systems of record, you know, these are CRM systems, ERP, things like that, which we use to run our business. And then we've had our collaboration tools and they're separate, even though we're collaborating on sales deals and we're collaborating on our supply chain. And so like, the team's announcement was in the same game. We can say, let's close that gap between our systems of record and our collaboration tools. Well, this announcement says, all right, well, we still have these isolated systems of record. How can we streamline them to build and start connecting together a little bit so that we have processes that might cross all of those things, right? It's still going to order comes in from the CRM system. Then you can complete it in the, in the ERP system, you know, ordering that product for them. So they actually get it. You know, and that's probably overkill, that scenario for this particular example. But for example, collecting data from workers saying, let's build some forms and collect some data and then feed it to this process, or this system record. You can do it much more easily than before, before you would have to hire a development team or a contractor to develop another system that would integrate, you know, CRM or ERP or whatever. Now you can do it very quickly inside that builder. First simple, basic applications, and get a lot of the low hanging fruit off your plate and more automated inside of your Citrix workspace. >> And automation has been one of the keys that we've seen to streamlining worker productivity in the last 18 months. Another thing that I was looking at is, you know, the fact that we have so many different apps and we're constantly switching apps, context is constantly changing. Is this sort of system of record going to allow or reduce the amount of context switching that employees have to do? >> Yep. Almost all of these announcements have some flavor to that saying, can we start bringing more systems together in one place? So you're not switching between applications. You don't have different and disconnected sets of data that if you need to, and if they are disconnected, you can connect them, right. That's what the app builder announcement again is about saying, all right, if you're already, always using these three applications to do something, and you're switching between them, maybe you can just build something that connect them into one experience and, you know, maybe a low level of IT person, or even a business user can do that. That's the big trend right now. >> That's so important for that continued productivity, as things will continue to be a little bit unstable, I guess, for awhile. One more thing that I saw that Citrix is announcing is integrations with, Wrike I've been a Wrike user myself. I like to have program project management tools that I can utilize to keep track of projects, but they've done a number of integrations, one of them with Wrike Signature, which I thought was really cool. So for, to secure e-signature within Wrike, based on a program or a project that you're working on. Talk to me about some of the boosts to Wrike that they've done and how you think that's going to be influential in the employee experience. >> Well, first let's just say that the Wrike acquisition was a really important one for Citrix to go above just the basic digital workplace and simple systems of record. This is a really a mass collaboration tool for managing work itself. And so they're, this is taking Citrix up the stack in the more sophisticated work scenarios. And, and when you, we are in more sophisticated work scenarios, you want to be able to pull in different data sets. So, you know, they have the Citrix ShareFile support. You want to be able to bring in really important things like, you know, signing contracts or signing sales deals or mortgage applications, or all sorts of exciting things that actually run in your business. And so, Wrike Signatures, support's really important so that when you have key processes that involve people putting signatures on documents, you can just build collaborative work management flows that, that take all that into account without having to leave the experience. Everything's in one place as much as possible. And this is the big push and we need to have all these different systems. We don't have too many apps. What we have is too many touchpoints, so lets start combining some of these. And so the Wrike integrations, really help you do that. >> Well, and ultimately it seems like what Citrix is doing with the work launchpad series. All the announcements here is really helping workers to work how and where they want to work. Which is very similar to what we say when we're talking about the end user customer experience. When tech companies like Citrix say, we have to meet our customers where they are, it sounds like that's the same thing that's happening here. >> It is. And I would just add on top of that and to make it all safe. So you can bring all these systems together, work from anywhere, and you can feel confident that you're going to do so securely and safely. And it's that whole package I think that's really critical here. >> You're right, I'm glad you brought up that security. All right, Dion take out your crystal ball for me. As we wrap things up, you're saying, you know, going into the future, we're going to be moving from this distributed workforce to this hybrid. What are some of the things that you see as really critical happening in the next six to nine months? >> Well, there's a real push to say, we need to bring in all the workers that we've hired over the last year. Maybe not bringing them in, in person, but can we use these collaborative tools and technologies to bring them, hold them closer so they get to know us. And so, you know, things like, having Microsoft teams integrated right into your Citrix workspace makes it easier for you to collaborate with remote workers and inside any process wherever you are. So whether you're in the office or not, it should bring workers closer, especially those remote ones that are at risk of being left out as they move to hybrid work. And then it's really important. And so the things like the app builder are going to also allow building those connections. And I think that workers and businesses are really going to try and build those bridges, because the number one thing I'm hearing from business leaders and IT leaders is, is it, you know, we're worried about splitting into two different organizations, the ones that are remote and the ones that are in the office and any way that we can bring all of them together in an easy way, in a natural way, situate the digital employee experience so that we really back or back to one company, one common culture, everybody has equal access and equity to the employee experience. That's going to be really important. And I think that Citrix launchpad announcements around work really are a step, a major step in the right direction for that. There's still more things that have to be done and all, all vendors are working on that. But it's nice to see. I really liked what Citrix is doing here to move the ball forward towards where we're all going. >> It is nice to see, and those connections are critically important. I happen to be at an in-person event last week, and several folks had just had been hired during the pandemic and just got to meet some of their teams. So in terms of, of getting that cultural alignment, once again, this is a great step towards that. Dion thank you for joining me on the program, talking about the Citrix launchpad series for work, all the great new things that they're announcing and sharing with us as some of the things that you see coming down the pike. We appreciate your time. >> Thanks Lisa, for having me. >> For Dion Hinchcliffe. I'm Lisa Martin. You're watching this Cube conversation. (upbeat music)

>>it's mhm Okay, we're here in the cube unpacking the HPD Green Lake announcements, Daniel neumann series Principal analyst and founder of your um research Damn. You're good to see you again, >>Dave always going to jump jump on with you. It's good to have a minute sit down. So >>what's your favorite announcement from from Green Lake? What do you, what do you make of what they announced today? >>Well, I love the opportunity for the company to position itself up against a growth monster like snowflake. I mean looking at the ability to handle the breath of the data at scale and offer a data service that can compete in that space. That's exactly the kind of narrative that I think the markets, the outside world is going to want to hear from HP is how you're not just competing with your traditional, the doubles, the Ciscos, the IBM, you're going after the, the mega growth cloud players and data services. And for me that's really attractive because I've been really on top of hb saying, hey, you're doing a lot of the right things, but people have to feel and see the growth. >>To me this is a major move toward the tam expansion strategy. It's kind of the job of every Ceo right, is to expand the tam. And I'm interested to see how HP e plays this and communicates this because, you know, traditionally it's a hardware company, uh moving into data management Data services. That's an enormous market. We'll talk about how important data is but the data management is just huge. And to do it in a cloud like fashion, how do you see that as potentially expanding the total available market for HP? >>Well, first, let's just almost walking back a second, Dave HP is a cloud player. Okay. And that's the story that it is trying to get out there. It is not a hardware player that's tinkering in software. Hp has done software, this isn't its first go. But if you want to be a cloud player, you look at the big hyper scale as you look at the AWS, as you look at the google, you look at as the google built, not just on hardware, it's built that big C and I've had this conversation before, all the things that make up the cloud, it's the hardware, it's the software, it's the services, the platform, you got to put all these things together. And if HP wants to be a public cloud experience, taking advantage of where we're moving with hybrid and offering it private, it has to have that same subset of services. Look at the investment, whether it's been a W S or google or Azure in data services, HP has to be in this space. So, seeing this come to fruition, in my opinion, is directionally the right path, getting it to be well received, winning the right customers and showing the growth from these investments is going to be the next important phase. >>Do you see that as a service model as being more margin friendly for HP and and if so why? Well, I think >>universally we found there's two major improvements that moving to the as a service. One is, it does over time create expanded operational margin. It's just economies of scale. You can utilize every resource more efficiently. Of course there are Capex expenses, You've seen the amount that hyper skeletons have had to spend to expand their their footprints globally. So there is some Capex upfront but that also on the back end creates the depreciation and different bottom line profit creators. At the same time though, as a service is huge for the multiples and evaluation, which by the way is one of the things that has been a real in focus point for H. P. E. Is how does it up that that number, You know, you look at the snowflakes, not even profitable but getting huge. You know, um, you know, huge multiples on revenue. And then you see even the other hyper scale is all getting bigger plays on revenue and on E. P. S. Most of it has to do with the fact that recurring revenue is beloved by investors, but it's also really sticky and creates a ton of stability within the company for the culture of the business to say, hey, we have customers, they're going to stay with us. They're not going anywhere. They're subscribed to our services. They're buying into what we're doing and by the way, net revenue expansion as you get them sticky, you layer in new services. We've seen how this has worked across the board with public cloud, with software with SAS, can HP do it as well? And of course it's been something they're doing, but it's something we need to watch really closely and I think it's an opportunity that the company needs to lean into it. And I think they will, >>you mentioned snowflake a couple times, there's a there's a, there's a discussion in the industry, it was sort of prompted by martin casado and sarah wang about repatriation and particularly as it relates to software, saas companies uh that the the the cloud bill is so high at some point, they're giving away margin, so they're going to have to come back on prem, I'm not sure that to date that has applied to the general audience of customer, although there's a lot of debate as well between the expensive cloud, obviously, you know, egress charges. So it's hard sometimes to squint through that when you think about HP E bringing Green Lake to market at scale bringing repeatable processes, driving automation, etcetera. How do you think that that cloud repatriation argument, which frankly, I haven't seen a huge cloud repatriation in in the macro, but how do you think that will play out over time, Do you feel like the on prem play can be as cost effective or more cost effective or maybe you feel like it is already today? >>Well, I also listen to the injuries and Horowitz uh, repatriation narrative as well. I think there are economies of scale with cloud that companies have to look at closely. But I also think that has a lot to do with why hybrid has been sort of the story of the day. That's why hyper sailors are going on prem or, and that's why I'm primes are moving to the cloud is because it's always going to be some, you know, some group of different placements of workloads to ultimately get to that optimized result. And so, you know, when you look at, you know, sort of what you asked in my opinion, you know, ultimately it's all about the efficiency of your organization trying to accomplish what your business is. And will there be some repatriation of workloads possibly. But there will be a very important hybrid mix. And I think we're gonna continue to see that trend and I think that's exactly where everyone's going in. Hp is going as well. >>All right, then we've got to leave it there. Thanks so much for your insights, appreciate it. We're gonna definitely have you back you and I are going to do some cool stuff together. So we'll talk next time. Thanks all right, and thank you for watching, this is Dave Volonte for the keeps coverage of H P E Green Lakes announcement, keep it right there. Mm

>> From around the globe, it's theCUBE, covering Data Citizens '21. Brought to you by Collibra. >> For the past decade organizations have been effecting very deliberate data strategies and investing quite heavily in people, processes and technology, specifically designed to gain insights from data, better serve customers, drive new revenue streams we've heard this before. The results quite frankly have been mixed. As much of the effort is focused on analytics and technology designed to create a single version of the truth, which in many cases continues to be elusive. Moreover, the world of data is changing. Data is increasingly distributed making collaboration and governance more challenging, especially where operational use cases are a priority. Hello, everyone. My name is Dave Vellante and you're watching theCUBE coverage of Data Citizens '21. And we're pleased to welcome Michele Goetz who's the vice president and principal analyst at Forrester Research. Hello, Michele. Welcome to theCUBE. >> Hi, Dave. Thanks for having me today. >> It's our pleasure. So I want to start, you serve have a wide range of roles including enterprise architects, CDOs, chief data officers that is, analyst, the analyst, et cetera, and many data-related functions. And my first question is what are they thinking about today? What's on their minds, these data experts? >> So there's actually two things happening. One is what is the demand that's placed on data for our new intelligent digital systems. So we're seeing a lot of investment and interest in things like edge computing. And then how does that intersect with artificial intelligence to really run your business intelligently and drive new value propositions to be both adaptive to the market as well as resilient to changes that are unforeseen. The second thing is then you create this massive complexity to managing the data, governing the data, orchestrating the data because it's not just a centralized data warehouse environment anymore. You have a highly diverse and distributed landscape that you both control internally, as well as taking advantage of third party information. So really what the struggle then becomes is how do you trust the data? How do you govern it, and secure, and protect that data? And then how do you ensure that it's hyper contextualized to the types of value propositions that our intelligence systems are going to serve? >> Well, I think you're hitting on the key issues here. I mean, you're right. The data and I sort of refer to this as well is sort of out there, it's distributed at the edge. But generally our data organizations are actually quite centralized and as well you talk about the need to trust the data obviously that's crucial. But are you seeing the organization change? I know you're talking about this to clients, your discussion about collaboration. How are you seeing that change? >> Yeah, so as you have to bring data into context of the insights that you're trying to get or the intelligence that's automating and scaling out the value streams and outcomes within your business, we're actually seeing a federated model emerge in organizations. So while there's still a centralized data management and data services organization led typical enterprise architects for data, a data engineering team that's managing warehouses as in data lakes. They're creating this great platform to access and orchestrate information, but we're also seeing data, and analytics, and governance teams come together under chief data officers or chief data and analytics officers. And this is really where the insights are being generated from either BI and analytics or from data science itself and having dedicated data engineers and stewards that are helping to access and prepare data for analytic efforts. And then lastly, this is the really interesting part is when you push data into the edge the goal is that you're actually driving an experience and an application. And so in that case we are seeing data engineering teams starting to be incorporated into the solutions teams that are aligned to lines of business or divisions themselves. And so really what's happening is if there is a solution consultant who is also overseeing value-based portfolio management when you need to instrument the data to these new use cases and keep up with the pace of the business it's this engineering team that is part of the DevOps work bench to execute on that. So really the balances we need the core, we need to get to the insights and build our models for AI. And then the next piece is how do you activate all that? And there's a team over there to help. So it's really spreading the wealth and expertise where it needs to go. >> Yeah, I love that. You took a couple of things that really resonated with me. You talked about context a couple of times and this notion of a federated model, because historically the sort of big data architecture, the team, they didn't have the context, the business context, and my inference is that's changing and I think that's critical. Your talk at Data Citizens is called how obsessive collaboration fuels scalable DataOps. You talk about the data, the DevOps team. What's the premise you put forth to the audience? >> So the point about obsessive collaboration is sort of taking the hubris out of your expertise on the data. Certainly there's a recognition by data professionals that the business understands and owns their data. They know the semantics, they know the context of it and just receiving the requirements on that was assumed to be okay. And then you could provide a data foundation, whether it's just a lake or whether you have a warehouse environment where you're pulling for your analytics. The reality is that as we move into more of AI machine learning type of model, one, more context is necessary. And you're kind of balancing between what are the things that you can ascribe to the data globally which is what data engineers can support. And then there's what is unique about the data and the context of the data that is related to the business value and outcome as well as the feature engineering that is being done on the machine learning models. So there has to be a really tight link and collaboration between the data engineers, the data scientists, and analysts, and the business stakeholders themselves. You see a lot of pods starting up that way to build the intelligence within the system. And then lastly, what do you do with that model? What do you do with that data? What do you do with that insight? You now have to shift your collaboration over to the work bench that is going to pull all these components together to create the experiences and the automation that you're looking for. And that requires a different collaboration model around software development. And still incorporating the business expertise from those stakeholders, so that you're satisfying, not only the quality of the code to run the solution, but the quality towards the outcome that meets the expectation and the time to value that your stakeholders have. So data teams aren't just sitting in the basement or in another part of the organization and digitally disconnected anymore. You're finding that they're having to work much more closely and side by side with their colleagues and stakeholders. >> I think it's clear that you understand this space really well. Hubris out context in, I mean, that's kind of what's been lacking. And I'm glad you said you used the word anymore because I think it's a recognition that that's kind of what it was. They were down in the basement or out in some kind of silo. And I think, and I want to ask you this. I come back to organization because I think a lot of organizations look the most cost effective way for us to serve the business is to have a single data team with hyper specialized roles. That'll be the cheapest way, the most efficient way that we can serve them. And meanwhile, the business, which as you pointed out has the context is frustrated. They can't get to data. So there's this notion of a federated governance model is actually quite interesting. Are you seeing actual common use cases where this is being operationalized? >> Absolutely, I think the first place that you were seeing it was within the operational technology use cases. There the use cases where a lot of the manufacturing industrial device. Any sort of IOT based use case really recognized that without applying data and intelligence to whatever process was going to be executed. It was really going to be challenging to know that you're creating the right foundation, meeting the SLA requirements, and then ultimately bringing the right quality and integrity to the data, let alone any sort of data protection and regulatory compliance that has to be necessary. So you already started seeing the solution teams coming together with the data engineers, the solution developers, the analysts, and data scientists, and the business stakeholders to drive that. But that is starting to come back down into more of the IT mindset as well. And so DataOps starts to emerge from that paradigm into more of the corporate types of use cases and sort of parrot that because there are customer experience use cases that have an IOT or edge component to though. We live on our smart phones, we live on our smart watches, we've got our laptops. All of us have been put into virtual collaboration. And so we really need to take into account not just the insight of analytics but how do you feed that forward. And so this is really where you're seeing sort of the evolution of DataOps as a competency not only to engineer the data and collaborate but ensure that there sort of an activation and alignment where the value is going to come out, and still being trusted and governed. >> I got kind of a weird question, but I'm going. I was talking to somebody in Israel the other day and they told me masks are off, the economy's booming. And he noted that Israel said, hey, we're going to pay up for the price of a vaccine. The cost per dose out, 28 bucks or whatever it was. And he pointed out that the EU haggled big time and they don't want to pay $19. And as a result they're not as far along. Israel understood that the real value was opening up the economy. And so there's an analogy here which I want to come back to my organization and it relates to the DataOps. Is if the real metric is, hey, I have an idea for a data product. How long does it take to go from idea to monetization? That seems to me to be a better KPI than how much storage I have, or how much geometry petabytes I'm managing. So my question is, and it relates to DataOps. Can that DataOps, should that DataOps individual maybe live, and then maybe even the data engineer live inside of the business and is that even feasible technically with this notion of federated governance? Are you seeing that and maybe talk a little bit more about this DataOps role. Is it. >> Yeah. >> Fungible. >> Yeah, it's definitely fungible. And in fact, when I talked about sort of those three units of there's your core enterprise data services, there's your BI and data, and then there's your line of business. All of those, the engineering and the ops is the DataOps which is living in all of those environments and being as close as possible to where the value proposition is being defined and designed. So absolutely being able to federate that. And I think the other piece on DataOps that is really important is recognizing how the practices around continuous integration and continuous deployment using agile methodologies is really reshaping. A lot of the waterfall approaches that were done before where data was lagging 12 to 18 months behind any sort of insights, but a lot of the platforms today assume that you're moving into a standard mature software development life cycle. And you can start seeing returns on investment within a quarter, really, so that you can iterate and then speed that up so that you're delivering new value every two weeks. But it does change the mindset this DataOps team aligned to solution development, aligned to a broader portfolio management of business capabilities and outcomes needs to understand how to appropriately scope the data products that they're delivering to incremental value-based milestones. So the business feels that they're getting improvements over time and not just waiting. So there's an MVP, you move forward on that and optimize, optimize, extend scale. So again, that CICD mindset is helping to not bottleneck and wait for the complete field of dreams to come from your data and your insights. >> Thank you for that, Michelle. I want to come back to this idea of collaboration because over the last decade we've seen attempts, I've seen software come out to try to help the various roles collaborate and some of it's been okay, but you have these hyper specialized roles. You've got data scientists, data engineers, quality engineers, analysts, et cetera. And they tend to be in their own little worlds. But at the end of the day we rely on them all to get answers. So how can these data scientists, all these stewards, how can they collaborate better? What are you seeing there? >> You need to get them onto the same process. That's really what it comes down to. If you're working from different points of view, that's one thing. But if you're working from different processes collaborating is really challenging. And I think the one thing that's really come out of this move to machine learning and AI is recognizing that you need processes that reinforce collaboration. So that's number one. So you see agile development in CICD not just for DataOps, not just for DevOps, but also encouraging and propelling these projects and iterations for the data science teams as well or even if there's machine learning engineers incorporated. And then certainly the business stakeholders are inserted within there as appropriate to accept what it is that is going to be developed. So processes is number one. And number two is what is the platform that's going to reinforce those processes and collaboration. And it's really about what's being shared. How do you share? So certainly what we're seeing within the platforms themselves is everybody contributing into some sort of a library where their components and products are being ascribed to and then that's able to help different teams grab those components and build out what those solutions are going to be. And in fact, what gets really cool about that is you don't always need hardcore data scientists anymore as you have this social platform for data product and analytic product development. This is where a lot of the auto ML begins because those who are less data science-oriented but can build an insight pipeline, can grab all the different components from the pipelines to the transformations, to capture mechanisms, to bolting into the model itself and allowing that to be delivered to the application. So really kind of balancing out between process and platforms that enable and encourage, and almost force you to collaborate and manage through sharing. >> Thank you for that. I want to ask you about the role data governance. You've mentioned trust and that's data quality, and you've got teams that are focused on and specialists focused on data quality. There's the data catalog. Here's my question. You mentioned edge a couple of times and I can see a lot of that. I mean, today, most AI is are a lot of value, I would say most is modeling. And in the future, you mentioned edge it's going to be a lot of influencing in real time. And people maybe not going to have the time or be involved in that decision. So what are you seeing in terms of data governance, federate. We talked about federated governance, this notion of a data catalog and maybe automating data quality without necessarily having it be so labor intensive. What are you seeing the trends there? >> Yeah, so I think our new environment, our new normal is that you have to be composable, interoperable, and portable. Portability is really the key here. So from a cataloging perspective and governance we would bring everything together into our catalogs and business glossaries. And it would be a reference point, it was like a massive Wiki. Well, that's wonderful, but why just how's it in a museum. You really want to activate that. And I think what's interesting about the technologies today for governance is that you can turn those rules, and business logic, and policies into services that are composable components and bring those into the solutions that you're defining. And in that way what happens is that creates portability. You can drive them wherever they need to go. But from the composability and the interoperability portion of that you can put those services in the right place at the right time for what you need for an outcome so that you start to become behaviorally driven on executing on governance rather than trying to write all of the governance down into transformations and controls to where the data lives. You can have quality and observability of that quality and performance right at the edge and context of behavior and use of that solution. You can run those services and in governance on gateways that are managing and routing information at those edge solutions and we synchronization between the edge and the cloud comes up. And if it's appropriate during synchronization of the data back into the data lake you can run those services there. So there's a lot more flexibility and elasticity for today's modern approaches to cataloging, and glossaries, and governance of data than we had before. And that goes back into what we talked about earlier of like, this is the new wave of DataOps. This is how you bring data products to fruition now. Everything is about activation. >> So how do you see the future of DataOps? I mean, I kind of been pushing you to a more decentralized model where the business has more control 'cause the business has the context. I mean, I feel as though, hey, we've done a great job of contextualizing our operational systems. The sales team they know when the data is crap within my CRM, but our data systems are context agnostic generally. And you obviously understand that problem well. But so how do you see the future of DataOps? >> So I think what's kind of interesting about that is we're going to go to governance on greed versus governance on right more so. What do I mean by that? That means that from a business perspective there's two sides of it. There's ensuring that where governance is run is as we talked about before executing at the appropriate place at the appropriate time. It's semantically domain-centric driven not logical and systems centric. So that's number one. Number two is also recognizing that business owners or business operations actually plays a role in this, because as you're working within your CRM systems, like a Salesforce, for example you're using an iPaaS MuleSoft to connect to other applications, connect to other data sources, connect to other analytics sources. And what's happening there is that the data is being modeled and personalized to whatever view insight our task has to happen within those processes. So even CRM environments where we think of as sort of traditional technologies that we're used to are getting a lift, both in terms of intelligence from the data but also your flexibility and how you execute governance and quality services within that environment. And that actually opens up the data foundations a lot more and avoids you from having to do a lot of moving, copying centralizing data and creating an over-weighted business application and an over, both in terms of the data foundation but also in terms of the types of business services, and status updates, and processes that happen in the application itself. You're drawing those tasks back down to where they should be and where performance can be managed rather than trying to over customize your application environment. And that gives you a lot more flexibility later too for any sort of upgrades or migrations that you want to make because all of the logic is contained back down in a service layer instead. >> Great perspectives, Michelle, you obviously know your stuff and it's been a pleasure having you on. My last question is when you look out there anything that really excites you or any specific research that you're working on that you want to share, that you're super pumped about? >> I think there's two things. One is it's truly incredible the amount of insight and growth that is coming through data profiling and observation. Really understanding and contextualizing data anomalies so that you understand is data helping or hurting the business value and tying it very specifically to processes and metrics, which is fantastic as well as models themselves like really understanding how data inputs and outputs are making a difference whether the model performs or not. And then I think the second thing is really the emergence of more active data, active insights. And as what we talked about before your ability to package up services for governance and quality in particular that allow you to scale your data out towards the edge or where it's needed. And doing so not just so that you can run analytics but that you're also driving overall processes and value. So the research around the operationalization and activation of data is really exciting. And looking at the networks and service mesh to bring those things together is kind of where I'm focusing right now because what's the point of having data in a database if it's not providing any value. >> Michele Goetz, Forrester Research, thanks so much for coming on theCUBE. Really awesome perspectives. You're in an exciting space, so appreciate your time. >> Absolutely, thank you. >> And thank you for watching Data Citizens '21 on theCUBE. My name is Dave Vellante. (upbeat music)

>> From around the globe, it's theCube covering Data Citizens '21, brought to you by Collibra. >> For the past decade, organizations have been effecting very deliberate data strategies investing quite heavily in people, processes, and technology specifically designed to gain insights from data, better serve customers, drive new revenue streams, we've heard this before. The results quite frankly have been mixed. As much of the effort is focused on analytics and technology designed to create a single version of the truth, which in many cases continues to be elusive. Moreover, the world of data is changing, data is increasingly distributed making collaboration in governance more challenging especially where operational use cases are a priority. Hello, everyone, my name is Dave Vellante and you're watching theCube's coverage of Data Citizens '21. And we're pleased to welcome Michele Goetz, who's the Vice President and Principal Analyst at Forrester Research. Hello, Michele, welcome to theCube. >> Hi, Dave thanks for having me today. >> It's our pleasure. So I want to start, you serve have a wide range of roles including enterprise architects, CDOs, chief data officers that is, the analyst et cetera, and many data related functions. And my first question is what are they thinking about today? What's on their minds? These data experts. >> So there's actually two things happening. One is what is the demand that's placed on data for our new intelligent digital systems. So we're seeing a lot of investment and interest in things like edge computing. And then how does that intersect with artificial intelligence to really run your business intelligently and drive new value propositions, to be both adaptive to the market as well as resilient to changes that are unforeseen. The second thing is then you create this massive complexity to managing the data, governing the data, orchestrating the data, because it's not just a centralized data warehouse environment anymore. You have a highly diverse and distributed landscape that you both control internally, as well as taking advantage of third party information. So really what the struggle then becomes is how do you trust the data? How do you govern it and secure or protect that data? And then how do you ensure that it's hyper-contextualized to the types of value propositions that our intelligence systems are going to serve? >> Well, I think you're hitting on the key issues here. I mean, you're right, the data and I sort of refer to this as well as sort of out there it's distributed as at the edge, but generally our data organizations are actually quite centralized. And as well, you talk about the need to trust the data, obviously that's crucial. But are you seeing the organization change? I know you're talking about this to clients, your discussion about collaboration. How are you seeing that change? >> Yeah, so as you have to bring data into context of the insights that you're trying to get or the intelligence that's automating and scaling out the value streams and outcomes within your business. We're actually seeing a federated model emerge in organizations. So while there's still a centralized data management and data services organization led typically by enterprise architects for data, a data engineering team that's managing warehouses and data lakes. They're creating this great platform to access and orchestrate information, but we're also seeing data and analytics and governance teams come together under chief data officers or chief data and analytics officers. And this is really where the insights are being generated from either BI and analytics or from data science itself and having dedicated data engineers and stewards that are helping to access and prepare data for analytic efforts. And then lastly, this is the really interesting part is when you push data into the edge, the goal is that you're actually driving an experience and an application. And so in that case, we are seeing data engineering teams starting to be incorporated into the solutions teams that are aligned to lines of business or divisions themselves. And so really what's happening is if there is a solution consultant who is also overseeing value-based portfolio management when you need to instrument the data to these new use cases and keep up with the pace of the business, it's this engineering team that is part of the DevOps work bench to execute on that. So really the balances we need the core, we need to get to the insights and build our models for AI. And then the next piece is how do you activate all that and there's a team over there to help? So it's really spreading the wealth and expertise where it needs to go. >> Yeah, I love that you to, a couple of things that really resonated with me. You talked about context a couple of times and this notion of a federated model, because historically the sort of big data architecture, the team, they didn't have the context, the business context, and you're the, my inference is that's changing. And I think that's critical. Your talk at Data Citizens is called how obsessive collaboration fuels scalable DataOps. You talk about the data, the DevOps team. What's the premise you put forth to the audience? >> So the point about obsessive collaboration is sort of taking the hubris out of your expertise on the data. Certainly, there's a recognition by data professionals that the business understands and owns their data. They know the semantics, they know the context of it and just receiving the requirements on that was assumed to be okay. And then you could provide a data foundation whether it's just a lake or whether you have a warehouse environment where you're pulling for your analytics. The reality is that as we move into more of AI machine learning type of model, one, more context is necessary and you're kind of balancing between what are the things that you can ascribe to the data globally which is what data engineers can support. And then there's what is unique about the data and the context of about the data that is related to the business value and outcome as well as the feature engineering that is being done on the machine learning models. So there has to be a really tight link and collaboration between the data engineers, the data scientists, and analysts, and the business stakeholders themselves. You see a lot of pods starting up that way to build the intelligence within the system. And then lastly, what do you do with that model? What do you do with that data? What do you do with that insight? You now have to shift your collaboration over to the work bench that is going to pull all these components together to create the experiences and the automation that you're looking for. And that requires a different collaboration model around software development and still incorporating the business expertise from those stakeholders so that you're satisfying, not only the quality of the code to run the solution, but the quality towards the outcome that meets the expectation and the time to value that your stakeholders have. So data teams aren't just sitting in the basement or in another part of the organization and digitally, disconnected anymore. You're finding that they're having to work much more closely and side by side with their colleagues and stakeholders. >> I think it's clear that you understand this space really well, hubris out, context in, I mean, that's kind of what's been lacking. And I'm glad you said, you used the word anymore because I think it's a recognition that that's kind of what it was. They were down in the basement or out in some kind of silo. And I think, and I want to ask you this, I'll come back to organization because I think a lot of organizations, look the most cost effective way for us to serve the businesses to have a single data team with hyper-specialized roles, that'll be the cheapest way, the most efficient way that we can serve them. And meanwhile, the business which as you pointed out has the context is frustrated. They can't get to data. So this notion of a federated governance model is actually quite interesting. Are you seeing actual common use cases where this is being operationalized? >> Absolutely, I think the first place that you were seeing it was within the operational technology use cases. The use cases where a lot of the manufacturing, industrial device, any sort of IoT-based use case really recognized that without applying data and intelligence to whatever process was going to be executed, it was really going to be challenging to know that you're creating the right foundation, meeting the SLA requirements, and then ultimately bringing the right quality and integrity to the data, let alone any sort of data protection and regulatory compliance that has to be necessary. So you already started seeing the solution teams coming together with the data engineers, the solution developers, the analysts, and data scientists, and the business stakeholders to drive that. But that is starting to come back down into more of the IT mindset as well. And so DataOps starts to emerge from that paradigm into more of the corporate types of use cases and sort of parrot that because there are customer experience use cases that have an IoT or edge component to them. We live on our smart phones, we live on our smart watches, we've got our laptops, all of us have been put into virtual collaboration. And so we really need to take into account not just the insight of analytics, but how do you feed that, you know, feed that forward. And so this is really where you're seeing sort of the evolution of DataOps as a competency not only to engineer the data and collaborate, but ensure that there sort of an activation and alignment where the value is going to come out and still being trusted and governed. >> I've got kind of a weird question, but I'm going to (indistinct). I was talking to somebody in Israel the other day and they told me masks are off, the economy's booming. And he noted that Israel said, "Hey, we're going to pay up for the price of a vaccine, the cost per dose around 28 bucks," or whatever it was. And he pointed out that the EU haggled big time and they go, "We're going to pay $19." And as a result, they're not, you know, as far along Israel understood that the real value was opening up the economy. And so there's an analogy here, which I want to come back to my organization and it relates to the DataOps. If the real metric is, "Hey, I have an idea for a data product." How long does it take to go from idea to monetization? That seems to me to be a better KPI than, you know, how much storage I have or how much petabytes I'm managing. So my question is, and it relates to DataOps, can that DataOps, should that DataOps individual maybe live and then maybe even the data engineer live inside of the business and is that even feasible technically with this notion of federated governance? Are you seeing that? And maybe talk a little bit more about this DataOps role. Is it-- >> Yeah. >> Fungible? >> Yeah, it's definitely fungible. And in fact, when I talked about sort of those three units of there's your core enterprise data services, there's your BI and data and then there's your line of business. All of those, the engineering and the ops is the DataOps which is living in all of those environments and being as close as possible to where the value proposition is being defined and designed. So absolutely being able to federate that. And I think the other piece on DataOps that is really important is recognizing how the practices around continuous integration and continuous deployment using agile methodologies is really reshaping a lot of the waterfall approaches that were done before where data was lagging 12 to 18 months behind any sort of insights, but a lot of the platforms today assume that you're moving into a standard mature software development life cycle. And you can start seeing returns on investment within a quarter really, so that you can iterate and then speed that up so that you're delivering new value every two weeks. But it does change the mindset, this DataOps team align to solution development, align to a broader portfolio management of business capabilities and outcomes needs to understand how to appropriately stop the data products that they're delivering to incremental value based milestones. So the business feels that they're getting improvements over time and not just waiting. So there's an MVP, you move forward on that and optimize, optimize, extend scale. So again, that CICD mindset is helping to not bottleneck and wait for the complete field of dreams to come from your data and your insights. >> Thank you for that, Michele. I want to come back to this idea of collaboration 'cause over the last decade, we've seen attempts. I've seen software come out to try to help the various roles, collaborate and some of it's been okay, but you have these hyper-specialized roles. You've got data scientists, data engineers, quality engineers, analysts, et cetera. And they tend to be in their own little worlds. But at the end of the day, we rely on them all to get answers. So how can these data scientists, all these stewards, how can they collaborate better? What are you seeing there? >> You need to get them onto the same process, that's really what it comes down to. If you're working from different points of view, that's one thing. But if you're working from different processes, collaborating is really challenging. And I think the one thing that's really come out of this move to machine learning and AI is recognizing that you need processes that reinforce collaboration. So that's number one. So you see agile development in CICD not just for DataOps, not just for DevOps, but also encouraging and propelling these projects and iterations before the data science teams as well or even if there's machine learning engineers incorporated. And then, certainly the business stakeholders are inserted within there as appropriate to accept what it is that is going to be developed. So process is number one. Number two is what is the platform that's going to reinforce those processes and collaboration. And it's really about what's being shared. How do you share? So certainly what we're seeing within the platforms themselves is everybody contributing into some sort of a library where their components and products are being ascribed to and then that's able to help different teams grab those components and build out what those solutions are going to be. And in fact, what gets really cool about that is you don't always need hardcore data scientists anymore as you have this social platform for data product and analytic product development. This is where a lot of the auto ML begins because those who are less data science oriented but can build an insight pipeline, can grab all the different components from the pipelines to the transformations, to capture mechanisms, to bolting into the model itself and allowing that to be delivered to the application. So really kind of balancing out between process and platforms that enable and encourage and almost force you to collaborate and manage through sharing. >> Thank you for that I want to ask you about the role of data governance. You've mentioned trust and that's data quality and you've got teams that are focused on and specialists focused on data quality. There's the data catalog and here's my question. You mentioned edge a couple of times and I can see a lot of that. I mean, today, most AI is a lot of the AI, I would say most is modeling. And in the future, you mentioned edge. It's going to be a lot of inferencing in real-time. And you know people maybe not going to have the time or be involved in that decision. So what are you seeing in terms of data governance, federate, we talked about federated governance, this notion of a data catalog and maybe automating data quality without necessarily having it be so labor-intensive. What are you seeing trends there? >> Yeah, so I think our new environment, our new normal is that you have to be composable, interoperable, and portable. Portability is really the key here. So from a cataloging perspective, in governance we would bring everything together into our catalogs and business glossaries. And it would be a reference point. It was like a massive Wiki. Well, that's wonderful, but why just how's it in a museum you really want to activate that. And I think what's interesting about the technologies today for governance is that you can turn those rules and business logic and policies into services that are composable components and bring those into the solutions that you're defining. And in that way, what happens is that creates portability. You can drive them wherever they need to go. But from the composability and the interoperability portion of that, you can put those services in the right place at the right time for what you need for an outcome so that you start to become behaviorally-driven on executing on governance, rather than trying to write all of the governance down into transformations and controls to where the data lives. You can have quality and observability of that quality and performance right at the edge in context of behavior and use of that solution. You can run those services and in governance on gateways that are managing and routing information at those edge solutions and where synchronization between the edge and the cloud comes up. And if it's appropriate during synchronization of the data back into the data lake, you can run those services there. So there's a lot more flexibility and elasticity for today's modern approaches to cataloging and glossaries and governance of data than we had before. And that goes back into what we talked about earlier of like this is the new wave of DataOps. This is how you bring data products to fruition now everything is about activation. >> So how do you see the future of DataOps? I mean, I kind of been pushing you to a more decentralized model where the business has more control 'cause the business has the context. I mean, I feel as though, hey, we've done a great job of contextualizing our operational systems. The sales team, they know when the data is crap within my CRM, but our data systems are context agnostic, which you know, generally and you obviously understand that problem well but so how do you see the future of DataOps? >> So I think what's kind of interesting about that is we're going to go to governance on greed versus governance on right, more so. What do I mean by that? That means that from a business perspective there's two sides of it. There's ensuring that where governance is run as we talked about before executing at the appropriate place at the appropriate time. It's semantically domain centric driven not logical and systems centric. So that's number one. Number two is also recognizing that business owners or business operations actually plays a role in this because as you're working within your CRM systems like a Salesforce, for example, you're using an I-PASS environment MuleSoft to connect to other applications, connect to other data sources, connect to other analytics sources, and what's happening there is that the data is being modeled and personalized to whatever view, insight, or task has to happen within those processes. So even CRM environments where we think of as sort of traditional technologies that we're used to are getting a lift to both in terms of intelligence from the data but also your flexibility and how you execute governance and quality services within that environment. And that actually opens up the data foundations a lot more and avoids you from having to do a lot of moving, copying, centralizing data, and creating an over-weighted business application and an over, you know, both in terms of the data foundation but also in terms of the types of business services and status updates and processes that happen in the application itself. You're drawing those tasks back down to where they should be and where performance can be managed rather than trying to over customize your application environment. And that gives you a lot more flexibility later too for any sort of upgrades or migrations that you want to make because all of the logic is contained back down in a service layer instead. >> Great perspectives, Michele, you obviously know your stuff and it's been a pleasure having you on. My last question is when you look out there anything that really excites you or any specific research that you're working on that you want to share that you're super-pumped about. >> I think there's two things. One is it's truly incredible the amount of insight and growth that is coming through data profiling and observation, really understanding and contextualizing data anomalies so that you understand is data helping or hurting the business value. And, you know tying it very specifically to processes and metrics which is fantastic as well as models themselves like really understanding how data inputs and outputs are making a difference whether the model performs or not. And then I think the second thing is really the emergence of more active data, active insights, as what we talked about before your ability to package up services for governance and quality in particular that allow you to scale your data out towards the edge or where it's needed and doing so, you know not just so that you can run analytics but that you're also driving overall processes and value. So the research around the operationalization and activation of data is really exciting. And looking at the networks and service mesh to bring those things is kind of where I'm focusing right now because what's the point of having data in a database if it's not providing any value. >> Michele Goetz, Forrester Research, thanks so much for coming on theCube really awesome perspectives. You're in an exciting space. So appreciate your time. >> Absolutely, thank you. >> And thank you for watching Data Citizens '21 on theCube. My name is Dave Vellante. (upbeat music)

>>the >>globe. It's the Cube with digital coverage of AWS >>reinvent 2020 >>sponsored by Intel, AWS and our community partners. Everyone welcome back to the cubes. Virtual coverage of AWS reinvent 2020 Virtual I'm John for your host. Got a great segment here with two analyst day Volonte and Zia's Carvell who's head principles of zk research dot com. Guys. Great to see you A W s Kino. Thanks for >>coming on. Let's be back in the cube. >>Welcome back. Great to see you guys. Wanna get your thoughts? Um, it's mainly you because we talked with the enterprise a lot. You are leading analyst. You cover a broad range from networking all the way up to the C suite for enterprise buyers and and technology trends. Um, Andy Jassy laid down, in my opinion, what was directionally his next 20 mile stare. The next conquest for Amazon. And that is global. I t spend they locked in the infrastructures of service pass kicking ass. There. Check check. Hello, Enterprise. Different ballgame. What's your thoughts? >>Yeah, they have so much in different areas, obviously. You know, they have dominated cloud instances right there. Mawr compute storage memory. You know insists that anybody but you can see him, um, spreading their wings now, right? I think one of the more interesting announcements was actually what they're doing with Amazon connect. That's their contact center platform. And this is something that I think, Even last year, a lot of people weren't really even sure if they'd be in a long primary in the pocket. People about this market, they were asking, If you really think Amazon's in this, there's something they're experimenting. But we're here to stay. And I think one of the interesting things that they bring to market is, you know, almost unprecedented scale with their cloud platform as well as all the machine learning algorithms. And I think if if you believe that machine learning artificial intelligence is changing, I t. Forever and that's everything from the infrastructure to the network through the applications, then they have an inherent advantage because they have all those machine learning albums built into this stuff that they dio and so they can constantly look at these different markets and disruptive, disruptive, disrupt and take more and more sharing that and that's what they've done. E think that's you know, the context and announcements were great example that they're not doing the telephony things, and, you know, they're kind of bare table stakes. They do that pretty well, but they've just unloaded a whole bunch of ai based features that >>Dave, what's your take on this context center? Because it's not just call centers. I mean, there was a whole industry around call center, unified communications. That whole world. This is about the contact. It's about the person. This is not just a nuanced thing like telephony or, you know, PBX is in the old days. Remember those days? Things is not about the call. It's about the contact. This is what Jazzy saying. >>I think that way had Diana or on early. And I said, I like the fact that their AWS specifically is going after these solutions because several years ago it was just sort of. Here's a bunch of tools. Go figure it out. I think the contact center is I mean, everybody can relate Thio the pains of going through getting rerouted, having to restate all your credentials, not knowing who you are. And so between machine learning, Alexa, Natural language processing, better work flows. I mean there's this huge opportunity toe reinvent the whole call center contact center. So, uh, yeah, I think you called it John. It's a no brainer for a W s toe Really disrupt that >>business. Well, it also puts him in a position. You know, news is breaking on the day of and yet his keynote here at reinvent that, uh, you got Salesforce spying slack for 27 close toe, $28 billion. That's a 55% premium over when they announced it. And that's like a 30 x or 50 x on on revenue. Massive number to confess the message board software. I mean, so So. So. If Amazon can come in and get the context center model, which is not just voice, it's chat, it's machine learning. It's bots. And the innovation to create a step function kind of brings it back into the that integration of user network compute. You know, I just think that it feels very edgy in the sense of edge computing, because if I'm a person, I'm mobile. If I'm a person at work or at home, so there's a whole redefinition Zs, what's your take on this edge? Play from Amazon in context toe the enterprise software landscape. That seems to be, you know, focus on buying companies like Salesforce. >>Well, I think edges really the next big foray for computing. If one of the things and you ask we talked about this, you know, was that the compute, the unit of Compute, has gotten smaller and smaller, Right? We went from data centers to servers to virtual machines, the virtual machines and clouds. Now we're talking about containers and containers on edges, and this requires, um if you if you believe in the world of distributed computing where we're gonna have mawr containers running in MAWR, places on MAWR edges, right. The value proposition where companies is now they can move their data closer to the customer. They could move data closer to the user. And so, if I'm a retailer and I'm trying to understand what a customer is doing, I could do that in store. If I'm Tesla and I'm trying to understand what the drivers doing, I could do that in car, right? If I'm a cellular provider, I could do it by cellular edge. So the edge, I think, is where a lot of the innovation is going to be at Amazon has the luxury of this massive global network. You know, they just announced the number another a number of other local nodes, including Boston and a few other places. So they've got the footprint in place. And this this is what makes Amazon's are difficult to compete with, right? They built this massive network and this all these, no doubt for their e commerce business. And now they're leveraging that deliver I t services. You can't just go build this from the ground up the variety, right? You have to be able to monetize it another way. And they've been doing that with the commerce for a long time. And so it makes them. It makes it very, very difficult for them to capture Google could with Daniel forget about the item. Oh, yeah, so good. Microsoft. Possibly. But they I think that the more distributed compute becomes the more favors Amazon, >>I would add to that if I could, John, I mean, look good. Look at the prevailing way in which many of the infrastructure the old guard is Andy. Jesse calls them. Companies have pursued the edge they've essentially taking, taking x 86 boxes and, you know, maybe made him rugged and throwing them over the fence to the edge. And that really is not gonna play the edges. Now there's not one edge. I mean, there's a very highly specific use cases and factories and windmills. And maybe maybe it's small retail organizations, and whatever it is that those are gonna be really unique situations. And I think the idea of putting a programmable infrastructure at the edge is gonna win. I also think that the edge architecture is gonna be different. It's going to require much more efficient processing to do a I Influencing a lot of the data is gonna be, uh, stay at the edge. A lot of it's not gonna be persisted. Some of it's gonna come back to the cloud. But I think most of it is actually gonna gonna either not be persisted or stay at the edge and be affected in real time. When you think of autonomous vehicles so totally different programming model, >>well, I think that's the point of what I was saying earlier Zeus was talking about Is that it's It's the edges is just different. I mean, you got purpose built stuff. I mean, they were talking by the way they have snowball. So they have, ah, hard edge device. And they got out outpost now in multiple flavors and sizes. But they also were talking about computer vision and machine learning. We're going together for that. The panoramic appliance. I think it was where there's all these different cases to your point, Dave, where it's just different. At the edge, you have the zones for five G. I mean, if you go to a five g tower, that's essentially an edge. Just there's equipment up to this. Radios is transceivers and other back haul equipment. So when you look at the totality of what it is, the diversity, I think that's why this whole idea of Lambda and Containers is interesting. Toe Zia's. When you were saying about the compute sizes being small, because if you could put compute at the edge on small pieces to match the form factor that becomes interesting. I think that's what this Lambda container announcement I found interesting because I see that playing directly into that your reaction to >>that. It actually, um, makes it. If not done correctly, it could make I t much more complex because, um, containers air interesting because they're not like virtual machines. First live in perpetuity. Containers you They're very ephemeral, right? You spin them up to 30 seconds, you spin them up for a couple of minutes that you deprecate them. So at any given point in time, you could have thousands of containers, a handful of containers, millions of containers, Right? But it necessitates a common management. Uh huh. Underlay that could be used to visualize where these containers are, what's running on them. And that's what AWS provides. You know, all the stuff they're doing Lambda and Eks and things like that that lends itself to that. So a customer can then go and almost create a container architecture that spans all their cloud's edges, even on Prem. Now, uh, when Amazon has but still be able to manage it and simplify it, I think somebody's trying to do it themselves. They're gonna find that the complexity almost becomes untenable. Unless you have a Nike organization the size of Amazon companies don't. So we're >>gonna here, we're gonna hear from Deepak singing in a few sessions. He did the eks anywhere. That's essentially kubernetes service on the data center. But look at what they did with eks anywhere and then CCS, which has a common control plane to your point, that's compelling. And so, you know, if you're a developer or you're an enterprise, you might not have If you want to go with this. I t world. We talked about earlier zeros before you came on on our last segment. Most I t is not that built out in terms of capabilities. So learning new stuff is hard, so operating Amazon might be foreign to most I t shops. This is a challenge. Did you agree with that? Or or how do you see that? >>Um, well, a lot of Amazon used, obviously just the interviews and numbers of fucked that right. Um, but I think the concept of in a world where you have that common operating layer that spans it's no longer geographically limited to a data center or to a server. You know, it's it's now distributed across your entire multi cloud or distributed cloud environment. And so one of the important things right people remember is the world is becoming more dynamic and or distributed, and your I t strategy has to follow that. If you're doing things that are counted that you're not only standing still, you're actually going backwards. And so what Amazon is doing is they're allowing companies to be is dynamic distributors. They need to be to be able to maintain that that common operating layer that actually makes it management, because without it, you just you wind up in a situation. Like I said, that's incredible. A lot of people facing that today. And that's why that's why there's this big divergence, right? This five native cos they're going fast and legacy companies that can. >>Guys, I want to spend the next 10 minutes we have getting into more of the business side from this keynote because because I know your research on digital transmission first. I know you know the networking side up and down the stack and all that good stuff, but you've been doing a lot of research around the digital transformation with the cloud. Dave, you just put out a great great breaking and else think your 55th, um, episode on digital transformation with the cloud. It's very clear that Jackie is basically preaching, saying, Hey, Clay Christensen is former professor who passed away. He brought up this whole innovator's dilemma kind of theme and saying, Hey, if you don't get the reality that you're in, you better wake up and smell the coffee. It's a wake up call. That's what he's basically saying That's my take away. This is really this business management lesson. Leadership thinking is super important, and I know we've We've talked about people process, technology. Uh, let's Covad eyes this real quick. Bottom line. What is the playbook? Do you agree with jazz? His point of view here? Um, he's pretty being hardcore. He's like, literally saying adapter die in his own way. What, you guys thoughts on this? This is a true forcing function. This cove, In reality, >>I mean I mean, if you talk about the business transformation, digital transformation, business transformation, you know, what does that mean? I, like, said earlier that the last 10 years about I t transformation, I think the next 10 is gonna be about business transformation, organizational industry transformation, and I think what that means is the entire operational stack is gonna get digitized. So your sales you're marketing your your customer support your logistics. You know you're gonna have one interface to the customer as opposed toe, you know, fragmented stovepipe siloed. You know, data sets all over the place, and that is a major change. And I think that's ultimately what a W. S is trying to affect with its model and has obviously big challenges in doing so. But But that, to me, is what digital transformation is ultimately all about. And I think you're going to see it unfold very rapidly over the next several >>years. What's your reaction? What's your view on on the on Jackie? >>And he talked about his eight steps toe reinvention. Um and e think what digital transformation to me is the willingness to re invent disruptive own business even in the face that it might look horrible for your business, right? But understanding he is there something that I think is true. And a lot of, um, business leaders don't fully by this that if something is good for your customer, they're going to do it, and you can either make it happen, or you gonna watch it happen and then have the market taken away from me because there's a lot of cases you look at how slow you know, A lot of the banks, you know, operated until you know, the a lot of these, uh, cloud native, uh, money exchange systems came around the cape. Alan Ben more and things like that, right? Even retailers Amazon completely disrupted that model. You could say that Amazon killed, you know, Toys R us, but 20 rescue Toys R Us E. And I think there's got to be this hard willingness to look at your business model and be willing to disrupt yourself. And what Kobe did, John, I think, is a taught us a lesson that you have to be prepared for anything because nobody saw this coming. And sure you can. And a lot of companies thrived out of this, and a lot of one's gone away, but that the ability to be agile has never been more important. But you're only is Angela's. Ike lets you be, and that's what that's what. The W. Is going to sell us the ability to do anything you want with your business. But the staff, you have to have the business because they're willing to do that. >>You know, that's a great point. That's so smart. It's crime that's worth calling out. And we were talking before we came on live about our business with the Cube. There's no virtual, there's no floor anymore. So we had to go virtual if we weren't in the cloud. If we weren't doing R and D and tinkering with some software and having our studio, we'd be out of business. Dave. Everyone knows it. Now Get the Cube virtual. We have some software were position, and this kind of speaks directly to what Andy Jassy said. He said. Quote. If you're not in the process of figuring out as a company, how you're going to reinvent your customer experience in your product and reinvent who you are, you are starting to unwind. You may not realize it, but you are. What he's saying is you better wake up and smell the coffee and I want to get your guys reacted. You, particularly you around your experience and research. I've noticed that some customers that had cloud going on did well with co vid and said ones that didn't are still struggling not to catch up. So you're kind of intense. You got some companies that were that were on the wave, Maybe kind of figuring it out, that we're in good position and some that were flat footed and are desperate. Um, seems to be a trend. Do you agree with that? And what's your view on this idea of being ready? What does that even mean to be? Have readiness or >>take, you don't get the data points that Andy threw up there, right? That 50% of the companies that were the global fortune $500.2000 or are no longer here, Right? That Zatz Pretty shocking statistic. And that does come, uh, you know, from the willingness to disrupt your business. And if you got you're right. The companies that had a good, solid class raging in place, we're able to adapt their business very quickly. You could you look at retailers. Some had a very strong online presence. They had online customer service set up those companies didn't find other ones, were really forced to try and figure out how to let people in the store had a mimic. You know, the in store experience, you know, through from, uh, you know, support interface or whatever. Those are the ones that really struggling. So you're right. I think companies that were on the offensive plug to Dover companies that were fully in the cloud really accelerated their business and ones that didn't buy into it. I think they're struggling to survive in a lot of They're gone. >>Yeah, and all that. John, When Jesus was talking about his view of digital transformation, I was just writing down some of the examples to your point. The folks that were sort of had were cloud ready, covert ready, if you will. And those that weren't But think about think about automobiles. You know, there's testily even a manufacturer of automobiles or they software company. Personal health has completely changed over the last nine months with remote. You know, uh, telehealth automated manufacturing. You think about digital cash, e commerce and retail is completely, you know, accelerated. Obviously toe online. Think about kids in college and kids in high school and remote learning farming. You know, we've done a great job in terms of mono crops and actually creating a lot of food. But now I think the next 10 years is gonna be how do we get more nutritious food to people and so virtually every industry is ripe for disruption, and the cloud is the underpinning of that disruption. >>Alright, guys, got a few more minutes left. I want to get your thoughts quickly on the keynote. What it means for the customers that we're watching again. This is not a sales and marketing conference as they talk about. But if you're sitting in the audience, you guys, we're watching and we're virtual um Did it hit home with you? If you're a customer, what did he what? Give us Give the grades. Where do you Where do you hit a home run? Where he missed. Did he leave anything out? What's your take Zia's? We'll start with you. >>Um, I thought it was actually really good Keynote. I thought you did a good job of making the case for AWS. They talked about the open. They have more instances than anybody. So you could do almost any kind of compute in their cloud. I think one of the important lessons variety to is the importance. You can't just do everything. The software right? Hardware Still important silicon still important that, and to meet the needs of very special he needs from things like machine learning and AI. Amazon's actually spending their own silicon very much like Athens doing with their computers. And so if you are going to be a customer service focused company, you need to think of the I T. Stack and everything from the silicon, the hardware through the software, and build that integrated experience to Amazon's giving a tools to do that Now E. Do I would like to see Amazon be a little more, um, a supposed the cloud competitive friendly. The one thing I hear from customers all the time is they love the Amazon tools. They love the optimization capabilities, but you know, if they are adopting some kind of multi cloud strategy, the Amazon tools don't work in Azure and the capital don't work in Amazon. The same with Google, and it would be well within the best interests of those three companies. They find a way to get together and allow their common framework to work across clouds. Amazon's already got a lead that they could do that, and I don't think it's gonna be, but that that is something I think that's still missing from this world is they make it very difficult for customers to move the multi cloud. >>Well, some would say some people are saying, saying that the number one in the cloud I mean, got cloud wars Bob Evans over there saying Microsoft is dominating number one position over everybody else, multiple quarters in a row Now he's looking at revenue and granted. You got a lot of propping up there you got. You know, Windows server and sequel. You got a bunch of professional services, But clearly the I as in past side of the market, Microsoft is, like, way behind um So, yeah, they've got the numbers little legacy in their Microsoft should, and they got a little base. If I'm Amazon, I'm not. I'm worried about Microsoft more than anybody. I think you know, I looking at the Civil War between the Seattle forces. I mean, this is really Microsoft's gotta greatest all base, and they could flip that license deals and >>the cloud is good enough. I mean, it's myself doing very, very well with its classic Microsoft. You know >>they your point. Microsoft is the king of good enough, right? They put out features. They market heavily to the I t pro on. They put out licensing packages, so you're almost foolish to not at least fry their products. And then they do roll it out. So it's good enough and then you live with it for a while. But ultimately, whenever people use Microsoft, they do have an alternative under in there for a very special case. But e don't wanna >>the king of good enough. That's a great line. I love that. I'm gonna use that. But this Babel fish thing for Aurora that is a huge dagger. Potentially, it's an escape valve for customers. They wanna leave Microsoft. But clearly, if Microsoft you're gonna get penalized by running your license on Amazon. >>If our CEO our i t c t, I'd say, Okay, I definitely want to do business with with Amazon. That's what I heard today from Jassy, and I would want to hedge my bets either with Microsoft, especially if I'm a Microsoft shop or with Google's from analytics heavy unquestionably. I'd want to hedge my bets and have some kind of 70 30 80 20 mix. >>Look, if you're Andy Jassy and he's told me my interview, do it directly. I asked this question. He was very forthright. He doesn't hide from the fact that, uh, customers have multiple clouds, but they have a primary and secondary, but they're not gonna have, like, five or six major clouds. Yeah, it's hard to get these teams trained at to begin with. So there's a hedge. There's a supplier leverage. I get that. He's totally gets that. But if you're Amazon, you're gonna have your annual conference. You really don't wanna be in the business of talking about the other guys cloud, you say hybrid, right? It's on my show. You know, like you're competing. This is there's definitely competition between Microsoft and A W s. So you gotta respect that. But yeah, of course. There's multiple clouds called hybrid eks everywhere. Uh, container service. I mean, >>especially global, right? Different cloud providers of different strengths in different regions. You know, Microsoft, very strong in the Gulf. AWS isn't you know. So if you're a global company, um, you know, then you almost by default, have to go multi cloud multiple cloud vendors because of geographic differences. Obviously, China, with its own set of cloud providers. So, you know, smaller midsize businesses could get away with one, but As soon as you become global, you have to use more. >>Well, I'm a big fan of distributed computing. I loved the large scale concept of distribute computing. You got regions. Now you've got local zones. You got I O t edge. You got cloud going on Prem Edge. It's really an edge game at this point. Greater now distributed hyper Put hyper next to anything hyper cloud on your sounds better Piper >>Cube. And the opportunities the cloud providers and Amazon, you know, certainly is leading. This is the ability to take this complex, hyper distributed world and use their management tools toe create a normalized operating simplify What would be an overly complex world about it? >>Okay, we got a break. Just quick plug. There's a big salesforce event coming up on December 10th. Check it out on the Amazon site that that plug in you watching the cube stay tuned for more coverage after this break

>>on >>the globe. It's the Cube with digital coverage of AWS reinvent 2020 sponsored by Intel, AWS and our community partners. Okay. Welcome back, everyone. That's the cubes. Live coverage here in Palo Alto, California. I'm John for your host with David Lantana in Boston. Massachusetts. Uh, we got a great panel here. Analysts just gonna break it down. Keynote analysis. Day one, we got Ah, longtime Web services expert analyst Diane Hinchcliffe, principal researcher at N V. P. It constantly research, but he goes way back. Dan, I remember, uh, 2000 and one time frame you and I'm >>reading Last time you and I hang out with Michael Arrington's house back in the TechCrunch days >>back when, you know you were on this was Web services. I mean, that's always, uh, serves on the architectures. They called it back then. This was the beginning. This really was the catalyst of cloud. If you think about virtualization and Web services in that era, that really spawned where we are today so great to >>have you on as an Amazon got their start saying that everyone could get whatever they want to on a P. I now right, >>all right? Well, we've been riding this wave. Certainly it's cotton now more clear for the mainstream America. And I quoted you in my story, uh, on Andy Jassy when I had my one on one with them because I saw your talk with star Bit of the weekend and in the way you kicked it off was the Pandemic four was forced upon everybody, which is true, and that caught my attention was very notable because you talked to a lot of C E. O s. Does jazz sees pitch resonate with them? In your opinion, what's your take on on that on that posture? Because we heard, hey, you know, get busy building or you're dying, right? So get busy building. That's what >>I thought that was a good message. But I mean on and certainly I saw tweets and said, Hey, he's just he's just directly talking to the CEO. But if you ask me, he's still talking to the CTO, right? The technology officer who's got a feels all this technology and bend it into the shape that it will serve the business. You talk to a CEO who wants is trying to get on the cloud their biggest challenges. I know I need armies of people who know all these brand new services. You saw the development velocity of all the things that they announced and things they re emphasized there was There was a lot of things that were bringing back again because they have so many things that they're offering to the public. But the developer skills or not, they're the partner skills are not there. So you talked to CEO, says All right, I buy in and and I have had to transform overnight because of the pandemic, my customers have moved, my workers have moved on, and I have to like, you know, redirect all my I t Overnight and Cloud is the best way to do that. Where's my where's all the skills for the training programs, the department programs that allow me to get access to large amounts of talent? Those are the types of things that the CEO is concerned about is from an operational perspective. We didn't hear anything about, like a sales force type trailhead where we're going to democratize cloud skills to the very far end of your organization. >>Yeah, they're just kind of scratching the service. They didn't mention that, you know, far Gates away to get into server list. I mean, this is ultimately the challenge Dave and Deena like, don't get your thoughts on this because I was talking Teoh a big time CTO and a big time see so and that perspectives were interesting. And here's the Here's the Here's what I want you to react Thio the sea level Say everything is gonna be a service. Otherwise we're gonna be extinct. Okay, that's true. I buy that narrative, Okay, Make it as a service. That's why not use it. And then they go to the C t. And they say, implement, They go Well, it's not that easy. So automation becomes a big thing. And then so there's this debate. Automate, automate, automate. And then everything becomes a service. Is it the cart before the horse? So is automation. It's the cart before the horse, for everything is a service. What do you guys think about that? >>We'll see. I mean, CEO is to Diane's point, are highly risk averse and they like services. And those services generally are highly customized. And I think the tell in the bevy of announcements the buffet have announces that we heard today was in the marketplace what you guys thought of this or if you caught this. But there was a discussion about curated professional services that were tied to software, and there were classic PDM services. But they were very, you know, tight eso sort of off the shelf professional services, and that's kind of how Amazon plays it. And they were designed to be either self serve. It's a Diane's point. Skill sets aren't necessarily there or third parties, not directly from Amazon. So that's a gap that Amazon's got too close. I mean, you talk about all the time without post installations, you know, going on Prem. You know who's gonna support and service those things. You know, that's a that's a white space right now. I think >>e think we're still reading the tea leaves on the announcements. But there was one announcement that was, I thought really important. And that was this VM Ware cloud for a W s. It says, Let's take your VM ware skills, which you've honed and and cultivated and built a talent base inside your organization to run VMS and let's make that work for a W s. So I thought the VM Ware cloud for a W s announcement was key. It was a sleeper. It didn't spend a lot of time on it. But the CEO ears are gonna perk up and say, Wait, I can use native born skills. I already have to go out to the cloud So I didn't think that they did have 11 announcement I thought was compelling in that >>in the spending data shows of VM Ware Cloud on AWS is really gaining momentum by the way, As you see in that open shift So you see in that hybrid zone really picking up. And we heard that from AWS today. John, you and I talked about it at the open I produces in >>Yeah, I want to double down on that point you made because I want to get your thoughts on this a Z analyst because you know, the VM ware is also tell. Sign to what I'm seeing as operating and developing Dev ops as they be called back in the day. But you gotta operate, i t. And if Jassy wants to go after this next tier of spend on premise and edge. He's gotta win the global i t posture game. He's gotta win hybrid. He's got to get there faster to your point. You gotta operate. It's not just develop on it. So you have a development environment. You have operational environment. I think the VM Ware thing that's interesting, cause it's a nice clean hand in glove. VM Ware's got operators who operate I t. And they're using Amazon to develop, but they work together. There's no real conflict like everyone predicted. So is that the tell sign is the operational side. The challenge? The Dev, How does Amazon get that global I t formula down? Is it the VM Ware partnership? >>I think part of it is there, finally learning to say that the leverage that the vast pool of operational data they have on their literally watching millions of organizations run all the different services they should know a lot and I say made that point today, he said, Well, people ask us all the time. You must have all these insights about when things were going right or wrong. Can you just tell us? And so I think the announcement around the Dev ops guru was very significant, also saying you don't necessarily have to again teach all your staff every in and out about how to monitor every aspect of all these new services that are much more powerful for your business. But you don't yet know how to manage, especially at scale. So the Dev Ops guru is gonna basically give a dashboard that says, based on everything that we've known in the past, we could give you insights, operational insights you can act on right away. And so I think that is again a tool that could be put in place on the operational side. Right. So b m where for cloud gives you migration ability, uh, of existing skills and workloads. And then the Dev Ops crew, if it turns out to be everything they say it is, could be a really panacea for unlocking the maturity curve that these operators have to climb >>on. AWS is in the business now of solving a lot of the problems that it sort of helped create. So you look at, for instance, you look at the sage maker Data Wrangler trying to simplify data workloads. The data pipeline in the cloud is very very complex and so they could get paid for helping simplify that. So that's a wonderful, virtuous circle. We've seen it before. >>Yeah. I mean, you have a lot of real time contact lens you've got, um, quick site. I mean, they have to kind of match the features. And And I want to get your guys thoughts on on hybrid because I think, you know, I'm still stuck on this, Okay? They won the as path and their innovations Great. The custom chips I buy that machine learning all awesome. So from the classic cloud I as infrastructure and platform as a service business looking good. Now, if you're thinking global, I t I just don't just not connecting the dots there. See Outpost? What's riel today for Amazon? Can you guys share E? I mean, if you were watching this keynote your head explode because you've got so many announcements. What's actually going on if you're looking at this is the CEO. >>So the challenge you have is the CEO. Is that your you have 10, 20 or 30 or more years of legacy hardware, including mainframes, right. Like so big insurance companies don't use mainframe because their claims systems have been developed in their very risk averse about changing them. Do you have to make all of this work together? Like, you know, we see IBM and Redhead are actually, you know, chasing that mainframe. Which angle, which is gonna die out where Amazon, I think is smart is saying, Look, we understand that container is gonna be the model container orchestration is gonna be how I t goes forward. The CEO is now buy into that. Last year, I was still saying, Are we gonna be able to understand? Understand? Kubernetes is the regular average i t person, which are not, you know, Google or Facebook level engineers Are there gonna be able to do do containers? And so we see the open sourcing of of the AWS is, uh, kubernetes, uh, server on. We see plenty of container options. That's how organizations could build cloud native internally. And when they're ready to go outside because we're gonna move, they're gonna move many times slower than a cloud native company to go outside. Everything is ready there. Um, I like what I'm seeing without posts. I like what I'm seeing with the hybrid options. The VM ware for cloud. They're building a pathway that says you can do real cloud. And I think the big announcement that was that. That s a really, uh, spend time on which is that PCs for everywhere. Um, a saying you're gonna be able to put Amazon services are compute services anywhere. You need it, e think that's a smart message. And that allows people to say I could eventually get toe one model to get my arms around this over time >>day. What does that mean for the numbers? I know you do a lot of research on spend customer data. Um, CEO is clearly no. This is gonna be the world's never go back to the same way it was. They certainly will accelerate cloud toe. What level depends upon where they are in their truth, as Jassy says. But >>what does >>the numbers look at? Because you're looking at the data you got Microsoft, You got Amazon. What's the customer spend look like where they're gonna be spending? >>Well, so a couple things one is that when you strip out the the SAS portion of both Google and Azure, you know, as we know, I asked him pass A W S is the leader, but there's no question that Microsoft is catching up. Says that we were talking about earlier. Uh, it's the law of large numbers Just to give you a sense Amazon this year we'll add. Q four is not done yet, but they'll add 10 billion over last year. And Jesse sort of alluded to that. They do that in 12 months. You know, uh, azure will add close to nine billion this year of incremental revenue. Google much, much smaller. And so So that's, you know, just seeing, uh, as you really catch up there for sure, you know, closing that gap. But still Amazon's got the lead. The other thing I would say is die on you and I were talking about this Is that you know Google is starting. Thio do a little bit better. People love their analytics. They love the built in machine learning things like like big query. And you know, even though they're much, much smaller there, another hedge people don't necessarily want to goto Microsoft unless they're Microsoft Shop. Google gives them that alternative, and that's been a bit of a tailwind for Google. Although I would say again, looking at the numbers. If I look back at where Azure and AWS were at this point where Google is with a few billion dollars in cloud the growth rates, I'd like to see Google growing a little faster. Maybe there's a covert factor there. >>Diane. I want to get your thoughts on this transition. Microsoft Oracle competition Um, Jesse knows he's got a deal with the elite Salesforce's out there. Oracle, Microsoft. Microsoft used to be the innovator. They had the they had the phrase embracing extend back in the day. Now Amazon's embracing and extending, but they gotta go through Oracle and Microsoft if they wanna win the enterprise on premise business and everybody else. Um, eso welcome to the party like Amazon. You What's your take on them versus Microsoft? Calling them out on sequel server licensing practices almost thrown him under the bus big time. >>Well, I think that's you know, we saw the evidence today that they're actually taking aim at Microsoft now. So Babel Fish, which allows you to run Microsoft sequel server workloads directly on Aurora. Uh, that that is what I call the escape pod that gives organizations an easy way That isn't Will parliament to redesign and re architect their applications to say, Just come over to AWS, right? We'll give you a better deal. But I think you've got to see Amazon have, um, or comprehensive sales plan to go into the C. E. O s. Go after the big deals and say, You know, we want to say the whole cloud suite, we have a stack that's unbeatable. You see our velocities, you know, best in class. Arguably against Microsoft is the big challenger, but we'll beat you on on a total cost of ownership. You know, your final bill. At the end of the day, we could we commit to being less than our competitors. Things like that will get the attention. But, you know, uh, Amazon is not known for cutting customized deals. Actually, even frankly, I'm hearing from very CEO is a very large, like Fortune 20 companies. They have very little wiggle room with Microsoft's anybody who's willing to go to the big enterprise and create custom deals. So if you build a sales team that could do that, you have a real shot and saying getting into the CEO's office and saying, You know, we want to move all the I t over and I'm seeing Microsoft getting winds like that. I'm not yet seeing Amazon and they're just gonna have to build a specialized sales team that go up against those guys and migration tools like we saw with Babel fish that says, If you want to come, we can get you over here pretty quick. >>I want to chime in on Oracle to John. I do. I think this is a blind spot somewhat for AWS, Oracle and mainframes. Jesse talks that talks like, Oh yeah, these people, they wanna get off there. And there's no question there are a number of folks that are unhappy, certainly with Oracle's licensing practices. But I talked to a lot of Oracle customers that are running the shops on Oracle database, and it's really good technology. It is world class for mission critical transaction workloads. Transaction workloads tend to be much, much smaller data set sizes, and so and Oracle's got, you know, decades built up, and so their their customers air locked in and and they're actually reasonably happy with the service levels they're getting out of Oracle. So yes, licensing is one thing, but there's more to the story and again, CEO or risk averse. To Diane's point, you're not just gonna chuck away your claim system. It's just a lot of custom code. And it's just the business case isn't there to move? >>Well, I mean, I would argue that Well, first of all, I see where you're coming from. But I would also argue that one of the things that Jesse laid out today that I thought was kind of a nuanced point was during the vertical section. I think it was under the manufacturing. He really laid out the case that I saw for startups and or innovation formula, that horizontal integration around the data. But then being vertically focused with the modern app with same machine learning. So what he was saying, and I don't think he did a good job doing it was you could disrupt horizontally in any industry. That's a that's a disruption formula, but you still could have that scale. That's cloud horizontal scalability, cloud. But the data gives you the ability to do both. I think bringing data together across multiple silos is critical, but having that machine learning in the vertical is the way you could different so horizontally. Scalable vertical specialization for the modern app, I think is a killer formula. And I think >>I think that's a I think it's a really strong point, John, and you're seeing that you're seeing in industries like, for instance, Amazon getting into grocery. And that's a data play. But I do like Thio following your point. The Contact Center solutions. I like the solutions play there and some of the stuff they're doing at the edge with i o T. The equipment optimization, the predictive maintenance, those air specialized solutions. I really like the solutions Focus, which several years ago, Amazon really didn't talk solution. So that's a positive sign, >>Diane, what do you think? The context And I think that was just such low hanging fruit for Amazon. Why not do it? You got the cloud scale. You got the Alexa knowledge, you know, got machine learning >>zone, that natural language processing maturity to allow them to actually monitor that. You know that that contact lens real time allows them a lot of supervisors to intervene them conversations before they go completely south, right? So allowing people to get inside decision windows they couldn't before. I think that's a really important capability. And that's a challenge with analytics in general. Is that generates form or insights than people know how to deal with? And it solutions like contact lens Real time? This is Let's make these insights actionable before it's broken. Let's give you the data to go and fix it before it even finishes breaking. And this is the whole predictive model is very powerful. >>Alright, guys, we got four minutes left. I wanted Segway and finish up with what was said in the keynote. That was a tell sign that gives us some direction of where the dots will connect in the future. There's a lot of stuff that was talked about that was, you know, follow on. That was meat on the bone from previous announcements. Where did Jassy layout? What? I would call the directional shift. Did you see anything particular that you said? Okay, that is solid. I mean, the zones was one I could see. What clearly is an edge piece. Where did you guys see? Um, some really good directional signaling from Jassy in terms of where they really go. Deal with start >>e I felt like Jassy basically said, Hey, we invented cloud. Even use these words we invented cloud and we're gonna define what hybrid looks like We're gonna bring our cloud model to the edge. And the data center just happens to be another edge point. And hey, I thought he laid down the gauntlet. E think it's a very powerful message. >>What do you think Jesse has been saying? That he laid out here, That's >>you laid out a very clear path to the edge that the Amazons marching to the edge. That's the next big frontier in the cloud. It isn't well defined. And that just like they defined cloud in the early days that they don't get out there and be the definitive leader in that space. Then they're gonna be the follower. I think so. We saw announcement after announcement around that you know, from the zones Thio the different options for outpost um, the five g announcement wavelength. All of those things says we're gonna go out to the very tippy edge is what I heard right out to your mobile devices. Right after the most obscure field applications imaginable. We're gonna have an appliance So we're gonna have a service that lets you put Amazon everywhere. And so I think the overarching message was This is a W s everywhere it z gonna go after 100% of I t. Eventually on DSO you can move to that. You know, this one stop shop? Um and you know, we saw him or more discussions about multi cloud, but it was interesting how they stand away from that. And this is what I think One area that they're going to continue to avoid. So it was interesting, >>John, I think I think the edges one by developers. And that's good news for Amazon. And good news for Microsoft. >>We'll see the facilities is gonna be good for me. I think guys, the big take away You guys nailed two of them there, but I think the other one was I think he's trying to speak to this new generation in a very professorial way. Talk about Clay Christensen was a professor at his business school at Harvard. We all know the book. Um, but there was this There was this a posture of speaking to the younger generation like hey, the old guy, the old that was running the mainframe. Wherever the old guys there, you could take over and run this. So it's kind of like more of a leadership preach of preaching like, Hey, it's okay to be cool and innovative, right now is the time to get in cloud. And the people who are blocking you are either holding on to what they built or too afraid to shift. Eso I think a Z we've seen through waves of innovation. You always have those people you know who are gonna stop that innovation. So I was very interesting. You mentioned that would service to the next generation. Um, compute. So he had that kind of posture. Interesting point. Yeah, just very, very preachy. >>E think he's talking to a group of people who also went through the through 2020 and they might be very risk averse and not bold anymore. And so, you know, I think that may have helped address that as well. >>All right, gentlemen, great stuff. Final word in the nutshell. Kena, What do you think about it in general? Will take away. >>Yeah, I I think we saw the continued product development intensity that Amazon is going to use to try and thrash the competition? Uh, the big vision. Um, you know, the real focus on developers first? Um and I think I t and C e O's second, I think before you could say they didn't really think about them too much at all. But now it's a close second. You know, I really liked what I saw, and I think it's It's the right move. I'd like to Seymour on on hybrid cloud migration than that, even when we saw them. >>All right, leave it there. Don. Thanks for coming on from this guest analyst segment. Appreciate you jumping in Cuba. Live. Thank you. >>Thanks. Alright. >>With acute virtual. I'm your host John per day Volonte here covering A W s live covering the keynote in real time State more for more coverage after the break

>> From around the globe, it's theCUBE, with digital coverage of Exascale Day. Made possible by Hewlett Packard Enterprise. >> Hey, welcome back everybody Jeff Frick here with theCUBE. We are celebrating Exascale Day. 10, 18, I think it's the second year of celebrating Exascale Day, and we're really excited to have our next guest and talk about kind of what this type of compute scale enables, and really look a little bit further down the road at some big issues, big problems and big opportunities that this is going to open up. And I'm really excited to get in this conversation with our next guest. He is Bryan Pijanowski the Professor of Landscape and Soundscape Ecology at Purdue University. Bryan, great to meet you. >> Great to be here. >> So, in getting ready for this conversation, I just watched your TED Talk, and I just loved one of the quotes. I actually got one of quote from it that's basically saying you are exploring the world through sound. I just would love to get a little deeper perspective on that, because that's such a unique way to think about things and you really dig into it and explain why this is such an important way to enjoy the world, to absorb the world and think about the world. >> Yeah, that's right Jeff. So the way I see it, sound is kind of like a universal variable. It exists all around us. And you can't even find a place on earth where there's no sound, where it's completely silent. Sound is a signal of something that's happening. And we can use that information in ways to allow us to understand the earth. Just thinking about all the different kinds of sounds that exist around us on a daily basis. I hear the birds, I hear the insects, but there's just a lot more than that. It's mammals and some cases, a lot of reptiles. And then when you begin thinking outside the biological system, you begin to hear rain, wind, thunder. And then there's the sounds that we make, sounds of traffic, the sounds of church bells. All of this is information, some of it's symbolic, some of it's telling me something about change. As an ecologist that's what I'm interested in, how is the earth changing? >> That's great and then you guys set up at Purdue, the Purdue Center for Global Soundscapes. Tell us a little bit about the mission and some of the work that you guys do. >> Well, our mission is really to use sound as a lens to study the earth, but to capture it in ways that are meaningful and to bring that back to the public to tell them a story about how the earth kind of exists. There's an incredible awe of nature that we all experience when we go out and listen into to the wild spaces of the earth. I've gone to the Eastern Steppes of Mongolian, I've climbed towers in the Paleotropics of Borneo and listened at night. And ask the question, how are these sounds different? And what is a grassland really supposed to sound like, without humans around? So we use that information and bring it back and analyze it as a means to understand how the earth is changing and really what the biological community is all about, and how things like climate change are altering our spaces, our wild spaces. I'm also interested in the role that people play and producing sound and also using sound. So getting back to Mongolia, we have a new NSF funded project where we're going to be studying herders and the ways in which they use sonic practices. They use a lot of sounds as information sources about how the environment is changing, but also how they relate back to place and to heritage a special sounds that resonate, the sounds of a river, for example, are the resonance patterns that they tune their throat to that pay homage to their parents that were born at the side of that river. There's these special connections that people have with place through sound. And so that's another thing that we're trying to do. In really simple terms, I want to go out and, what I call it sounds rather simple, record the earth-- >> Right. >> What does that mean? I want to go to every major biome and conduct a research study there. I want to know what does a grassland sound like? What is a coral reef sound like? A kelp forest and the oceans, a desert, and then capture that as baseline and use that information-- >> Yeah. >> For scientific purposes >> Now, there's so much to unpack there Bryan. First off is just kind of the foundational role that sound plays in our lives that you've outlined in great detail and you talked about it's the first sense that's really activated as we get consciousness, even before we're born right? We hear the sounds of our mother's heartbeat and her voice. And even the last sense that goes at the end a lot of times, in this really intimate relationship, as you just said, that the sounds represent in terms of our history. We don't have to look any further than a favorite song that can instantly transport you, almost like a time machine to a particular place in time. Very, very cool. Now, it's really interesting that what you're doing now is taking advantage of new technology and just kind of a new angle to capture sound in a way that we haven't done before. I think you said you have sound listening devices oftentimes in a single location for a year. You're not only capturing sound, the right sound is changes in air pressure, so that you're getting changes in air pressure, you're getting vibration, which is kind of a whole different level of data. And then to be able to collect that for a whole year and then start to try to figure out a baseline which is pretty simple to understand, but you're talking about this chorus. I love your phrase, a chorus, because that sound is made up of a bunch of individual inputs. And now trying to kind of go under the covers to figure out what is that baseline actually composed of. And you talk about a bunch of really interesting particular animals and species that combine to create this chorus that now you know is a baseline. How did you use to do that before? I think it's funny one of your research papers, you reach out to the great bird followers and bird listeners, 'cause as you said, that's the easiest way or the most prolific way for people to identify birds. So please help us in a crowdsource way try to identify all the pieces that make this beautiful chorus, that is the soundscape for a particular area. >> Right, yeah, that's right. It really does take a team of scientists and engineers and even folks in the social sciences and the humanities to really begin to put all of these pieces together. Experts in many fields are extremely valuable. They've got great ears because that's the tools that they use to go out and identify birds or insects or amphibians. What we don't have are generalists that go out and can tell you what everything sounds like. And I'll tell you that will probably never ever happen. That's just way too much, we have millions of species that exist on this planet. And we just don't have a specific catalog of what everything sounds like, it's just not possible or doable. So I need to go out and discover and bring those discoveries back that help us to understand nature and understand how the earth is changing. I can't wait for us to eventually develop that catalog. So we're trying to develop techniques and tools and approaches that allow us to develop this electronic catalog. Like you're saying this chorus, and it doesn't necessarily have to be a species specific chorus, it can be a chorus of all these different kind of sounds that we think relate back to this kind of animal or that kind of animal based upon the animals instrument-- >> Right, great. >> And this is the sound. >> Now again, you know, keep it to the exascale theme, right? You're collecting a lot of data and you mentioned in one of the pieces I've dug up, that your longest study in a single location is 17 years. You've got over 4 million recordings. And I think you said over 230 years if you wanted to listen to them all back to back. I mean, this is a huge, a big data problem in terms of the massive amount of data that you have and need to run through an analysis. >> Yeah, that's right. We're collecting 48,000 data points per second. So that's 48 kilohertz. And then so you multiply everything and then you have a sense of how many data points you actually have to put them all together. When you're listening to a sound file over 10 minutes, you have hundreds of sounds that exist in them. Oftentimes you just don't know what they are, but you can more or less put some kind of measure on all of them and then begin to summarize them over space and time and try to understand it from a perspective of really science. >> Right, right. And then I just love to get your take as you progress down this kind of identification road, we're all very familiar with copyright infringement hits on YouTube or social media or whatever, when it picks up on some sound and the technology is actually really sophisticated to pick up some of those sound signatures. But to your point, it's a lot easier to compare against the known and to search for that known. Then when you've got this kind of undefined chorus that said we do know that there can be great analysis done that we've seen AI and ML applied, especially in the surveillance side on the video-- >> Right. >> With video that it can actually do a lot of computation and a lot of extracting signal from the noise, if you will. As you look down the road on the compute side for the algorithms that you guys are trying to build with the human input of people that know what you're listening to, what kind of opportunities do you see and where are we on that journey where you can get more leverage out of some of these technology tools? >> Well, I think what we're doing right now is developing the methodological needs, kind of describe what it is we need to move into that new space, which is going to require these computational, that computational infrastructure. So, for example, we have a study right now where we're trying to identify certain kinds of mosquitoes (chuckling) a vector-borne mosquitoes, and our estimates is that we need about maybe 900 to 1200 specific recordings per species to be able to put it into something like a convolutional neural network to be able to extract out the information, and look at the patterns and data, to be able to say indeed this is the species that we're interested in. So what we're going to need and in the future here is really a lot of information that allow us to kind of train these neural networks and help us identify what's in the sound files. As you can imagine the computational infrastructure needed to do that for data storage and CPU, GPU is going to be truly amazing. >> Right, right. So I want to get your take on another topic. And again the basis of your research is really all bound around the biodiversity crisis right? That's from the kind of-- >> Yeah. >> The thing that's started it and now you're using sound as a way to measure baseline and talk about loss of species, reduced abundancies and rampant expansion of invasive species as part of your report. But I'd love to get your take on cities. And how do you think cities fit the future? Clearly, it's an efficient way to get a lot of people together. There's a huge migration of people-- >> Right. >> To cities, but one of your themes in your Ted Talk is reconnecting with nature-- >> Yeah. >> Because we're in cities, but there's this paradox right? Because you don't want people living in nature can be a little bit disruptive. So is it better to kind of get them all in a tip of a peninsula in San Francisco or-- >> Yeah. >> But then do they lose that connection that's so important. >> Yeah. >> I just love to get your take on cities and the impacts that they're have on your core research. >> Yeah, I mean, it truly is a paradox as you just described it. We're living in a concrete jungle surrounded by not a lot of nature, really, honestly, occasional bird species that tend to be fairly limited, selected for limited environments. So many people just don't get out into the wild. But visiting national parks certainly is one of those kinds of experience that people oftentimes have. But I'll just say that it's getting out there and truly listening and feeling this emotional feeling, psychological feeling that wraps around you, it's a solitude. It's just you and nature and there's just no one around. >> Right. >> And that's when it really truly sinks in, that you're a part of this place, this marvelous place called earth. And so there are very few people that have had that experience. And so as I've gone to some of these places, I say to myself I need to bring this back. I need to tell the story, tell the story of the awe of nature, because it truly is an amazing place. Even if you just close your eyes and listen. >> Right, right. >> And it, the dawn chorus in the morning in every place tells me so much about that place. It tells me about all the animals that exist there. The nighttime tells me so much too. As a scientist that's spent most of his career kind of going out and working during the day, there's so much happening at night. Matter of fact-- >> Right. >> There's more sounds at night than there were during the day. So there is a need for us to experience nature and we don't do that. And we're not aware of these crises that are happening all over the planet. I do go to places and I listen, and I can tell you I'm listening for things that I think should be there. You can listen and you can hear the gaps, the gaps and that in that chorus, and you think what should be there-- >> Right. >> And then why isn't it there? And that's where I really want to be able to dig deep into my sound files and start to explore that more fully. >> It's great, it's great, I mean, I just love the whole concept of, and you identified it in the moment you're in the tent, the thunderstorm came by, it's really just kind of changing your lens. It's really twisting your lens, changing your focus, because that sound is there, right? It's been there all along, it's just, do you tune it in or do you tune it out? Do you pay attention? Do not pay attention is an active process or a passive process and like-- >> Right. >> I love that perspective. And I want to shift gears a little bit, 'cause another big environmental thing, and you mentioned it quite frequently is feeding the world's growing population and feeding it-- >> Yeah. >> In an efficient way. And anytime you see kind of factory farming applied to a lot of things you wonder is it sustainable, and then all the issues that come from kind of single output production whether that's pigs or coffee or whatever and the susceptibility to disease and this and that. So I wonder if you could share your thoughts on, based on your research, what needs to change to successfully and without too much destruction feed this ever increasing population? >> Yeah, I mean, that's one of the grand challenges. I mean, society is facing so many at the moment. In the next 20 years or so, 30 years, we're going to add another 2 billion people to the planet, and how do we feed all of them? How do we feed them well and equitably across the globe? I don't know how to do that. But I'll tell you that our crops and the ecosystem that supports the food production needs the animals and the trees and the microbes for the ecosystem to function. We have many of our crops that are pollinated by birds and insects and other animals, seeds need to be dispersed. And so we need the rest of life to exist and thrive for us to thrive too. It's not an either, it's not them or us, it has to be all of us together on this planet working together. We have to find solutions. And again, it's me going out to some of these places and bringing it back and saying, you have to listen, you have to listen to these places-- >> Right. >> They're truly a marvelous. >> So I know most of your listening devices are in remote areas and not necessarily in urban areas, but I'm curious, do you have any in urban areas? And if so, how has that signature changed since COVID? I just got to ask, (Bryan chuckling) because we went to this-- >> Yeah. >> Light switch moment in the middle of March, human activity slowed down-- >> Yeah. >> In a way that no one could have forecast ever on a single event, globally which is just fascinating. And you think of the amount of airplanes that were not flying and trains that we're not moving and people not moving. Did you have any any data or have you been able to collect data or see data as the impact of that? Not only directly in wherever the sensors are, but a kind of a second order impact because of the lack of pollution and the other kind of human activity that just went down. I mean, certainly a lot of memes (Bryan chuckling) on social media of all the animals-- >> Yeah. >> Come back into the city. But I'm just curious if you have any data in the observation? >> Yeah, we're part of actually a global study, there's couple of hundred of us that are contributing our data to what we call the Silent Cities project. It's being coordinated out of Europe right now. So we placed our sensors out in different areas, actually around West Lafayette area here in Indiana, near road crossings and that sort of thing to be able to kind of capture that information. We have had in this area here now, the 17 year study. So we do have studies that get into areas that tend to be fairly urban. So we do have a lot of information. I tell you, I don't need my sensors to tell me something that I already know and you suspect is true. Our cities were quiet, much quieter during the COVID situation. And it's continued to kind of get a little bit louder, as we've kind of released some of the policies that put us into our homes. And so yes, there is a major change. Now there have been a couple of studies that just come out that are pretty interesting. One, which was in San Francisco looking at the white-crowned sparrow. And they looked at historical data that went back something like 20 years. And they found that the birds in the cities were singing a much softer, 30% softer. >> Really? >> And they, yeah, and they would lower their frequencies. So the way sound works is that if you lower your frequencies that sound can travel farther. And so the males can now hear themselves twice as far just due to the fact that our cities are quieter. So it does have an impact on animals, truly it does. There was some studies back in 2001, during  the September, the 9/11 crisis as well, where people are going out and kind of looking at data, acoustic data, and discovering that things were much quieter. I'd be very interested to look at some of the data we have in our oceans, to what extent are oceans quieter. Our oceans sadly are the loudest part of this planet. It's really noisy, sound travels, five times farther. Generally the noise is lower frequencies, and we have lots of ships that are all over the planet and in our oceans. So I'd really be interested in those kinds of studies as well, to what extent is it impacting and helping our friends in the oceans. >> Right, right, well, I was just going to ask you that question because I think a lot of people clearly understand sound in the air that surrounds us, but you talk a lot about sound in ocean, and sound as an indicator of ocean health, and again, this concept of a chorus. And I think everybody's probably familiar with the sounds of the humpback whale right? He got very popular and we've all seen and heard that. But you're doing a lot of research, as you said, in oceans and in water. And I wonder if you can, again, kind of provide a little bit more color around that, because I don't think you people, maybe we're just not that tuned into it, think of the ocean or water as a rich sound environment especially to the degree as you're talking about where you can actually start to really understand what's going on. >> Yeah, I mean, some of us think that sound in the oceans is probably more important to animals than on land, on the terrestrial side. Sound helps animals to navigate through complex waterways and find food resources. You can only use site so far underwater especially when it gets to be kind of dark, once you get down to certain levels. So there many of us think that sound is probably going to be an important component to measuring the status of health in our oceans. >> It's great. Well, Bryan, I really enjoyed this conversation. I've really enjoyed your Ted Talk, and now I've got a bunch of research papers I want to dig into a little bit more as well. >> Okay.(chuckling) >> It's a fascinating topic, but I think the most important thing that you talked about extensively in your Ted Talk is really just taking a minute to take a step back from the individual perspective, appreciate what's around us, hear, that information and I think there's a real direct correlation to the power of exascale, to the power of hearing this data, processing this data, and putting intelligence on that data, understanding that data in a good way, in a positive way, in a delightful way, spiritual way, even that we couldn't do before, or we just weren't paying attention like with what you know is on your phone please-- >> Yeah, really. >> It's all around you. It's been there a whole time. >> Yeah. (both chuckling) >> Yeah, Jeff, I really encourage your viewers to count it, just go out and listen. As we say, go out and listen and join the mission. >> I love it, and you can get started by going to the Center for Global Soundscapes and you have a beautiful landscape. I had it going earlier this morning while I was digging through some of the research of Bryan. (Bryan chuckling) Thank you very much (Bryan murmurs) and really enjoyed the conversation best to you-- >> Okay. >> And your team and your continued success. >> Alright, thank you. >> Alright, thank you. All right, he's Bryan-- >> Goodbye. >> I'm Jeff, you're watching theCUBE. (Bryan chuckling) for continuing coverage of Exascale Day. Thanks for watching. We'll see you next time. (calm ambient music)

>> Announcer: From "theCUBE" studios in Palo Alto and Boston, this is an episode in the Remote Works Citrix Virtual Series. >> Hi, I'm Stu Miniman. And welcome to this special conversation talking about back to work. Of course, the COVID global pandemic impacting everyone working from home and what's happening as these productivity changes. So, really happy to welcome to the program two of our Cube alumni. First of all, we have PJ Hough. He is the Executive Vice President and Chief Product Officer of the Citrix. And also joining us, Maribel Lopez, she is the Founder and Principal Analyst at Lopez Research. PJ and Maribel, thanks so much for joining us. >> Thank you Stu. >> Thanks Stu. >> Alright, so let's talk. You know, we've been in this pandemic now for, you know, a good chunk of time, many months. Some of us are back in the office. Some, we are talking a lot about, Maribel I think you talked about hybrid work in some of the readings and writings that you've done. So, I'd love to hear, you know, you're thinking right now, what you're hearing from your customers, and how should we be thinking about that workforce both today and really for kind of the next six to 12 months? PJ, maybe we'll start with you and how Citrix is helping and Maribel would love you to chime in with what you're hearing from customers and in your research. >> Yeah, I think it's a very interesting time for our customers right now. First of all, I have to say, generally impressed I am with the way that businesses have managed to transition from, you know, working in the office to working in this almost 100% remote environment for many of our customers. And that they've made that transition, you know, many of them using our technology. But using very much every technique available to them and maybe even bending some of the previous rules that they had about what their strategies would be with regard to particular technologies or solutions. But it's been really very impressive to see everyone move from that, you know, state where they had to leave their offices, many at relatively short notice, all the way to, you know, where we are today. And of course, as you mentioned Stu, we now have a subset of those customers who are actually either beginning to move back or preparing to move back. But, I still think that's a journey that's ahead of most of the customers that I deal with on a daily basis. >> So for me, you know, I feel that there are really several things happening, right? We have new profiles that we're looking at. So in the back to office, some people will go back to the office and be full time there. Many people will be remote work. In fact, you might even hire some people, and never physically have them come into the office to meet with anybody. It might all be done by a video as an example. And then there'll be nomadic workers, where some people will come in more for this concept of collaboration, and then they'll go back and work from home. So, those three profiles, I think we talked about them in the past, but really, there were very few people that thought there was going to be a large percentage of remote work. And nomadic work was more something that was thought I'm traveling. It wasn't thought that I might work at home and really use the office as more a collaborative engagement space. >> Yeah, it's been fascinating to watch many of the large technology enterprise companies that I work with, have been giving their employees the option. It is, you know, okay, hey, when things open up, do you want to stay fully remote? You know, it's going to be, you know, the ripple effect on real estate. Maribel as you were saying, you know, how we think about where they live and work compared to what they had before. PJ, I want to come to you. The discussion we've had for many years in the industry is, you know, customer experience is so important, but of course, it's the employee experience that is going to be a big piece of how customer experience and we create that delight. Of course, as you mentioned, Citrix has been helping customers, you know, really change how they think about where employees work, how employees work. So, you know, is this just accelerating what we've seen before? What does that, you know, employee experience look like in today's environment? >> Well, I think this is a really important area for, I think, organizations to focus on at a time like this. Obviously, there's been a lot of attention in the last decade on the customer experience, and I would say the digital customer experience. And maybe even a little bit ahead of some of the investments that have been made in the employee experience that has needed to keep up with that. And so, you know, we've been doing some research, some of it was done earlier in the year in fact, that shows a very high correlation between the performance of companies and the response from employees who claim that they have very good to excellent digital tools to help them do their job. And I think one of the areas where companies have either, I will say succeeded or maybe felt a little bit of stress in the system, in this movement of employees from the office to the home, is whether or not the experience they were able to deliver was consistent with what the employees had previously been leveraging when they were in the office. We've all built up a set of technologies and capabilities over many years in our offices, and now we somehow, you know, came home with a laptop or a Chromebook. And the reality was, you know, did that really reflect the best power of the tools and the capabilities that the employees previously had access to in the office? And it's certainly been an area of focus for us at Citrix. It's really matching that set of capabilities so that no matter where the employee is, they get full access to the set of applications and services with the security and the control that you need to protect all the assets of the enterprise. >> You know PJ, I think this is actually really important, this concept. I'm calling it a right time experience, you know, right information to the right person at the right time. So how do you get your applications and services to them on whatever device they might have had during the pandemic? Because a lot of people didn't actually have laptops at home. Maybe they were in an environment where they were using desktops. So that application delivery was really important. The security wrapped around that is super important because now we're in a scenario where basically the crown jewels of an organization, their data, is in homes and other places distributed around the world. So, we have to make sure that A, that that's accessible and that B, that that's secured. And I think that this is a new imperative that we've talked about for some time, but how you deliver it in this new world is very different. And I think that the employee experience had always lagged the customer experience. And now we're trying to close that gap and hopefully take it to the next level. >> It could great point out. I was just kind of laughing. I think back if you dial back the clock, you know, say 15 years, the discussion was all about the consumerization of IT. The experience that I had at home when I was using devices or using technology was better than what I had at the office. Now of course, you know, not only do I see people taking laptops home, they have their big screen monitors. They need to make sure that they have access to the right data. We need to make sure that things are secure. So PJ, help us understand a little bit what are some of those services? It's not, you know, the VDI conversation that we were having a decade ago. So, you know, what is it that IT has either been delivering or scrambling to make sure that we can be as productive at home as we were sitting in the office? >> Well, I can certainly tell you that for our customers, the critical pieces of technology that they've been leveraging, start with the workspace experience. We deliver a workspace experience that includes VDI. It includes virtualized applications and desktops, and for many organizations, they still are, you know, critical applications. But the application portfolio that the employees use today is much broader than that, and includes, you know, web applications and SaaS applications, homegrown service based applications, et-cetera, as well as there are mobile applications. And so really wrapping all that in a single workspace, that's the journey that we've been on as a company. And it's really being put to the test right now, by our customers who are really trying to give employees access, not just maybe to the one or two core applications, they needed to do their job. But remember, in the six months that's gone by, most of the employees have had to, you know, fill out an expense report, or maybe use the HR system for some process or maybe take some time off that they wanted to record. So in addition to the core applications, they needed access to that full suite of applications that they use on a daily basis. And so that's certainly one set of technologies that our customers have been leveraging. They're using it both for the experience, but also for the security because we provide that same control over those applications inside the workspace experience no matter what type of application it is. And then I'd say the second area where our technology has been heavily leveraged is in our networking products providing the access and the control back to the enterprise resources that employees have to get access to on a daily basis. >> I think one of the things that you brought up PJ. Sorry, sorry Stu, is really important. And that's sort of that acceleration layer to make sure that you have a good experience, and that you have that secure connection. The other thing I think is really interesting is we're actually rethinking what that experience means for the employee. It used to be that when you were trying to create an experience, it was sort of one device, one universal look and feel for everything, one set of applications. I actually think that organizations are being much more thoughtful now when they're creating what PJ referred to as a workspace. You know, the workspace for Maribel might look very different than it does for Stu than it does for PJ, and it might be a combination of different style technologies. I mean, it could be that, you know, I'm in the contact center and I want to VDI experience dropped on me where I don't have to manage anything. I don't do anything. I just open up the device, and everything comes down to me. And then it all goes away when I'm done with my workday, because that's what needs to happen. You can't have private information on, you know, personal identifiable information on someone's home device. So, I think we're really going to be sophisticated about what a workspace means. >> Yeah. Maribel I was just commenting PJ made a comment. There's this thing he said, talked about taking a day off. I didn't realize that was still a thing in 2020. But, Maribel I'm curious, you know, as many people felt that this was okay. It was a short time. I'm going to have a couple of months and then we're just going to go back to the office. I think we understand now that however, things have fundamentally changed. And therefore, this isn't okay, hey, temporarily I can do this, and have to worry about my kids and myself and the space and the internet and all of these pieces. What do companies need to do to kind of make sure that we've set up our employees for success? You know, what are some of the challenges that you hear out there? That people are saying, Oh, geez, you know, I'm ready for it. And I think you laid out very well. There's a big difference between, you know, you might be a developer, in which case, you're probably used to working distributed with people all around the globe and asynchronously, versus somebody that was like, hey, wait, you know, everyday I can have a stand up meeting with my entire team and look across the table at them. >> Well, there's a lot going on. Some of it is cultural. Some of it is technical. And some of it's actually surprising on the technology side. I think the first thing that when we started with COVID, we realized that not everybody has the right portfolio of devices and while that might sound a bit insignificant, if you do not have the say right PC with the right performance to do video, that's difficult. Now we're talking about all the environmental elements. Right? Do you have the right lighting? Do you have the right audio capability? Can I actually see you with that webcam? Is the webcam in the right place? So, the environmental things are sort of the first stage. We just talked a bit about the security that people are struggling with now, making sure that they have people with the right security for the data they have. The education and training around that also hasn't been done. You know, we had a certain set of people that were trained on how to work remotely, but then we sent everyone home, and they're clicking on links that they shouldn't be clicking on and compromising devices. So, there's a lot of challenges still with the education and training that we're seeing. And then as I mentioned earlier, I think that organizations are trying to figure out what's the right portfolio services and do I have the right portfolio services. I actually purchased something to deal with COVID, but is that the right thing? You know, and now we're moving from what I'm calling remote light to remote right. Where we're really being very thoughtful about who needs what style of services, how scalable are those services? And then culturally, I mean, I think we have issues like, how do you deal with multiple time zones? You have to find a time zone that works for, say, Europe and Asia for everybody to be on the call. Is that really feasible? How do we think about that collaborative environment moving forward? So, a lot of interesting challenges ahead. >> Yeah. Actually, I see customers really struggling or at least planning on all three fronts right now. The first being the people processes that we use. And think about the number of employees that have been hired since this has started, who've had an onboarding experience that's been, let's say, at least unorthodox. And maybe very much not what they were expecting or their colleagues either. I have certainly many colleagues now that I've never met face to face for the duration of their careers at Citrix. And hopefully that will change at some point in the future. But I know in the meantime, we're going to onboard quite a few more employees who have that same experience. So, I think your people processes, starting with onboarding, but all the way through to, you know, training and everything else, especially for managers, I think is really important. Then you think about the processes that we have as companies, and how we conduct our own business on a day to day basis. And many of our processes were highly optimized for face to face communication, as you pointed out, Stu. Being in the same conference room across the table from each other. So how do we, I would say, lean down maybe a little bit our processes, make them a little leaner, make them easier to operate for people who are operating remotely? And then that last part is, of course, what's the technology that we bring to burry these solutions? Both I will say the technology that we enable people to have access to when they're remotely working, working from home, and then how do we reconfigure shared space, office spaces so that they make even more sense, when we're back in the office? Personally, I don't see myself going back to the office to do solo work. I see myself going back to the office to communicate with other employees, to collaborate with other people and to connect to my team. And I'll probably find other ways to get my work done. But I leverage the office more as a shared collaboration space than I'd previously thought about in the past. >> PJ, I liked what Maribel talked about setting up, you know, remote work right. You know, the promise has been, we've talked about for a lot of years, like I remember working in the telecom industry back in the 90s. It was going to be well, you know, we should have ubiquitous video and access to everything, wherever we are. You know, 5G, come on we're going to have enough bandwidth to be able to solve all these things, right? So, help us understand, you know, how do we deploy something today that gives people the flexibility? So that as you said, you can be remote when you're doing solo work, you can go to the office. And, you know, are we getting to the point that companies have that elasticity and agility of technology to enable that? >> Well, I certainly think while the problem may have gotten more complicated, I think the array of solutions that's available to customers is staggering right now. Let's start with just the cloud infrastructure that's available to organizations. It truly is elastic capacity, if you've built a cloud footprint for your organization. And we've seen many of our customers take advantage of moving what had been a small group of employees who may have been working remote to having to support everybody, and just extending that cloud infrastructure capacity. Clearly something that you can do in a very different way than if you're trying to build out data center capacity, for example, on-premises in order to deal with it. So I think that's one thing that's changed. The second thing you hinted at, which is just the quality of network infrastructure. Clearly not perfect, and those of us that are working from home and remote locations, occasionally experience the glitches that we probably didn't experience quite so much in the office. But on average, I would say that technology has proven to be a, you know, highly scalable and worthy of all of the investment that we've made in it as countries and as industry. So, that's the second one that I think is really, you know, really quite different. And the third one is, I think the nature of the solutions that have been built on top. Not just, you know, the technologies from Citrix. But you look at many of the other applications, whether it's modern video conferencing software, or collaboration tools, many of them are designed with the cloud in mind and with connectivity as a core principle. And so many of these things that we previously had as a personal computing devices, there are no shared computing resources accessing vast quantities of capability that's cloud based over networks that have really evolved quite rapidly. And while all of these will continue to require investment. Once again, I would have to say how impressed I've been with the way that the infrastructure and the technology has scaled to meet what was really unprecedented demand in the last six months. >> I guess one of the things I want to pick up on that PJ said, is I've been starting to talk to clients about this concept of moving from a network of buildings to the network of one. So, when we think of employee experience, you know, my experience is a summation of like, the devices, the bandwidth, the service quality of the services that we're buying. And really, instead of us looking at managing just a few, you know, this floor, the WiFi on this floor, this building. We're now starting to say, okay, if we've got 10,000 people, then we have, you know, 10,000 networks of one, so to speak, that we're looking at monitoring, managing, making sure that we've optimized that experience, so that if we all want to have a call like this, that we can actually have a high quality video experience together. That's not a trivial task for organization. So I think that's another thing that they have to think about. And I'm actually really happy about this workspace concept and moving to this workspace concept. Because the great thing about a workspace is it's yours and it can be delivered wherever you are, on whatever devices are available. So, if you want to go to the office and use a shared device, you can log in and it's Maribel's experience. If I want to be at home, it's my experience at home. If I want to be in a coffee shop someday or hotel someday, hopefully, it's that experience as well. So, that I think is extremely powerful in a different way to think about what we're trying to achieve. >> Maribel I want to come back to you. It's companies have really had to make decisions very fast this year. Talk about how this whole discussion we have about where people work fits into the broader discussions of their cloud strategy and their security strategy which we've touched on a little bit. >> Well, one of the things I think is fascinating is pre-COVID. The type of discussions we're having with people is, I don't know if I can go to the cloud, or only this type of data can go to the cloud. And I really have to figure out how to parse it and do governance on it. And we going to need a managed, you know, three to five year transition plan. And I plan on having X percent of my apps this year and Y percent of my apps. Well, hey, that all went out the window, if you really wanted to get work done, you basically ramped up your cloud efforts very quickly. So, many of the sacred cows have actually gone away, which I'm really excited about. Because now I think we can truly take that digital transformation concept to the next level, where we're saying, okay, we're not recreating everything that we had in the past. We're now starting to think about, well, what types of new processes and services make sense? How do we actually do business process transformation? Not just technology transformation. So, very big change within six months. Now, I think a lot of organizations had to do it quick and dirty. And now they're going back and they're saying, okay, you know, part of that remote light or remote right concept it's just in general. Did I buy the right things? Should I buy something different? What is the set of SaaS services, cloud infrastructure I need? So, they're going full guns, like digital transformation has happened for many organizations now. Now, how do we get it to the next level? >> I think Maribel one of the important things that you highlighted is in this transition to new platforms like moving to the cloud, that organizations go through. Step one often is to effectively recreate what they had in that new environment. But the reality is that the cloud and the capability of the cloud opens up a whole vast new array of potential and possibilities. And certainly already in our Citrix portfolio, there are many examples of places where we've built services and capabilities in the cloud that would have been, you know, frankly either unimaginable or impossible to build, when we were thinking about customers running all of the software themselves in their own data centers. And as that transition occurs more and more, the customers who have made the leap to the cloud, not only do they get the elasticity of the capacity and the scale and the global footprint that cloud providers give them, but they also get access to new services and capabilities that they can use to power experiences inside their enterprise, either for their customers, or for their employees. And so, if you think about it in generational terms, you know, I've probably witnessed less than a handful of what I think of as significant transitions in our industry. Whether it was mainframe to PC or PC to mobile or mobile to internet, and now this transition, which I think is really, I think in, you know, progress is the transition to cloud. That's that next big platform, that next big opportunity that I think is going to transform the way not only we deliver capabilities to employees, but the way we think about what technology can actually do for us as organizations. >> Yeah PJ, we've absolutely seen just such a huge acceleration. I've talked to some companies. They were dipping their toe in, and now they've jumped full in because they have to. As you both pointed out, though, security is something we need to really make sure that it's not, okay, I've jumped in and of course, everything's going to be fine. We understand shared responsibility model when we're talking about cloud. PJ, are there tips that you have for companies as to here's what you absolutely should do. And hey, maybe as you're expanding your remote workforce, maybe there's certain things that it's time to retire or rethink of the way you think about security in this aspect. >> I think, you know, the area where I think customers are really starting to focus right now is securing the experience and the devices that they have their employees working on on a day to day basis. That's really where the biggest shift has occurred in their infrastructure. If your applications were in your data center, they probably still are. If they were in the cloud, or from a SaaS vendor, they probably still are. It's the employees and their device that's really moved to a location that requires a rethink around security. And I think there's several approaches that we see customers take. One is, of course, if you own and manage the device that you've given to the employee, you can clearly secure the endpoint. And then from there, you can manage and secure the traffic. And you can secure access to the applications on the back end. In fact, in some ways, that's the, I'd said either the brute force way or the, I think, easiest way for an enterprise to achieve this. The reality is, though, that many enterprises have relied on, employees either leveraging personally owned devices or issuing them with devices that previously they hadn't thought about required that they needed management in the organization. And so this is where some of the technologies that we have at Citrix, where we've moved the security boundary from the physical device, to the workspace itself to the experience. Really allows you to migrate that same security profile across multiple platforms, across multiple endpoints, and still deliver that same experience to the employees. I think that's one from an experience point of view. And then the second one is, we've seen a lot of customers rely very heavily on VPN as an access mechanism to get to corporate resources. And again, I think it's a unfortunately one size doesn't fit all but VPN is is effectively a one size solution. And it is the keys to the kingdom. Once you have access to VPN inside an organization, you have access to everything that an employee I had access to. And so what we see is customers taking maybe a more granular view of how they implement security at the application level, so that they can grant me access to the apps that I need inside the data center infrastructure inside the enterprise infrastructure, but not necessarily all the applications and all the data and all the content. And so I think there are, you know, real technologies that are, you know, in the market today that are available to customers, to really come back and look at maybe some of those brute force solutions that they initially deployed. And now start to layer on maybe more granular and more sophisticated solutions on top of that. That really minimize the security risk, and narrow the exposure to literally just the data that's absolutely required and the applications that are absolutely required. >> You know, I actually want to pick up on this. 'Cause I think this is such a critical point for organizations and this VPN point is a good one. When I was talking about moving from remote light to remote right. VPN isn't enough, if you've given somebody access to the kingdom, what if they happen to be on a compromised device? Well, then you basically just opened, as PJ said, yourself up for bad actors to enter your organization. So, security continues to be a layer cake. It's always been a layer cake. Some people call it a Jenga Tower, same concept. But basically, you have to secure every layer of the stack. You have to secure at the device layer. You have to secure at the application layer, the network transit layer in the cloud. And I think that organizations that are really serious about this, are spending more time and energy trying to figure out where to plug those different gaps. But you can start as an organization, everything from what computing hardware do you buy. You know, does it have a secure route of trust on it? So, that's one thing if you're thinking about buying new equipment. And then you start to layer things like workspace technologies, device management technologies, and all those provide different layers of security up the stack. And sadly, as PJ said, you know, there is no silver bullet. But, we have gotten to a part where it could be easier where you can buy fewer things, but it's still a coordinated effort of tools to make that whole stack secure. >> Alright, the last technology area I want to poke at, is we haven't talked about data yet. You know, there's the opportunity for analytics. You know, and it's a little bit, you know, Maribel maybe start with you. There's the opportunity to really understand, you know, are people leveraging things? Are there problems that maybe they might not report that the system can let me? But you also want to make sure that it's not big brother looking over what we're doing, and there's concern about that. So, what are you seeing out there? Any, you know, emerging trends as to how that work remote right that you talk about can leverage analytics and data? >> So the first thing I think is really important is the fact that you should be looking for technology providers that do collect and provide a certain amount of analytics for you. And then the question is, how detailed do you want that analytics? Do you want that analytics down to a user level? Well, if it turns out to be network performance, that's great. If it turns out to be, you know, every application they've entered, and how much is in, and how much time they spent on that application. Maybe yes, maybe no. Maybe you want it to be a little more lightweight. You know, maybe it's something that says, if this application hasn't been used in any period of time, because that's an issue around licensing. Do you need that licensing? But do you need to know if I've been spending, you know, 30 hours a week in Outlook. There's a bit of a privacy dance that we need to do there. There's just because you can doesn't mean you should. But what you really should be talking to your vendors about is, you know, how can I see what the experience is that my employees are having with your service? You know, is it operational? Is it being used? Should it be be optimized in some way? Are there analytics that you can provide me that prevent issues? You know, if there is a slowdown in the network, I need to know that that's going to impact users. If there's an outage in a service, I need to know what the impact is to that user and then maybe be able to predict some of those things before it happens so that we can manage and control that experience. So I think analytics are important. I think you have to really say, okay, what are we trying to achieve with those analytics? And balance the privacy and experience. >> So maybe a couple of comments. We've been investing in our analytics platform before this pandemic struck. And so we've seen quite a significant shift in the use cases that customers are applying those analytics to address. The first one really is for remote workers. The point that Maribel alluded to is, you know, have I delivered as secure an experience as I previously had delivered to my employees who (indistinct) the office, and how do I measure myself against that? And certainly we have the security analytics capability to help organizations understand anomalies in the system. Whether or not they're occurring, you know, inside the data center or on the endpoint device that the employee is using. And so that's one that I think customers are finding very valuable. The secondary is to do with actually the quality of that experience, the performance of that individual experience. And so we're again tracking at the user level, what their experience is like. And we're allowing organizations to have visibility into whether or not, they've actually delivered a usable, you know, high quality experience to all of their employees. Something that I frequently saw IT do by walking into offices and looking over your shoulder as you use an application and saying that's pretty good performance. And now of course, they're relying on remote response from remote employees with, you know, networks that they don't manage. So really, can you get a handle on what that experience is like. So both of those are actually analytic services that are aimed at helping IT deliver a high quality, reliable, secure service. The other area where we are exploring and beginning to see some usage for analytics is actually sharing the insight of usage and patterns of usage with the employee themselves. So while it might not be advisable to record how many hours I spend in a given application and shared that with IT, it might be useful information to share back with the employee themselves, about their pattern of usage of applications. Maybe recommending applications that other people in their team or their work group are using. Maybe recommending content, documents, insights, reports that other people have access to. And so if you start to take a broader look at how that analytics, then understanding of user behavior can get used. You can see that it can not only inform the security posture understanding of the organization, but it can also augment the employees on experience inside the workspace. And personally, that's where I'm most excited about the use of analytics is not so much on the IT side, which I think is quite expected. I think it is the novel and innovative use of analytics to really drive new experiences inside the workspace. >> I think this contextual concept is great, right? So, understanding how you use your services, understanding what your team uses, providing that extra bit of analytics that tries to help you figure out what you should be doing next, how can you optimize your own personal performance and productivity. That's where we start to see the analytics sing and do something different that we didn't do before. So, it learns about me. It predicts things but it also creates, helps me create new new, better employees experiences. >> Yeah, I think my phone is keeps asking me if I want to uninstaller the entire folder of travel apps, because it's been a long time since I've touched those. Look, it's been a really great discussion. If there's one thing we've learned this year is that you need to be open to the new data, and listening to everyone and being able to adjust fast. As we said early on in this whole pandemic, (indistinct) the companies that have gone through digital transformation, they're lucky because the agility that they built into their processes is going to allow them to do that. But as we've seen, many other companies are moving fast. And I think Satya Nadella is the one who said, you know, we did two years worth of, you know, transformation in two months. So, I want to just give you both a final word, you know, final advice for companies as they look at that challenge in front of them as to back to work that we set up at the beginning. PJ, we'll start with you. >> Well, thank you, Stu. I mean be the first thing I'd say is once again how, you know, I've been impressed by the organizations that we work with our customers, and their ability to move quickly to address the immediate problems. I think the good news is that this was a roadmap and a journey that many of their suppliers and vendors, including Citrix, we were on the path to help deliver solutions that are very much aligned with what these organizations are experiencing. So I think it's a great time to engage with organizations like ours and others that are providing these technologies to understand what that roadmap actually looks like. And to really pick the best of what's out there to help organizations, I think, make them more thoughtful and considered and probably long term decisions that they've got to make over the next, you know, six to 12 months that really set them up for success here in the future. I'm very excited because in many ways, I feel like that experience that organizations had of accelerating their two year project through, you know, two months or two weeks. That's a journey that we've been on with those customers. And we are excited by the fact that they've come through that first phase. Lots of people have a lot of things, still to figure out ahead of them. And we're delighted and honored to be engaged with those customers to help them through that. >> So for me, when I talk to customers, I say this is an amazing time to reimagine your business and really focus on what you think your technology and strategic advantage of your business is. Use technology for that. You can build versus buy. Build for the things that are going to create strategic advantage, buy for everything else. >> Maribel and PJ, thank you so much for joining me. Great discussion, lots things for people to think about. And looking forward to watching everybody as they go through their journey in the next steps going back to work. >> Thank you. >> Thank you. >> And thank you for joining us. I'm Stu Miniman. As always, thank you for watching "theCUBE". (upbeat music)

>>from around the globe. It's the Cube covering upgrade 2020 The NTT Research Summit presented by NTT Research. >>Hi, I'm stupid, man. And this is the Cubes coverage of Upgrade 2020 the global research Summit for NTT and always happy when we get to talk about digital transformation. Happy to welcome to the program First time guests on the program. Eric Clark. He is the chief digital officer with NTT Data. Thanks so much for joining us. Thank >>you. Glad to be here. >>All right, so let's start, you know, CDOs. First of all, there there's lots of studios. We've done lots of events with the chief data officers, which I'm sure we'll talk a little bit about data. But the digital officers, of course, digital so important in general. And even more so in 2020. But let's understand your role is as chief digital officer. What's your charter where you sit in York? What you're responsible for? >>Yeah, definitely. And you know, it's a good question. I often start conversations with our customers by talking about exactly that, because Chief Digital officer means something different toe different companies. So for us, it's primarily market facing. Onda What that means is I spend most of my time looking at research, looking at R and D, looking at what our competitors are doing in the market and looking at where trends. We're going to make sure that we have the right offerings and capabilities to bring to our customers to make sure that they will remain competitive in their markets. >>That's great. You know, We've been talking for years about the, you know, the digital transformations that companies have been going through. One of our definitions have been. If you're not at the end of it, more data driven, you probably haven't done the right thing. But Eric, this year with 2020 you know, anecdotally we talked to a lot of customers, and obviously there's certain initiatives that get frozen or, you know, uh, we'll take a little bit longer. But those digital initiatives, which are supposed to rely on data and help us move fast and be more agile, seem to be at the top of the list and are accelerating because if I can't respond to you know, the daily and weekly changes that have been great in 2020 you know, I might have a tough time surviving. So what are you seeing? You know, how does that live in your world? >>Yeah, you're exactly right. And that's what we're seeing from our client base as well. So early on in the pandemic, there was a lot of freeze, you know, hold everything. Stop. Stop spending. And let's figure out where we are and where this is going. But very quickly that turn to we've got to react. We're gonna be living with this for a while and we can't. We can't afford to sit back and wait and see where it goes. We've got to react, and we've got to direct our our future. And very often the way that comes out is with digital. So you know, customers are looking for opportunities to leverage digital, to grow revenue, to improve customer engagement and to drive more of their revenue through digital channels. >>Interested in one thing I didn't here and there, but I'm sure is part of it. What about the employees themselves? One of the big things, of course, is that we've made this wonderful corporate environment. You've got the great great Internet there, and now wait. Everybody's at home and scrambling as to what they do. So so how about the kind of the the e x to go along with the C X? Yeah, >>exactly. And that was actually one of the first places that we focused as a company, because we do a lot of you know what we refer to as workplace services. So making sure that our customers employees have the tools they need to do their job successfully. Eso immediately. When when officers started closing and people started going home, our big challenge was Let's make sure that our customers can connect from anywhere from wherever they need to be working from and have access to the applications and the tools and the products that they need to perform their jobs remotely. And that's really turned into a significant business of its own of, you know, really addressing those needs not only for our customers but also for our employee base. You know, we have 50,000 people that we sent home more than 90% of overnight, and you know, many of these are our employees that are interacting with our customer based on a daily basis, So we had to make sure not only that they had connective, >>but >>he had to be secure. So it was a very big switch. And I think I personally was really impressed. Not only with what we did, but what we saw. The industry. Dutilleux make that transition very safely and seamlessly. >>Well, let's Eric, I love you to expand a little bit on that. You know which pieces of that that full solution, Uh, is NTT offering? And how do you and your partner's, uh, you know, help your customers through. You know, those rapid options that they need? >>Yeah, so So So we're a full suite provider. So we're focused on digital operations, which is, you know, digitizing your back office from your workplace services to your hybrid infrastructure network, etcetera, all the way through bringing. You know what? We refer to his journey to the cloud. So how do we help you identify what applications and what data you need in the cloud? Um uh, c X and E x. Very big focuses for us. In fact, we take a lot of pride in while we do go to market and sell c X specifically, we consider c x part of everything we do so if we're talking about workplace services or hybrid infrastructure or security. We want the employee experience to be solid, and we want the employee experience to be consistent across all of those things. So way think that our customers should not expect to have different interfaces and different portals and different user experiences when they do work with us across infrastructure and application and cloud etcetera. >>That's excellent, Eric. You know, we spent the last six months talking about how do we react to the pandemic? And now, at least, you know, here in the U. S. Uh, the Children are back in school. If they're back, though, it tends to be ah, hybrid model. And when we look at work, often we know we're gonna have this elongated kind of new abnormal, if you will. So, yes, you might be back in the office some, but chances are you will spend some time remote and therefore it's not work from home or back toe work. It's work from anywhere, is what I need to be able to do. So how are you preparing? How are you helping your customers through that? Because, you know, it's one thing if it was just, you know, a switch that says I'm either here or there, but it z changing and it's very fluid. >>Yeah, and you're exactly right. It is work from anywhere, but there are some of our customers that don't have the luxury of work from anywhere. So when you think about manufacturing facilities and different hospitality companies, um, there there are people that need to go into physical places. We do a lot in the healthcare space. We need doctors in the hospitals. So we've done a lot to help our customers figure out safe ways to return to the work. Recently, we've seen universities and, as you mentioned, you know, high schools and elementary schools all going back with varying degrees of success, right? Some of them have failed, and they've had to take a pause and and figure out how they're going to restart. We've also seen professional sports leagues and now college sports leagues. Andi, When we see them having issues, we see protocols adjusting and we see them looking for what can we do to make this safer, more effective and more successful for whether it's our sports team, our school or our business. So we've taken a very active approaching that, and we're leveraging technology and creating I P. That starts with pre arrival, you know, registering in advance and, you know, opting in for things like tracking social distancing and tracking the use of mask, then using cameras and facilities to monitor it, to make sure people that are are adhering to social distancing and adhering to wearing masks. Andi In the event that they aren't we can send instant notifications to their phone. If we have repeat violators, Weaken. Prohibit them from coming back to the office so we can have very strict controls and adherence to whatever the protocols. Maybe as the protocols change. And then the other thing that allows us to do is in the event someone would test positive with co vid, we will know exactly who they've been within 6 ft of without a mask over the past X number of days. All that is stored in the cloud for us to, you know, use for reference and use for audit purposes so that gives us the ability to then use are apt to direct all the people that the person that was positive was in contact with, let them go, get tested, come back with a negative test before they return to the office. So So, basically, what we've done is we've created all kinds of technology using automation and AI and facial recognition to bring MAWR safety and more security to the workplace. Whatever that work placement might be, whether again, school, university manufacturing facility or a hotel >>Really interesting topic. You know, tracking and tracing so critically important we've seen in many countries around the world. That's really help them get their arms around and control that. You know, we talked to the top of the interview about, you know, digital means leveraging the data. And if I don't have the data, I can't respond to what's happening there. Um, here in the US, I haven't heard as much about the tracking and tracing. Is this a company by company thing do they have is the expense all on them to do it? And of course, it raises the concerns about Well, I'm concerned about my privacy and that that balance between the public interest on my right to privacy, how do you help your customer sort through some of those issues >>Well, privacy is definitely a big issue. And, you know, you noticed that when I was explaining that I said in pre pre arrival, you opt in. So the way we've approached it is it is an opt in. So those that don't wanna opt into that kind of tracking and tracing, um won't won't be those that will be allowed to come back to the office. And that goes back to your other point of work from anywhere. Many of those people can still successfully work from anywhere but those that feel like they're more effective, more successful or have a need to be in an office or need to be physically again in a manufacturing facility or a hotel. We have a way to do that safely, >>right? Well, Eric, one of the things I love about research events like yours is a little peek in tow. What's coming on down the road? So any other things you'd like toe, you know, share about, You know, some of the things that are exciting. You some things we should be looking at a little bit further down the road. >>Well, I think you know for us, as you know, We spend a significant amount of money each year on research, and and we really get excited about thes thes opportunities in these showcases. So you'll see ah, lot of exciting information and a lot of what's coming in the future. Um, a lot of it right now, obviously, because of the times you'll see themes of safety and security. Um, but you're also going to see just ah, whole lot of really thought provoking forward thinking technology. >>Always take the opportunity. Even when there are crisis is out there. There's the opportunity for innovation and acceleration off. What's happening? Eric, Thanks so much pleasure talking with you and definitely looking forward to hearing more from from the event. >>Great. Thank you. Enjoyed it. >>Stay with us for more coverage from upgrade 2020 times to minimum. Thanks as always, for watching cute with

>> Announcer: From around the globe, it's theCUBE. Covering the UPGRADE 2020, the NTT Research Summit. Presented by NTT research. >> Hey, welcome back everybody. Jeff Frick here with theCUBE. Welcome back to our ongoing coverage of UPGRADE 2020. It's the NTT Research Labs Summit, and it's all about upgrading reality. Heavy duty basic research around a bunch of very smart topics. And we're really excited to have our next guest to kind of dive in. I promise you, it'll be the deepest conversation you have today, unless you watch a few more of these segments. So our first guest we're welcoming back Kazuhiro Gomi He's the president and CEO of NTT research, Kaza great to see you. >> Good to see you. And joining him is Yoshi Yamamoto. He is a fellow for NTT Research and also the director of the Physics and Informatics Lab. Yoshi, great to meet you as well. >> Nice to meet you. >> So I was teasing the crew earlier, Yoshi, when I was doing some background work on you and I pulled up your Wikipedia page and I was like, okay guys, read this thing and tell me what a, what Yoshi does. You that have been knee deep in quantum computing and all of the supporting things around quantum heavy duty kind of next gen computing. I wonder if you can kind of share a little bit, you know, your mission running this labs and really thinking so far in advance of what we, you know, kind of experience and what we work with today and this new kind of basic research. >> NTT started the research on quantum computing back in 1986 87. So it is already more than 30 years. So, the company invested in this field. We have accumulated a lot of sort of our ideas, knowledge, technology in this field. And probably, it is the right time to establish the connection, close connection to US academia. And in this way, we will jointly sort of advance our research capabilities towards the future. The goal is still, I think, a long way to go. But by collaborating with American universities, and students we can accelerate NTT effort in this area. >> So, you've been moving, you've been working on quantum for 30 years. I had no idea that that research has been going on for such a very long time. We hear about it in the news and we hear about it a place like IBM and iSensor has a neat little demo that they have in the new sales force period. What, what is, what makes quantum so exciting and the potential to work so hard for so long? And what is it going to eventually open up for us when we get it to commercial availability? >> The honest answer to that question is we don't know yet. Still, I think after 30 years I think of hard working on quantum Physics and Computing. Still we don't know clean applications are even, I think we feel that the current, all the current efforts, are not necessarily, I think, practical from the engineering viewpoint. So, it is still a long way to go. But the reason why NTT has been continuously working on the subject is basically the very, sort of bottom or fundamental side of the present day communication and the computing technology. There is always a quantum principle and it is very important for us to understand the quantum principles and quantum limit for communication and computing first of all. And if we are lucky, maybe we can make a breakthrough for the next generation communication and computing technology based on quantum principles. >> Right. >> But the second, is really I think just a guess, and hope, researcher's hope and nothing very solid yet. >> Right? Well, Kazu I want to go, go to you cause it really highlights the difference between, you know, kind of basic hardcore fundamental research versus building new applications or building new products or building new, you know, things that are going to be, you know, commercially viable and you can build an ROI and you can figure out what the customers are going to buy. It really reflects that this is very different. This is very, very basic with very, very long lead times and very difficult execution. So when, you know, for NTT to spend that money and invest that time and people for long, long periods of time with not necessarily a clean ROI at the end, that really, it's really an interesting statement in terms of this investment and thinking about something big like upgrading reality. >> Yeah, so that's what this, yeah, exactly that you talked about what the basic research is, and from NTT perspective, yeah, we feel like we, as Dr. Yamamoto, he just mentioned that we've been investing into 30 plus years of a time in this field and, you know, and we, well, I can talk about why this is important. And some of them is that, you know, that the current computer that everybody uses, we are certainly, well, there might be some more areas of improvement, but we will someday in, I don't know, four years, five years, 10 years down the road, there might be some big roadblock in terms of more capacity, more powers and stuff. We may run into some issues. So we need to be prepared for those kinds of things. So, yes we are in a way of fortunate that we are, we have a great team to, and a special and an expertise in this field. And, you know, we have, we can spend some resource towards that. So why not? We should just do that in preparation for that big, big wall so to speak. I guess we are expecting to kind of run into, five, 10 years down the road. So let's just looking into it, invest some resources into it. So that's where we are, we're here. And again, I I'm, from my perspective, we are very fortunate that we have all the resources that we can do. >> It's great. Right, as they give it to you. Dr. Yamamoto, I wonder if you can share what it's like in terms of the industry and academic working together. You look at the presentations that are happening here at the event. All the great academic institutions are very well represented, very deep papers. You at NTT, you spend some time at Stanford, talk about how it is working between this joint development with great academic institutions, as well as the great company. >> Traditionally in the United States, there has been always two complementary opportunities for training next generation scientists and engineers. One opportunity is junior faculty position or possible position in academia, where main emphasis is education. The other opportunity is junior researcher position in industrial lab where apparently the focus emphasis is research. And eventually we need two types of intellectual leaders from two different career paths. When they sort of work together, with a strong educational background and a strong research background, maybe we can make wonderful breakthrough I think. So it is very important to sort of connect between two institutions. However, in the recent past, particularly after Better Lab disappeared, basic research activity in industrial lab decreases substantially. And we hope MTT research can contribute to the building of fundamental science in industry side. And for that purpose cross collaboration with research Universities are very important. So the first task we have been working so far, is to build up this industry academia connection. >> Huge compliment NTT to continue to fund the basic research. Cause as you said, there's a lot of companies that were in it before and are not in it any more. And when you often read the history of, of, of computing and a lot of different things, you know, it goes back to a lot of times, some basic, some basic research. And just for everyone to know what we're talking about, I want to read a couple of, of sessions that you could attend and learn within Dr. Yamamoto space. So it's Coherent nonlinear dynamics combinatorial optimization. That's just one session. I love it. Physics successfully implements Lagrange multiplier optimization. I love it. Photonics accelerators for machine learning. I mean, it's so it's so interesting to read basic research titles because, you know, it's like a micro-focus of a subset. It's not quantum computing, it's all these little smaller pieces of the quantum computing stack. And then obviously very deep and rich. Deep dives into those, those topics. And so, again, Kazu, this is the first one that's going to run after the day, the first physics lab. But then you've got the crypto cryptography and information security lab, as well as the medical and health information lab. You started with physics and informatics. Is that the, is that the history? Is that the favorite child you can lead that day off on day two of the event. >> We did throw a straw and Dr. Yamamoto won it Just kidding (all laugh) >> (indistinct), right? It's always fair. >> But certainly this quantum, Well, all the topics certainly are focuses that the basic research, that's definitely a commonality. But I think the quantum physics is in a way kind of very symbolic to kind of show that the, what the basic research is. And many people has a many ideas associated with the term basic research. But I think that the quantum physics is certainly one of the strong candidates that many people may think of. So well, and I think this is definitely a good place to start for this session, from my perspective. >> Right. >> Well, and it almost feels like that's kind of the foundational even for the other sessions, right? So you talk about medical or you talk about cryptography in information, still at the end of the day, there's going to be compute happening to drive those processes. Whether it's looking at, at, at medical slides or trying to do diagnosis, or trying to run a bunch of analysis against huge data sets, which then goes back to, you know, ultimately algorithms and ultimately compute, and this opening up of this entirely different set of, of horsepower. But Dr. Yamamoto, I'm just curious, how did you get started down this path of, of this crazy 30 year journey on quantum computing. >> The first quantum algorithm was invented by David Deutsch back in 1985. These particular algorithm turned out later the complete failure, not useful at all. And he spent seven years, actually, to fix loophole and invented the first successful algorithm that was 1992. Even though the first algorithm was a complete failure, that paper actually created a lot of excitement among the young scientists at NTT Basic Research Lab, immediately after the paper appeared. And 1987 is actually, I think, one year later. So this paper appeared. And we, sort of agreed that maybe one of the interesting future direction is quantum information processing. And that's how it started. It's it's spontaneous sort of activity, I think among young scientists of late twenties and early thirties at the time. >> And what do you think Dr. Yamamoto that people should think about? If, if, if again, if we're at a, at a cocktail party, not with not with a bunch of, of people that, that intimately know the topic, how do you explain it to them? How, how should they think about this great opportunity around quantum that's kept you engaged for decades and decades and decades. >> The quantum is everywhere. Namely, I think this world I think is fundamentally based on and created from quantum substrate. At the very bottom of our, sort of world, consist of electrons and photons and atoms and those fundamental particles sort of behave according to quantum rule. And which is a very different from classical reality, namely the world where we are living every day. The relevant question which is also interesting is how our classical world or classical reality surfaces from the general or universal quantum substrate where our intuition never works. And that sort of a fundamental question actually opens the possibility I think by utilizing quantum principle or quantum classical sort of crossover principle, we can revolutionize the current limitation in communication and computation. That's basically the start point. We start from quantum substrate. Under classical world the surface is on top of quantum substrate exceptional case. And we build the, sort of communication and computing machine in these exceptional sort of world. But equally dig into quantum substrate, new opportunities is open for us. That's somewhat the fundamental question. >> That's great. >> Well, I'm not, yeah, we can't get too deep cause you'll lose me, you'll lose me long before, before you get to the bottom of the, of the story, but, you know, I really appreciate it. And of course back to you this is your guys' first event. It's a really bold statement, right? Upgrade reality. I just wonder if, when you look at the, at the registrant's and you look at the participation and what do you kind of anticipate, how much of the anticipation is, is kind of people in the business, you know, kind of celebrating and, and kind of catching up to the latest research and how much of it is going to be really inspirational for those next, you know, early 20 somethings who are looking to grab, you know, an exciting field to hitch their wagon to, and to come away after this, to say, wow, this is something that really hooked me and I want to get down and really kind of advance this technology a little bit, further advance this research a little bit further. >> So yeah, for, from my point of view for this event, I'm expecting, there are quite wide range of people. I'm, I'm hoping that are interested in to this event. Like you mentioned that those are the, you know, the business people who wants to know what NTT does, and then what, you know, the wider spectrum of NTT does. And then, and also, especially like today's events and onwards, very specific to each topic. And we go into very deep dive. And, and so to, to this session, especially in a lot of participants from the academia's world, for each, each subject, including students, and then some other, basically students and professors and teachers and all those people as well. So, so that's are my expectations. And then from that program arrangement perspective, that's always something in my mind that how do we address those different kind of segments of the people. And we all welcoming, by the way, for those people. So to me to, so yesterday was the general sessions where I'm kind of expecting more that the business, and then perhaps some other more and more general people who're just curious what NTT is doing. And so instead of going too much details, but just to give you the ideas that the what's that our vision is and also, you know, a little bit of fla flavor is a good word or not, but give you some ideas of what we are trying to do. And then the better from here for the next three days, obviously for the academic people, and then those who are the experts in each field, probably day one is not quite deep enough. Not quite addressing what they want to know. So day two, three, four are the days that designed for that kind of requirements and expectations. >> Right? And, and are most of the presentations built on academic research, that's been submitted to journals and other formal, you know, peer review and peer publication types of activities. So this is all very formal, very professional, and very, probably accessible to people that know where to find this information. >> Mmh. >> Yeah, it's great. >> Yeah. >> Well, I, I have learned a ton about NTT and a ton about this crazy basic research that you guys are doing, and a ton about the fact that I need to go back to school if I ever want to learn any of this stuff, because it's, it's a fascinating tale and it's it's great to know as we've seen these other basic research companies, not necessarily academic but companies kind of go away. We mentioned Xerox PARC and Bell Labs that you guys have really picked up that mantle. Not necessarily picked it up, you're already doing it yourselves. but really continuing to carry that mantle so that we can make these fundamental, basic building block breakthroughs to take us to the next generation. And as you say, upgrade the future. So again, congratulations. Thanks for sharing this story and good luck with all those presentations. >> Thank you very much. >> Thank you. >> Thank you. Alright, Yoshi, Kazu I'm Jeff, NTT UPGRADE 2020. We're going to upgrade the feature. Thanks for watching. See you next time. (soft music)