>> From theCUBE Studios in Palo Alto in Boston, bringing you data-driven insights from theCUBE and ETR. This is Breaking Analysis with Dave Vellante. >> OpenAI The company, and ChatGPT have taken the world by storm. Microsoft reportedly is investing an additional 10 billion dollars into the company. But in our view, while the hype around ChatGPT is justified, we don't believe OpenAI will lock up the market with its first mover advantage. Rather, we believe that success in this market will be directly proportional to the quality and quantity of data that a technology company has at its disposal, and the compute power that it could deploy to run its system. Hello and welcome to this week's Wikibon CUBE insights, powered by ETR. In this Breaking Analysis, we unpack the excitement around ChatGPT, and debate the premise that the company's early entry into the space may not confer winner take all advantage to OpenAI. And to do so, we welcome CUBE collaborator, alum, Sarbjeet Johal, (chuckles) and John Furrier, co-host of the Cube. Great to see you Sarbjeet, John. Really appreciate you guys coming to the program. >> Great to be on. >> Okay, so what is ChatGPT? Well, actually we asked ChatGPT, what is ChatGPT? So here's what it said. ChatGPT is a state-of-the-art language model developed by OpenAI that can generate human-like text. It could be fine tuned for a variety of language tasks, such as conversation, summarization, and language translation. So I asked it, give it to me in 50 words or less. How did it do? Anything to add? >> Yeah, think it did good. It's large language model, like previous models, but it started applying the transformers sort of mechanism to focus on what prompt you have given it to itself. And then also the what answer it gave you in the first, sort of, one sentence or two sentences, and then introspect on itself, like what I have already said to you. And so just work on that. So it it's self sort of focus if you will. It does, the transformers help the large language models to do that. >> So to your point, it's a large language model, and GPT stands for generative pre-trained transformer. >> And if you put the definition back up there again, if you put it back up on the screen, let's see it back up. Okay, it actually missed the large, word large. So one of the problems with ChatGPT, it's not always accurate. It's actually a large language model, and it says state of the art language model. And if you look at Google, Google has dominated AI for many times and they're well known as being the best at this. And apparently Google has their own large language model, LLM, in play and have been holding it back to release because of backlash on the accuracy. Like just in that example you showed is a great point. They got almost right, but they missed the key word. >> You know what's funny about that John, is I had previously asked it in my prompt to give me it in less than a hundred words, and it was too long, I said I was too long for Breaking Analysis, and there it went into the fact that it's a large language model. So it largely, it gave me a really different answer the, for both times. So, but it's still pretty amazing for those of you who haven't played with it yet. And one of the best examples that I saw was Ben Charrington from This Week In ML AI podcast. And I stumbled on this thanks to Brian Gracely, who was listening to one of his Cloudcasts. Basically what Ben did is he took, he prompted ChatGPT to interview ChatGPT, and he simply gave the system the prompts, and then he ran the questions and answers into this avatar builder and sped it up 2X so it didn't sound like a machine. And voila, it was amazing. So John is ChatGPT going to take over as a cube host? >> Well, I was thinking, we get the questions in advance sometimes from PR people. We should actually just plug it in ChatGPT, add it to our notes, and saying, "Is this good enough for you? Let's ask the real question." So I think, you know, I think there's a lot of heavy lifting that gets done. I think the ChatGPT is a phenomenal revolution. I think it highlights the use case. Like that example we showed earlier. It gets most of it right. So it's directionally correct and it feels like it's an answer, but it's not a hundred percent accurate. And I think that's where people are seeing value in it. Writing marketing, copy, brainstorming, guest list, gift list for somebody. Write me some lyrics to a song. Give me a thesis about healthcare policy in the United States. It'll do a bang up job, and then you got to go in and you can massage it. So we're going to do three quarters of the work. That's why plagiarism and schools are kind of freaking out. And that's why Microsoft put 10 billion in, because why wouldn't this be a feature of Word, or the OS to help it do stuff on behalf of the user. So linguistically it's a beautiful thing. You can input a string and get a good answer. It's not a search result. >> And we're going to get your take on on Microsoft and, but it kind of levels the playing- but ChatGPT writes better than I do, Sarbjeet, and I know you have some good examples too. You mentioned the Reed Hastings example. >> Yeah, I was listening to Reed Hastings fireside chat with ChatGPT, and the answers were coming as sort of voice, in the voice format. And it was amazing what, he was having very sort of philosophy kind of talk with the ChatGPT, the longer sentences, like he was going on, like, just like we are talking, he was talking for like almost two minutes and then ChatGPT was answering. It was not one sentence question, and then a lot of answers from ChatGPT and yeah, you're right. I, this is our ability. I've been thinking deep about this since yesterday, we talked about, like, we want to do this segment. The data is fed into the data model. It can be the current data as well, but I think that, like, models like ChatGPT, other companies will have those too. They can, they're democratizing the intelligence, but they're not creating intelligence yet, definitely yet I can say that. They will give you all the finite answers. Like, okay, how do you do this for loop in Java, versus, you know, C sharp, and as a programmer you can do that, in, but they can't tell you that, how to write a new algorithm or write a new search algorithm for you. They cannot create a secretive code for you to- >> Not yet. >> Have competitive advantage. >> Not yet, not yet. >> but you- >> Can Google do that today? >> No one really can. The reasoning side of the data is, we talked about at our Supercloud event, with Zhamak Dehghani who's was CEO of, now of Nextdata. This next wave of data intelligence is going to come from entrepreneurs that are probably cross discipline, computer science and some other discipline. But they're going to be new things, for example, data, metadata, and data. It's hard to do reasoning like a human being, so that needs more data to train itself. So I think the first gen of this training module for the large language model they have is a corpus of text. Lot of that's why blog posts are, but the facts are wrong and sometimes out of context, because that contextual reasoning takes time, it takes intelligence. So machines need to become intelligent, and so therefore they need to be trained. So you're going to start to see, I think, a lot of acceleration on training the data sets. And again, it's only as good as the data you can get. And again, proprietary data sets will be a huge winner. Anyone who's got a large corpus of content, proprietary content like theCUBE or SiliconANGLE as a publisher will benefit from this. Large FinTech companies, anyone with large proprietary data will probably be a big winner on this generative AI wave, because it just, it will eat that up, and turn that back into something better. So I think there's going to be a lot of interesting things to look at here. And certainly productivity's going to be off the charts for vanilla and the internet is going to get swarmed with vanilla content. So if you're in the content business, and you're an original content producer of any kind, you're going to be not vanilla, so you're going to be better. So I think there's so much at play Dave (indistinct). >> I think the playing field has been risen, so we- >> Risen and leveled? >> Yeah, and leveled to certain extent. So it's now like that few people as consumers, as consumers of AI, we will have a advantage and others cannot have that advantage. So it will be democratized. That's, I'm sure about that. But if you take the example of calculator, when the calculator came in, and a lot of people are, "Oh, people can't do math anymore because calculator is there." right? So it's a similar sort of moment, just like a calculator for the next level. But, again- >> I see it more like open source, Sarbjeet, because like if you think about what ChatGPT's doing, you do a query and it comes from somewhere the value of a post from ChatGPT is just a reuse of AI. The original content accent will be come from a human. So if I lay out a paragraph from ChatGPT, did some heavy lifting on some facts, I check the facts, save me about maybe- >> Yeah, it's productive. >> An hour writing, and then I write a killer two, three sentences of, like, sharp original thinking or critical analysis. I then took that body of work, open source content, and then laid something on top of it. >> And Sarbjeet's example is a good one, because like if the calculator kids don't do math as well anymore, the slide rule, remember we had slide rules as kids, remember we first started using Waze, you know, we were this minority and you had an advantage over other drivers. Now Waze is like, you know, social traffic, you know, navigation, everybody had, you know- >> All the back roads are crowded. >> They're car crowded. (group laughs) Exactly. All right, let's, let's move on. What about this notion that futurist Ray Amara put forth and really Amara's Law that we're showing here, it's, the law is we, you know, "We tend to overestimate the effect of technology in the short run and underestimate it in the long run." Is that the case, do you think, with ChatGPT? What do you think Sarbjeet? >> I think that's true actually. There's a lot of, >> We don't debate this. >> There's a lot of awe, like when people see the results from ChatGPT, they say what, what the heck? Like, it can do this? But then if you use it more and more and more, and I ask the set of similar question, not the same question, and it gives you like same answer. It's like reading from the same bucket of text in, the interior read (indistinct) where the ChatGPT, you will see that in some couple of segments. It's very, it sounds so boring that the ChatGPT is coming out the same two sentences every time. So it is kind of good, but it's not as good as people think it is right now. But we will have, go through this, you know, hype sort of cycle and get realistic with it. And then in the long term, I think it's a great thing in the short term, it's not something which will (indistinct) >> What's your counter point? You're saying it's not. >> I, no I think the question was, it's hyped up in the short term and not it's underestimated long term. That's what I think what he said, quote. >> Yes, yeah. That's what he said. >> Okay, I think that's wrong with this, because this is a unique, ChatGPT is a unique kind of impact and it's very generational. People have been comparing it, I have been comparing to the internet, like the web, web browser Mosaic and Netscape, right, Navigator. I mean, I clearly still remember the days seeing Navigator for the first time, wow. And there weren't not many sites you could go to, everyone typed in, you know, cars.com, you know. >> That (indistinct) wasn't that overestimated, the overhyped at the beginning and underestimated. >> No, it was, it was underestimated long run, people thought. >> But that Amara's law. >> That's what is. >> No, they said overestimated? >> Overestimated near term underestimated- overhyped near term, underestimated long term. I got, right I mean? >> Well, I, yeah okay, so I would then agree, okay then- >> We were off the charts about the internet in the early days, and it actually exceeded our expectations. >> Well there were people who were, like, poo-pooing it early on. So when the browser came out, people were like, "Oh, the web's a toy for kids." I mean, in 1995 the web was a joke, right? So '96, you had online populations growing, so you had structural changes going on around the browser, internet population. And then that replaced other things, direct mail, other business activities that were once analog then went to the web, kind of read only as you, as we always talk about. So I think that's a moment where the hype long term, the smart money, and the smart industry experts all get the long term. And in this case, there's more poo-pooing in the short term. "Ah, it's not a big deal, it's just AI." I've heard many people poo-pooing ChatGPT, and a lot of smart people saying, "No this is next gen, this is different and it's only going to get better." So I think people are estimating a big long game on this one. >> So you're saying it's bifurcated. There's those who say- >> Yes. >> Okay, all right, let's get to the heart of the premise, and possibly the debate for today's episode. Will OpenAI's early entry into the market confer sustainable competitive advantage for the company. And if you look at the history of tech, the technology industry, it's kind of littered with first mover failures. Altair, IBM, Tandy, Commodore, they and Apple even, they were really early in the PC game. They took a backseat to Dell who came in the scene years later with a better business model. Netscape, you were just talking about, was all the rage in Silicon Valley, with the first browser, drove up all the housing prices out here. AltaVista was the first search engine to really, you know, index full text. >> Owned by Dell, I mean DEC. >> Owned by Digital. >> Yeah, Digital Equipment >> Compaq bought it. And of course as an aside, Digital, they wanted to showcase their hardware, right? Their super computer stuff. And then so Friendster and MySpace, they came before Facebook. The iPhone certainly wasn't the first mobile device. So lots of failed examples, but there are some recent successes like AWS and cloud. >> You could say smartphone. So I mean. >> Well I know, and you can, we can parse this so we'll debate it. Now Twitter, you could argue, had first mover advantage. You kind of gave me that one John. Bitcoin and crypto clearly had first mover advantage, and sustaining that. Guys, will OpenAI make it to the list on the right with ChatGPT, what do you think? >> I think categorically as a company, it probably won't, but as a category, I think what they're doing will, so OpenAI as a company, they get funding, there's power dynamics involved. Microsoft put a billion dollars in early on, then they just pony it up. Now they're reporting 10 billion more. So, like, if the browsers, Microsoft had competitive advantage over Netscape, and used monopoly power, and convicted by the Department of Justice for killing Netscape with their monopoly, Netscape should have had won that battle, but Microsoft killed it. In this case, Microsoft's not killing it, they're buying into it. So I think the embrace extend Microsoft power here makes OpenAI vulnerable for that one vendor solution. So the AI as a company might not make the list, but the category of what this is, large language model AI, is probably will be on the right hand side. >> Okay, we're going to come back to the government intervention and maybe do some comparisons, but what are your thoughts on this premise here? That, it will basically set- put forth the premise that it, that ChatGPT, its early entry into the market will not confer competitive advantage to >> For OpenAI. >> To Open- Yeah, do you agree with that? >> I agree with that actually. It, because Google has been at it, and they have been holding back, as John said because of the scrutiny from the Fed, right, so- >> And privacy too. >> And the privacy and the accuracy as well. But I think Sam Altman and the company on those guys, right? They have put this in a hasty way out there, you know, because it makes mistakes, and there are a lot of questions around the, sort of, where the content is coming from. You saw that as your example, it just stole the content, and without your permission, you know? >> Yeah. So as quick this aside- >> And it codes on people's behalf and the, those codes are wrong. So there's a lot of, sort of, false information it's putting out there. So it's a very vulnerable thing to do what Sam Altman- >> So even though it'll get better, others will compete. >> So look, just side note, a term which Reid Hoffman used a little bit. Like he said, it's experimental launch, like, you know, it's- >> It's pretty damn good. >> It is clever because according to Sam- >> It's more than clever. It's good. >> It's awesome, if you haven't used it. I mean you write- you read what it writes and you go, "This thing writes so well, it writes so much better than you." >> The human emotion drives that too. I think that's a big thing. But- >> I Want to add one more- >> Make your last point. >> Last one. Okay. So, but he's still holding back. He's conducting quite a few interviews. If you want to get the gist of it, there's an interview with StrictlyVC interview from yesterday with Sam Altman. Listen to that one it's an eye opening what they want- where they want to take it. But my last one I want to make it on this point is that Satya Nadella yesterday did an interview with Wall Street Journal. I think he was doing- >> You were not impressed. >> I was not impressed because he was pushing it too much. So Sam Altman's holding back so there's less backlash. >> Got 10 billion reasons to push. >> I think he's almost- >> Microsoft just laid off 10000 people. Hey ChatGPT, find me a job. You know like. (group laughs) >> He's overselling it to an extent that I think it will backfire on Microsoft. And he's over promising a lot of stuff right now, I think. I don't know why he's very jittery about all these things. And he did the same thing during Ignite as well. So he said, "Oh, this AI will write code for you and this and that." Like you called him out- >> The hyperbole- >> During your- >> from Satya Nadella, he's got a lot of hyperbole. (group talks over each other) >> All right, Let's, go ahead. >> Well, can I weigh in on the whole- >> Yeah, sure. >> Microsoft thing on whether OpenAI, here's the take on this. I think it's more like the browser moment to me, because I could relate to that experience with ChatG, personally, emotionally, when I saw that, and I remember vividly- >> You mean that aha moment (indistinct). >> Like this is obviously the future. Anything else in the old world is dead, website's going to be everywhere. It was just instant dot connection for me. And a lot of other smart people who saw this. Lot of people by the way, didn't see it. Someone said the web's a toy. At the company I was worked for at the time, Hewlett Packard, they like, they could have been in, they had invented HTML, and so like all this stuff was, like, they just passed, the web was just being passed over. But at that time, the browser got better, more websites came on board. So the structural advantage there was online web usage was growing, online user population. So that was growing exponentially with the rise of the Netscape browser. So OpenAI could stay on the right side of your list as durable, if they leverage the category that they're creating, can get the scale. And if they can get the scale, just like Twitter, that failed so many times that they still hung around. So it was a product that was always successful, right? So I mean, it should have- >> You're right, it was terrible, we kept coming back. >> The fail whale, but it still grew. So OpenAI has that moment. They could do it if Microsoft doesn't meddle too much with too much power as a vendor. They could be the Netscape Navigator, without the anti-competitive behavior of somebody else. So to me, they have the pole position. So they have an opportunity. So if not, if they don't execute, then there's opportunity. There's not a lot of barriers to entry, vis-a-vis say the CapEx of say a cloud company like AWS. You can't replicate that, Many have tried, but I think you can replicate OpenAI. >> And we're going to talk about that. Okay, so real quick, I want to bring in some ETR data. This isn't an ETR heavy segment, only because this so new, you know, they haven't coverage yet, but they do cover AI. So basically what we're seeing here is a slide on the vertical axis's net score, which is a measure of spending momentum, and in the horizontal axis's is presence in the dataset. Think of it as, like, market presence. And in the insert right there, you can see how the dots are plotted, the two columns. And so, but the key point here that we want to make, there's a bunch of companies on the left, is he like, you know, DataRobot and C3 AI and some others, but the big whales, Google, AWS, Microsoft, are really dominant in this market. So that's really the key takeaway that, can we- >> I notice IBM is way low. >> Yeah, IBM's low, and actually bring that back up and you, but then you see Oracle who actually is injecting. So I guess that's the other point is, you're not necessarily going to go buy AI, and you know, build your own AI, you're going to, it's going to be there and, it, Salesforce is going to embed it into its platform, the SaaS companies, and you're going to purchase AI. You're not necessarily going to build it. But some companies obviously are. >> I mean to quote IBM's general manager Rob Thomas, "You can't have AI with IA." information architecture and David Flynn- >> You can't Have AI without IA >> without, you can't have AI without IA. You can't have, if you have an Information Architecture, you then can power AI. Yesterday David Flynn, with Hammersmith, was on our Supercloud. He was pointing out that the relationship of storage, where you store things, also impacts the data and stressablity, and Zhamak from Nextdata, she was pointing out that same thing. So the data problem factors into all this too, Dave. >> So you got the big cloud and internet giants, they're all poised to go after this opportunity. Microsoft is investing up to 10 billion. Google's code red, which was, you know, the headline in the New York Times. Of course Apple is there and several alternatives in the market today. Guys like Chinchilla, Bloom, and there's a company Jasper and several others, and then Lena Khan looms large and the government's around the world, EU, US, China, all taking notice before the market really is coalesced around a single player. You know, John, you mentioned Netscape, they kind of really, the US government was way late to that game. It was kind of game over. And Netscape, I remember Barksdale was like, "Eh, we're going to be selling software in the enterprise anyway." and then, pshew, the company just dissipated. So, but it looks like the US government, especially with Lena Khan, they're changing the definition of antitrust and what the cause is to go after people, and they're really much more aggressive. It's only what, two years ago that (indistinct). >> Yeah, the problem I have with the federal oversight is this, they're always like late to the game, and they're slow to catch up. So in other words, they're working on stuff that should have been solved a year and a half, two years ago around some of the social networks hiding behind some of the rules around open web back in the days, and I think- >> But they're like 15 years late to that. >> Yeah, and now they got this new thing on top of it. So like, I just worry about them getting their fingers. >> But there's only two years, you know, OpenAI. >> No, but the thing (indistinct). >> No, they're still fighting other battles. But the problem with government is that they're going to label Big Tech as like a evil thing like Pharma, it's like smoke- >> You know Lena Khan wants to kill Big Tech, there's no question. >> So I think Big Tech is getting a very seriously bad rap. And I think anything that the government does that shades darkness on tech, is politically motivated in most cases. You can almost look at everything, and my 80 20 rule is in play here. 80% of the government activity around tech is bullshit, it's politically motivated, and the 20% is probably relevant, but off the mark and not organized. >> Well market forces have always been the determining factor of success. The governments, you know, have been pretty much failed. I mean you look at IBM's antitrust, that, what did that do? The market ultimately beat them. You look at Microsoft back in the day, right? Windows 95 was peaking, the government came in. But you know, like you said, they missed the web, right, and >> so they were hanging on- >> There's nobody in government >> to Windows. >> that actually knows- >> And so, you, I think you're right. It's market forces that are going to determine this. But Sarbjeet, what do you make of Microsoft's big bet here, you weren't impressed with with Nadella. How do you think, where are they going to apply it? Is this going to be a Hail Mary for Bing, or is it going to be applied elsewhere? What do you think. >> They are saying that they will, sort of, weave this into their products, office products, productivity and also to write code as well, developer productivity as well. That's a big play for them. But coming back to your antitrust sort of comments, right? I believe the, your comment was like, oh, fed was late 10 years or 15 years earlier, but now they're two years. But things are moving very fast now as compared to they used to move. >> So two years is like 10 Years. >> Yeah, two years is like 10 years. Just want to make that point. (Dave laughs) This thing is going like wildfire. Any new tech which comes in that I think they're going against distribution channels. Lina Khan has commented time and again that the marketplace model is that she wants to have some grip on. Cloud marketplaces are a kind of monopolistic kind of way. >> I don't, I don't see this, I don't see a Chat AI. >> You told me it's not Bing, you had an interesting comment. >> No, no. First of all, this is great from Microsoft. If you're Microsoft- >> Why? >> Because Microsoft doesn't have the AI chops that Google has, right? Google is got so much core competency on how they run their search, how they run their backends, their cloud, even though they don't get a lot of cloud market share in the enterprise, they got a kick ass cloud cause they needed one. >> Totally. >> They've invented SRE. I mean Google's development and engineering chops are off the scales, right? Amazon's got some good chops, but Google's got like 10 times more chops than AWS in my opinion. Cloud's a whole different story. Microsoft gets AI, they get a playbook, they get a product they can render into, the not only Bing, productivity software, helping people write papers, PowerPoint, also don't forget the cloud AI can super help. We had this conversation on our Supercloud event, where AI's going to do a lot of the heavy lifting around understanding observability and managing service meshes, to managing microservices, to turning on and off applications, and or maybe writing code in real time. So there's a plethora of use cases for Microsoft to deploy this. combined with their R and D budgets, they can then turbocharge more research, build on it. So I think this gives them a car in the game, Google may have pole position with AI, but this puts Microsoft right in the game, and they already have a lot of stuff going on. But this just, I mean everything gets lifted up. Security, cloud, productivity suite, everything. >> What's under the hood at Google, and why aren't they talking about it? I mean they got to be freaked out about this. No? Or do they have kind of a magic bullet? >> I think they have the, they have the chops definitely. Magic bullet, I don't know where they are, as compared to the ChatGPT 3 or 4 models. Like they, but if you look at the online sort of activity and the videos put out there from Google folks, Google technology folks, that's account you should look at if you are looking there, they have put all these distinctions what ChatGPT 3 has used, they have been talking about for a while as well. So it's not like it's a secret thing that you cannot replicate. As you said earlier, like in the beginning of this segment, that anybody who has more data and the capacity to process that data, which Google has both, I think they will win this. >> Obviously living in Palo Alto where the Google founders are, and Google's headquarters next town over we have- >> We're so close to them. We have inside information on some of the thinking and that hasn't been reported by any outlet yet. And that is, is that, from what I'm hearing from my sources, is Google has it, they don't want to release it for many reasons. One is it might screw up their search monopoly, one, two, they're worried about the accuracy, 'cause Google will get sued. 'Cause a lot of people are jamming on this ChatGPT as, "Oh it does everything for me." when it's clearly not a hundred percent accurate all the time. >> So Lina Kahn is looming, and so Google's like be careful. >> Yeah so Google's just like, this is the third, could be a third rail. >> But the first thing you said is a concern. >> Well no. >> The disruptive (indistinct) >> What they will do is do a Waymo kind of thing, where they spin out a separate company. >> They're doing that. >> The discussions happening, they're going to spin out the separate company and put it over there, and saying, "This is AI, got search over there, don't touch that search, 'cause that's where all the revenue is." (chuckles) >> So, okay, so that's how they deal with the Clay Christensen dilemma. What's the business model here? I mean it's not advertising, right? Is it to charge you for a query? What, how do you make money at this? >> It's a good question, I mean my thinking is, first of all, it's cool to type stuff in and see a paper get written, or write a blog post, or gimme a marketing slogan for this or that or write some code. I think the API side of the business will be critical. And I think Howie Xu, I know you're going to reference some of his comments yesterday on Supercloud, I think this brings a whole 'nother user interface into technology consumption. I think the business model, not yet clear, but it will probably be some sort of either API and developer environment or just a straight up free consumer product, with some sort of freemium backend thing for business. >> And he was saying too, it's natural language is the way in which you're going to interact with these systems. >> I think it's APIs, it's APIs, APIs, APIs, because these people who are cooking up these models, and it takes a lot of compute power to train these and to, for inference as well. Somebody did the analysis on the how many cents a Google search costs to Google, and how many cents the ChatGPT query costs. It's, you know, 100x or something on that. You can take a look at that. >> A 100x on which side? >> You're saying two orders of magnitude more expensive for ChatGPT >> Much more, yeah. >> Than for Google. >> It's very expensive. >> So Google's got the data, they got the infrastructure and they got, you're saying they got the cost (indistinct) >> No actually it's a simple query as well, but they are trying to put together the answers, and they're going through a lot more data versus index data already, you know. >> Let me clarify, you're saying that Google's version of ChatGPT is more efficient? >> No, I'm, I'm saying Google search results. >> Ah, search results. >> What are used to today, but cheaper. >> But that, does that, is that going to confer advantage to Google's large language (indistinct)? >> It will, because there were deep science (indistinct). >> Google, I don't think Google search is doing a large language model on their search, it's keyword search. You know, what's the weather in Santa Cruz? Or how, what's the weather going to be? Or you know, how do I find this? Now they have done a smart job of doing some things with those queries, auto complete, re direct navigation. But it's, it's not entity. It's not like, "Hey, what's Dave Vellante thinking this week in Breaking Analysis?" ChatGPT might get that, because it'll get your Breaking Analysis, it'll synthesize it. There'll be some, maybe some clips. It'll be like, you know, I mean. >> Well I got to tell you, I asked ChatGPT to, like, I said, I'm going to enter a transcript of a discussion I had with Nir Zuk, the CTO of Palo Alto Networks, And I want you to write a 750 word blog. I never input the transcript. It wrote a 750 word blog. It attributed quotes to him, and it just pulled a bunch of stuff that, and said, okay, here it is. It talked about Supercloud, it defined Supercloud. >> It's made, it makes you- >> Wow, But it was a big lie. It was fraudulent, but still, blew me away. >> Again, vanilla content and non accurate content. So we are going to see a surge of misinformation on steroids, but I call it the vanilla content. Wow, that's just so boring, (indistinct). >> There's so many dangers. >> Make your point, cause we got to, almost out of time. >> Okay, so the consumption, like how do you consume this thing. As humans, we are consuming it and we are, like, getting a nicely, like, surprisingly shocked, you know, wow, that's cool. It's going to increase productivity and all that stuff, right? And on the danger side as well, the bad actors can take hold of it and create fake content and we have the fake sort of intelligence, if you go out there. So that's one thing. The second thing is, we are as humans are consuming this as language. Like we read that, we listen to it, whatever format we consume that is, but the ultimate usage of that will be when the machines can take that output from likes of ChatGPT, and do actions based on that. The robots can work, the robot can paint your house, we were talking about, right? Right now we can't do that. >> Data apps. >> So the data has to be ingested by the machines. It has to be digestible by the machines. And the machines cannot digest unorganized data right now, we will get better on the ingestion side as well. So we are getting better. >> Data, reasoning, insights, and action. >> I like that mall, paint my house. >> So, okay- >> By the way, that means drones that'll come in. Spray painting your house. >> Hey, it wasn't too long ago that robots couldn't climb stairs, as I like to point out. Okay, and of course it's no surprise the venture capitalists are lining up to eat at the trough, as I'd like to say. Let's hear, you'd referenced this earlier, John, let's hear what AI expert Howie Xu said at the Supercloud event, about what it takes to clone ChatGPT. Please, play the clip. >> So one of the VCs actually asked me the other day, right? "Hey, how much money do I need to spend, invest to get a, you know, another shot to the openAI sort of the level." You know, I did a (indistinct) >> Line up. >> A hundred million dollar is the order of magnitude that I came up with, right? You know, not a billion, not 10 million, right? So a hundred- >> Guys a hundred million dollars, that's an astoundingly low figure. What do you make of it? >> I was in an interview with, I was interviewing, I think he said hundred million or so, but in the hundreds of millions, not a billion right? >> You were trying to get him up, you were like "Hundreds of millions." >> Well I think, I- >> He's like, eh, not 10, not a billion. >> Well first of all, Howie Xu's an expert machine learning. He's at Zscaler, he's a machine learning AI guy. But he comes from VMware, he's got his technology pedigrees really off the chart. Great friend of theCUBE and kind of like a CUBE analyst for us. And he's smart. He's right. I think the barriers to entry from a dollar standpoint are lower than say the CapEx required to compete with AWS. Clearly, the CapEx spending to build all the tech for the run a cloud. >> And you don't need a huge sales force. >> And in some case apps too, it's the same thing. But I think it's not that hard. >> But am I right about that? You don't need a huge sales force either. It's, what, you know >> If the product's good, it will sell, this is a new era. The better mouse trap will win. This is the new economics in software, right? So- >> Because you look at the amount of money Lacework, and Snyk, Snowflake, Databrooks. Look at the amount of money they've raised. I mean it's like a billion dollars before they get to IPO or more. 'Cause they need promotion, they need go to market. You don't need (indistinct) >> OpenAI's been working on this for multiple five years plus it's, hasn't, wasn't born yesterday. Took a lot of years to get going. And Sam is depositioning all the success, because he's trying to manage expectations, To your point Sarbjeet, earlier. It's like, yeah, he's trying to "Whoa, whoa, settle down everybody, (Dave laughs) it's not that great." because he doesn't want to fall into that, you know, hero and then get taken down, so. >> It may take a 100 million or 150 or 200 million to train the model. But to, for the inference to, yeah to for the inference machine, It will take a lot more, I believe. >> Give it, so imagine, >> Because- >> Go ahead, sorry. >> Go ahead. But because it consumes a lot more compute cycles and it's certain level of storage and everything, right, which they already have. So I think to compute is different. To frame the model is a different cost. But to run the business is different, because I think 100 million can go into just fighting the Fed. >> Well there's a flywheel too. >> Oh that's (indistinct) >> (indistinct) >> We are running the business, right? >> It's an interesting number, but it's also kind of, like, context to it. So here, a hundred million spend it, you get there, but you got to factor in the fact that the ways companies win these days is critical mass scale, hitting a flywheel. If they can keep that flywheel of the value that they got going on and get better, you can almost imagine a marketplace where, hey, we have proprietary data, we're SiliconANGLE in theCUBE. We have proprietary content, CUBE videos, transcripts. Well wouldn't it be great if someone in a marketplace could sell a module for us, right? We buy that, Amazon's thing and things like that. So if they can get a marketplace going where you can apply to data sets that may be proprietary, you can start to see this become bigger. And so I think the key barriers to entry is going to be success. I'll give you an example, Reddit. Reddit is successful and it's hard to copy, not because of the software. >> They built the moat. >> Because you can, buy Reddit open source software and try To compete. >> They built the moat with their community. >> Their community, their scale, their user expectation. Twitter, we referenced earlier, that thing should have gone under the first two years, but there was such a great emotional product. People would tolerate the fail whale. And then, you know, well that was a whole 'nother thing. >> Then a plane landed in (John laughs) the Hudson and it was over. >> I think verticals, a lot of verticals will build applications using these models like for lawyers, for doctors, for scientists, for content creators, for- >> So you'll have many hundreds of millions of dollars investments that are going to be seeping out. If, all right, we got to wrap, if you had to put odds on it that that OpenAI is going to be the leader, maybe not a winner take all leader, but like you look at like Amazon and cloud, they're not winner take all, these aren't necessarily winner take all markets. It's not necessarily a zero sum game, but let's call it winner take most. What odds would you give that open AI 10 years from now will be in that position. >> If I'm 0 to 10 kind of thing? >> Yeah, it's like horse race, 3 to 1, 2 to 1, even money, 10 to 1, 50 to 1. >> Maybe 2 to 1, >> 2 to 1, that's pretty low odds. That's basically saying they're the favorite, they're the front runner. Would you agree with that? >> I'd say 4 to 1. >> Yeah, I was going to say I'm like a 5 to 1, 7 to 1 type of person, 'cause I'm a skeptic with, you know, there's so much competition, but- >> I think they're definitely the leader. I mean you got to say, I mean. >> Oh there's no question. There's no question about it. >> The question is can they execute? >> They're not Friendster, is what you're saying. >> They're not Friendster and they're more like Twitter and Reddit where they have momentum. If they can execute on the product side, and if they don't stumble on that, they will continue to have the lead. >> If they say stay neutral, as Sam is, has been saying, that, hey, Microsoft is one of our partners, if you look at their company model, how they have structured the company, then they're going to pay back to the investors, like Microsoft is the biggest one, up to certain, like by certain number of years, they're going to pay back from all the money they make, and after that, they're going to give the money back to the public, to the, I don't know who they give it to, like non-profit or something. (indistinct) >> Okay, the odds are dropping. (group talks over each other) That's a good point though >> Actually they might have done that to fend off the criticism of this. But it's really interesting to see the model they have adopted. >> The wildcard in all this, My last word on this is that, if there's a developer shift in how developers and data can come together again, we have conferences around the future of data, Supercloud and meshs versus, you know, how the data world, coding with data, how that evolves will also dictate, 'cause a wild card could be a shift in the landscape around how developers are using either machine learning or AI like techniques to code into their apps, so. >> That's fantastic insight. I can't thank you enough for your time, on the heels of Supercloud 2, really appreciate it. All right, thanks to John and Sarbjeet for the outstanding conversation today. Special thanks to the Palo Alto studio team. My goodness, Anderson, this great backdrop. You guys got it all out here, I'm jealous. And Noah, really appreciate it, Chuck, Andrew Frick and Cameron, Andrew Frick switching, Cameron on the video lake, great job. And Alex Myerson, he's on production, manages the podcast for us, Ken Schiffman as well. Kristen Martin and Cheryl Knight help get the word out on social media and our newsletters. Rob Hof is our editor-in-chief over at SiliconANGLE, does some great editing, thanks to all. Remember, all these episodes are available as podcasts. All you got to do is search Breaking Analysis podcast, wherever you listen. Publish each week on wikibon.com and siliconangle.com. Want to get in touch, email me directly, david.vellante@siliconangle.com or DM me at dvellante, or comment on our LinkedIn post. And by all means, check out etr.ai. They got really great survey data in the enterprise tech business. This is Dave Vellante for theCUBE Insights powered by ETR. Thanks for watching, We'll see you next time on Breaking Analysis. (electronic music)

(upbeat music) >> Welcome back to San Francisco, "theCUBE" is live, our day two coverage of VMware Explore 2022 continues. Lisa Martin with Dave Nicholson. Dave and I are pleased to welcome Jason Collier, principal member of technical staff at AMD to the program. Jason, it's great to have you. >> Thank you, it's great to be here. >> So what's going on at AMD? I hear you have some juicy stuff to talk about. >> Oh, we've got a ton of juicy stuff to talk about. Clearly the Project Monterey announcement was big for us, so we've got that to talk about. Another thing that I really wanted to talk about was a tool that we created and we call it, it's the VMware Architecture Migration Tool, call it VAMT for short. It's a tool that we created and we worked together with VMware and some of their professional services crew to actually develop this tool. And it is also an open source based tool. And really the primary purpose is to easily enable you to move from one CPU architecture to another CPU architecture, and do that in a cold migration fashion. >> So we're probably not talking about CPUs from Tandy, Radio Shack systems, likely this would be what we might refer to as other X86 systems. >> Other X86 systems is a good way to refer to it. >> So it's interesting timing for the development and the release of a tool like this, because in this sort of X86 universe, there are players who have been delayed in terms of delivering their next gen stuff. My understanding is AMD has been public with the idea that they're on track for by the end of the year, Genoa, next gen architecture. So can you imagine a situation where someone has an existing set of infrastructure and they're like, hey, you know what I want to get on board, the AMD train, is this something they can use from the VMware environment? >> Absolutely, and when you think about- >> Tell us exactly what that would look like, walk us through 100 servers, VMware, 1000 VMs, just to make the math easy. What do you do? How does it work? >> So one, there's several things that the tool can do, we actually went through, the design process was quite extensive on this. And we went through all of the planning phases that you need to go through to do these VM migrations. Now this has to be a cold migration, it's not a live migration. You can't do that between the CPU architectures. But what we do is you create a list of all of the virtual machines that you want to migrate. So we take this CSV file, we import this CSV file, and we ask for things like, okay, what's the name? Where do you want to migrate it to? So from one cluster to another, what do you want to migrate it to? What are the networks that you want to move it to? And then the storage platform. So we can move storage, it could either be shared storage, or we could move say from VSAN to VSAN, however you want to set it up. So it will do those storage migrations as well. And then what happens is it's actually going to go through, it's going to shut down the VM, it's going to take a snapshot, it is going to then basically move the compute and/or storage resources over. And once it does that, it's going to power 'em back up. And it's going to check, we've got some validation tools, where it's going to make sure VM Tools comes back up where everything is copacetic, it didn't blue screen or anything like that. And once it comes back up, then everything's good, it moves onto the next one. Now a couple of things that we've got feature wise, we built into it. You can parallelize these tasks. So you can say, how many of these machines do you want to do at any given time? So it could be, say 10 machines, 50 machines, 100 machines at a time, that you want to go through and do this move. Now, if it did blue screen, it will actually roll it back to that snapshot on the origin cluster. So that there is some protection on that. A couple other things that are actually in there are things like audit tracking. So we do full audit logging on this stuff, we take a snapshot, there's basically kind of an audit trail of what happens. There's also full logging, SYS logging, and then also we'll do email reporting. So you can say, run this and then shoot me a report when this is over. Now, one other cool thing is you can also actually define a change window. So I don't want to do this in the middle of the afternoon on a Tuesday. So I want to do this later at night, over the weekend, you can actually just queue this up, set it, schedule it, it'll run. You can also define how long you want that change window to be. And what it'll do, it'll do as many as it can, then it'll effectively stop, finish up, clean up the tasks and then send you a report on what all was successfully moved. >> Okay, I'm going to go down the rabbit hole a little bit on this, 'cause I think it's important. And if I say something incorrect, you correct me. >> No problem. >> In terms of my technical understanding. >> I got you. >> So you've got a VM, essentially a virtual machine typically will consist of an entire operating system within that virtual machine. So there's a construct that containerizes, if you will, the operating system, what is the difference, where is the difference in the instruction set? Where does it lie? Is it in the OS' interaction with the CPU or is it between the construct that is the sort of wrapper around the VM that is the difference? >> It's really primarily the OS, right? And we've not really had too many issues doing this and most of the time, what is going to happen, that OS is going to boot up, it's going to recognize the architecture that it's on, it's going to see the underlying architecture, and boot up. All the major operating systems that we test worked fine. I mean, typically they're going to work on all the X86 platforms. But there might be instruction sets that are kind of enabled in one architecture that may not be in another architecture. >> And you're looking for that during this process. >> Well usually the OS itself is going to kind of detect that. So if it pops up, the one thing that is kind of a caution that you need to look for. If you've got an application that's explicitly using an instruction set that's on one CPU vendor and not the other CPU vendor. That's the one thing where you're probably going to see some application differences. That said, it'll probably be compatible, but you may not get that instruction set advantage in it. >> But this tool remediates against that. >> Yeah, and what we do, we're actually using VM Tools itself to go through and validate a lot of those components. So we'll look and make sure VM Tools is enabled in the first place, on the source system. And then when it gets to the destination system, we also look at VM Tools to see what is and what is not enabled. >> Okay, I'm going to put you on the spot here. What's the zinger, where doesn't it work? You already said cold, we understand, you can schedule for cold migrations, that's not a zinger. What's the zinger, where doesn't it work? >> It doesn't work like, live migrations just don't work. >> No live, okay, okay, no live. What about something else? What's the oh, you've got that version, you've got that version of X86 architecture, it-won't work, anything? >> A majority of those cases work, where it would fail, where it's going to kick back and say, hey, VM Tools is not installed. So where you would see this is if you're running a virtual appliance from some vendor, like insert vendor here that say, got a firewall, or got something like that, and they don't have VM Tools enabled. It's going to fail it out of the gate, and say, hey, VM Tools is not on this, you might want to manually do it. >> But you can figure out how to fix that? >> You can figure out how to do that. You can also, and there's a flag in there, so in kind of the options that you give it, you say, ignore VM Tools, don't care, move it anyway. So if you've got less, some VMs that are in there, but they're not a priority VM, then it's going to migrate just fine. >> Got It. >> Can you elaborate a little bit on the joint development work that AMD and VMware are doing together and the value in it for customers? >> Yeah, so it's one of those things we worked with VMware to basically produce this open source tool. So we did a lot of the core component and design and we actually engaged VMware Professional Services. And a big shout out to Austin Browder. He helped us a ton in this project specifically. And we basically worked, we created this, kind of co-designed, what it was going to look like. And then jointly worked together on the coding, of pulling this thing together. And then after that, and this is actually posted up on VMware's public repos now in GitHub. So you can go to GitHub, you can go to the VMware samples code, and you can download this thing that we've created. And it's really built to help ease migrations from one architecture to another. So if you're looking for a big data center move and you got a bunch of VMs to move. I mean, even if it's same architecture to same architecture, it's definitely going to ease the pain of going through and doing a migration of, it's one thing when you're doing 10 machines, but when you're doing 10,000 virtual machines, that's a different story. It gets to be quite operationally inefficient. >> I lose track after three. >> Yeah. >> So I'm good for three, not four. >> I was going to ask you what your target market segment is here. Expand on that a little bit and talk to me about who you're working with and those organizations. >> So really this is targeted toward organizations that have large deployments in enterprise, but also I think this is a big play with channel partners as well. So folks out there in the channel that are doing these migrations and they do a lot of these, when you're thinking about the small and mid-size organizations, it's a great fit for that. Especially if they're kind of doing that upgrade, the lift and shift upgrade, from here's where you've been five to seven years on an architecture and you want to move to a new architecture. This is really going to help. And this is not a point and click GUI kind of thing. It's command line driven, it's using PowerShell, we're using PowerCLI to do the majority of this work. And for channel partners, this is an excellent opportunity to put the value and the value add and VAR, And there's a lot of opportunity for, I think, channel partners to really go and take this. And once again, being open source. We expect this to be extensible, we want the community to contribute and put back into this to basically help grow it and make it a more useful tool for doing these cold migrations between CPU architectures. >> Have you seen any in the last couple of years of dynamics, obviously across the world, any industries in particular that are really leading edge for what you guys are doing? >> Yeah, that's really, really interesting. I mean, we've seen it, it's honestly been a very horizontal problem, pretty much across all vertical markets. I mean, we've seen it in financial services, we've seen it in, honestly, pretty much across the board. Manufacturing, financial services, healthcare, we have seen kind of a strong interest in that. And then also we we've actually taken this and presented this to some of our channel partners as well. And there's been a lot of interest in it. I think we presented it to about 30 different channel partners, a couple of weeks back about this. And I got contact from 30 different channel partners that said they're interested in basically helping us work on it. >> Tagging on to Lisa's question, do you have visibility into the AMD thought process around the timing of your next gen release versus others that are competitors in the marketplace? How you might leverage that in terms of programs where partners are going out and saying, hey, perfect time, you need a refresh, perfect time to look at AMD, if you haven't looked at them recently. Do you have any insight into that in what's going on? I know you're focused on this area. But what are your thoughts on, well, what's the buzz? What's the buzz inside AMD on that? >> Well, when you look overall, if you look at the Gartner Hype Cycle, when VMware was being broadly adopted, when VMware was being broadly adopted, I'm going to be blunt, and I'm going to be honest right here, AMD didn't have a horse in the race. And the majority of those VMware deployments we see are not running on AMD. Now that said, there's an extreme interest in the fact that we've got these very cored in systems that are now coming up on, now you're at that five to seven year refresh window of pulling in new hardware. And we have extremely attractive hardware when it comes to running virtualized workloads. The test cluster that I'm running at home, I've got that five to seven year old gear, and I've got some of the, even just the Milan systems that we've got. And I've got three nodes of another architecture going onto AMD. And when I got these three nodes completely maxed to the number of VMs that I can run on 'em, I'm at a quarter of the capacity of what I'm putting on the new stuff. So what you get is, I mean, we worked the numbers, and it's definitely, it's like a 30% decrease in the amount of resources that you need. >> That's a compelling number. >> It's a compelling number. >> 5%, 10%, nobody's going to do anything for that. You talk 30%. >> 30%. It's meaningful, it's meaningful. Now you you're out of Austin, right? >> Yes. >> So first thing I thought of when you talk about running clusters in your home is the cost of electricity, but you're okay. >> I'm okay. >> You don't live here, you don't live here, you don't need to worry about that. >> I'm okay. >> Do you have a favorite customer example that you think really articulates the value of AMD when you're in customer conversations and they go, why AMD and you hit back with this? >> Yeah. Actually it's funny because I had a conversation like that last night, kind of random person I met later on in the evening. We were going through this discussion and they were facing exactly this problem. They had that five to seven year infrastructure. It's funny, because the guy was a gamer too, and he's like, man, I've always been a big AMD fan, I love the CPUs all the way since back in basically the Opterons and Athlons right. He's like, I've always loved the AMD systems, loved the graphics cards. And now with what we're doing with Ryzen and all that stuff. He's always been a big AMD fan. He's like, and I'm going through doing my infrastructure refresh. And I told him, I'm just like, well, hey, talk to your VAR and have 'em plug some AMD SKUs in there from the Dells, HPs and Lenovos. And then we've got this tool to basically help make that migration easier on you. And so once we had that discussion and it was great, then he swung by the booth today and I was able to just go over, hey, this is the tool, this is how you use it, here's all the info. Call me if you need any help. >> Yeah, when we were talking earlier, we learned that you were at Scale. So what are you liking about AMD? How does that relate? >> The funny thing is this is actually the first time in my career that I've actually had a job where I didn't work for myself. I've been doing venture backed startups the last 25 years and we've raised couple hundred million dollars worth of investment over the years. And so one, I figured, here I am going to AMD, a larger corporation. I'm just like, am I going to be able to make it a year? And I have been here longer than a year and I absolutely love it. The culture at AMD is amazing. We still have that really, I mean, almost it's like that underdog mentality within the organization. And the team that I'm working with is a phenomenal team. And it's actually, our EVP and our Corp VP, were actually my executive sponsors, we were at a prior company. They were one of my executive sponsors when I was at Scale. And so my now VP boss calls me up and says, hey, I'm putting a band together, are you interested? And I was kind of enjoying a semi-retirement lifestyle. And then I'm just like, man, because it's you, yes, I am interested. And the group that we're in, the work that we're doing, the way that we're really focusing on forward looking things that are affecting the data center, what's going to be the data center like three to five years from now. It's exciting, and I am having a blast, I'm having the time of my life. I absolutely love it. >> Well, that relationship and the trust that you will have with each other, that bleeds into the customer conversations, the partner conversations, the employee conversations, it's all inextricably linked. >> Yes it is. >> And we want to know, you said three to five years out, like what? Like what? Just general futurist stuff, where do you think this is going. >> Well, it's interesting. >> So moon collides with the earth in 2025, we already know that. >> So we dialed this back to the Pensando acquisition. When you look at the Pensando acquisition and you look at basically where data centers are today, but then you look at where basically the big hyperscalers are. You look at an AWS, you look at their architecture, you specifically wrap Nitro around that, that's a very different architecture than what's being run in the data center. And when you look at what Pensando does, that's a lot of starting to bring what these real clouds out there, what these big hyperscalers are running into the grasps of the data center. And so I think you're going to see a fundamental shift. The next 10 years are going to be exciting because the way you look at a data center now, when you think of what CPUs do, what shared storage, how the networking is all set up, it ain't going to look the same. >> Okay, so the competing vision with that, to play devil's advocate, would be DPUs are kind of expensive. Why don't we just use NICs, give 'em some more bandwidth, and use the cheapest stuff. That's the competing vision. >> That could be. >> Or the alternative vision, and I imagine everything else we've experienced in our careers, they will run in parallel paths, fit for function. >> Well, parallel paths always exist, right? Otherwise, 'cause you know how many times you've heard mainframe's dead, tape's dead, spinning disk is dead. None of 'em dead, right? The reality is you get to a point within an industry where it basically goes from instead of a growth curve like that, it goes to a growth curve of like that, it's pretty flat. So from a revenue growth perspective, I don't think you're going to see the revenue growth there. I think you're going to see the revenue growth in DPUs. And when you actually take, they may be expensive now, but you look at what Monterey's doing and you look at the way that those DPUs are getting integrated in at the OEM level. It's going to be a part of it. You're going to order your VxRail and VSAN style boxes, they're going to come with them. It's going to be an integrated component. Because when you start to offload things off the CPU, you've driven your overall utilization up. When you don't have to process NSX on basically the X86, you've just freed up cores and a considerable amount of them. And you've also moved that to where there's a more intelligent place for that pack to be processed right, out here on this edge. 'Cause you know what, that might not need to go into the host bus at all. So you have just alleviated any transfers over a PCI bus, over the PCI lanes, into DRAM, all of these components, when you're like, but all to come with, oh, that bit needs to be on this other machine. So now it's coming in and it's making that decision there. And then you take and integrate that into things like the Aruba Smart Switch, that's running the Pensando technology. So now you got top of rack that is already making those intelligent routing decisions on where packets really need to go. >> Jason, thank you so much for joining us. I know you guys could keep talking. >> No, I was going to say, you're going to have to come back. You're going to have to come back. >> We've just started to peel the layers of the onion, but we really appreciate you coming by the show, talking about what AMD and VMware are doing, what you're enabling customers to achieve. Sounds like there's a lot of tailwind behind you. That's awesome. >> Yeah. >> Great stuff, thank you. >> It's a great time to be at AMD, I can tell you that. >> Oh, that's good to hear, we like it. Well, thank you again for joining us, we appreciate it. For our guest and Dave Nicholson, I'm Lisa Martin. You're watching "theCUBE Live" from San Francisco, VMware Explore 2022. We'll be back with our next guest in just a minute. (upbeat music)

>> Narrator: Live, from Washington DC, it's theCUBE. Covering AWS Public Sector Summit. Brought to you by Amazon Web Services. >> Welcome back everyone to theCUBE's live coverage of the AWS Public Sector Summit here in our nation's capital. I'm your host, Rebecca Knight. Co-hosting along side John Furrier. We are joined by Jamil Jaffer, he is the VP Strategy and Partnerships at IronNet. Thanks so much for coming on theCUBE. >> Thanks for having me Rebecca. >> Rebecca: I know you've been watching us for a long time so here you are, soon to be a CUBE alumn. >> I've always wanted to be in theCUBE, it's like being in the octagon but for computer journalists. (laughing) I'm pumped about it. >> I love it. Okay, why don't you start by telling our viewers a little bit about IronNet and about what you do there. >> Sure, so IronNet was started about 4 1/2 years ago, 5 years ago, by General Kieth Alexander, the former director of the NSA and founding commander of US Cyber command. And essentially what we do is, we do network traffic analytics and collective defense. Now I think a lot of people know what network traffic analytics are, you're looking for behavioral anomalies and network traffic, trying to identify the bad from the good. Getting past all the false positives, all the big data. What's really cool about what we do is collective defense. It's this idea that one company standing alone can't defend itself, it's got to work with multiple companies, it's got to work across industry sectors. Potentially even with the governments, and potentially across allied governments, really defending one another. And the way that works, the way we think about that, is we share all the anomalies we see across multiple companies to identify threat trends and correlations amongst that data, so you can find things before they happen to you. And so the really cool idea here is, that something may not happen to you, but it may happen to your colleague, you find about it, you're defended against it. And it takes a real commitment by our partners, our companies that we work with, to do this, but increasingly they're realizing the threat is so large, they have no choice but to work together, and we provide that platform that allows that to happen. >> And the premise is that sharing the data gives more observational space to have insights into that offense, correct? >> That's exactly right. It's as though, it's almost like you think about an air traffic control picture, or a radar picture, right? The idea being that if you want to know what's happening in the air space, you got to see all of it in real time at machine speed, and that allows you to get ahead of the threats rather than being reactive and talking about instant response, we're talking about getting ahead of the problems before they happen so you can stop them and prevent the damage ahead of time. >> So you're an expert, they're lucky to have you. Talk about what you've been doing before this. Obviously a lot of experience in security. Talk about some about some of the things you've done in the past. >> So I have to admit to being a recovering lawyer, but you have to forgive me because I did grow up with computers. I had a Tandy TRS-80 Color computer when I first started. 4K of all more RAM, we upgraded to 16K, it was the talk of the rainbow computer club, what are you doing, 16K of RAM? (laughing) I mean, it was-- >> Basic programming language, >> That's right. (laughing) Stored on cassette tapes. I remember when you used to have to punch a hole in the other side of a 5 1/4 floppy disc to make it double sided. >> Right, right. >> John: Glory days. >> Yeah, yeah. I paid my way through college running a network cable, but I'm a recovering lawyer, and so my job in the government, I worked at the House Intelligence Committee, the Senate Foreign Relations Committee and then the Bush administration on the Comprehensive National Cybersecurity Initiative, both the Justice Department and the White House. >> You've seen the arc, you've seen the trajectory, the progress we're making now seems to me slower than it should be, obviously a lot of inertia as Amy Chasity said today about these public sector government agencies, what not. But a real focus has been on it, we've been seeing activity. Where are we with the state of the union around the modernization of cyber and awareness to what's happening? How critical are people taking this threat seriously? >> Well I think I variety of things to say on that front. First, the government itself needs modernize its systems, right? We've seen that talked about in the Obama administration, we've seen President Trump put out an executive order on modernization of federal infrastructure. The need to move to the cloud, the need to move to shared services, make them more defensible, more resilient long-term. That's the right move. We've seen efforts at the Department of Defense and elsewhere. They aren't going as fast as the need to, more needs to happen on that front. IT modernization can really be accelerated by shifting to the cloud, and that's part of why that one of the things that IronNet's done really aggressively is make a move into the cloud space, putting all of our back end in the cloud and AWS. And also, ability, capability to do surveillance and monitoring. When I say surveillance I mean network threat detection not surveillance of the old kind. But network threat detection in the cloud, and in cloud-enabled instances too. So both are important, right? Classic data centers, but also in modern cloud infrastructure. >> Yeah, one of the things people want to know about is what your enemy looks like, and now with the democratization with open source, and democratization of tools, the enemies could be hiding through obscure groups. The states, the bad actors and the state actors can actually run covert activities through other groups, so this is kind of a dynamic that creates confusion. >> No, in fact, it's their actual mode of operating, right? It's exactly what they do, they use proxies, right? So you'll see the Russians operating, looking like a criminal hacker group operating out of the eastern Europe. In part because a lot of those Russian criminal rings, in actuality. You see a lot of patriotic hackers, right? I would tell most people, if you see a patriotic hacker there's probably a government behind that whole operation. And so the question becomes, how do you confront that threat, right? A lot of people say deterrence doesn't work in cyberspace. I don't believe that. I think deterrence can and does work in cyberspace, we just don't practice it. We don't talk about our capabilities, we don't talk our red lines, we don't talk about what'll happen if you cross our red lines, and when we do establish red lines and they're crossed, we don't really enforce them. So it's no surprise that our enemies, or advisories, are hitting us in cyberspace, are testing our boundaries. It's cause we haven't really give them a sense of where those lines are and what we're going to do if they cross them. >> Are we making an progress on doing anything here? What's the state of the market there? >> Well the government appears to have gotten more aggressive, right? We've seen efforts in congress to give the Department of Defense and the US Intelligence Committee more authorities. You can see the stand up of US Cyber Command. And we've seen more of a public discussion of these issues, right? So that's happening. Now, is it working? That's a harder question to know. But the real hard question is, what do you do on private sector defense? Because our tradition has been, in this country, that if it's a nation-state threat, the government defends you against it. We don't expect Target or Walmart or Amazon to have service to air missiles on the roof of your buildings to defend against Russian Bear bombers. We expect the government to do that. But in cyberspace, the idea's flipped on its head. We expect Amazon and every company in America, from a mom and pop shop, all the way up to the big players, to defend themselves against script kiddies, criminal hacker gangs, and nation-states. >> John: And randomware's been taking down cities, Baltimore, recent example, >> Exactly. >> John: multiple times. Hit that well many times. >> That's right, that's right. >> Talk about where the US compares. I mean, here as you said, the US, we are starting to have these conversations, there's more of an awareness of these cyber threats. But modernization has been slow, it does not quite have the momentum. How do we rate with other countries? >> Well I think in a lot of ways we have the best capabilities when it comes to identifying threats, identifying the adversary, the enemy, and taking action to respond, right? If we're not the top one, we're in the top two or three, right? And the question, though, becomes one of, how do you work with industry to help industry become that good? Now our industry is at the top of that game also, but when you're talking about a nation-state, which has virtually unlimited resources, virtually unlimited man-power to throw at a problem, it's not realistic to expect a single company to defend itself, and at the same time, we as a nation are prepared to say, "Oh, the Department of Defense should be sitting on "the boundaries of the US internet." As if you could identify them even, right? And we don't want that. So the question becomes, how does the government empower the private sector to do better defense for itself? What can the government do working with industry, and how can industry work with one another, to defend each other? We really got to do collective defense, not because it makes sense, which it does, but because there is no other option if you're going to confront nation-state or nation-state enabled actors. And that's another threat, we've seen the leakage of nation-state capabilities out to a lot broader of an audience now. That's a problem, even though that may be 2013 called and wants it's hack back, those things still work, right? What we saw in Baltimore was stuff that has been known for a long time. Microsoft has released patches long ago for that, and yet, still vulnerable. >> And the evolution of just cyber essential command, and Cyber Command, seems to be going slow, at least from my frame. Maybe I'm not in the know, but what is the imperative? I mean, there's a lot of problems to solve. How does the public sector, how does the government, solve these problems? Is cloud the answer? What are some of the things that people of this, the top minds, discussing? >> Well and I think cloud is clearly one part of the solution, right? There's no question that when you move to a cloud infrastructure, you have sort of a more bounded perimeter, right? And that provides that ability to also rapidly update, you could update systems in real time, and in mass. There's not going around and bringing your floppy disc and loading software, and it sounds like that's sort of a joke about an older era, but you look at what happened with NotPetya and you read this great Wired article about what happened with NotPetya, and you look at Maersk. And the way that Maersk brought its systems back up, was they had domain controller in Africa that had gone down due to a power surge, where they were able to recover the physical hard drive and re-image all their world-wide domain controls off of that one hard drive. You think about a major company that runs a huge percentage of the world's ports, right? And this is how they recovered, right? So we really are in that, take your disc and go to computers. In a cloud infrastructure you think about how you can do that in real time, or rapidly refresh, rapidly install patches, so there's a lot of that, that's like a huge part of it. It's not a complete solution, but it's an important part. >> Yeah, one of the things we talk about, a lot of tech guys, is that this debate's around complexity, versus simplicity. So if you store your data in one spot, it's easy to audit and better for governing compliance, but yet easier for hackers to penetrate. From an IQ standpoint, the more complex it is, distributed, harder. >> Yeah I think that's right. >> John: But what's the trade off there? How are people thinking about that kind of direction? >> No that's a great question, right? There's a lot of benefits to diversity of systems, there's a lot of benefit to spreading out your crown jewels, the heart of your enterprise. At the same time, there's real resilience in putting it in one place, having it well defended. Particularly when it's a shared responsibility and you have partial responsibility for the defense, but the provider to, I mean, Amazon, and all the other cloud providers, Microsoft and Google, all have it in their own self interest to really defend their cloud really well. Because whether or not you call it shared responsibility, it's your stock price that matters if you get hit, right? And so, instead of you, Amazon, and all the other cloud players have an incentive to do the right thing and do it really well. And so this shared responsibility can work to both side's benefits. That being said, there's an ongoing debate. A lot of folks want to do there stuff on-prem in a lot of ways. You know, a lot of us are old school, right? When you touch it, you feel it, you know it's there. And we're working through that conversation with folks, and I think that at the end of the day, the real efficiency gains and the power of having super computing power at your fingertips for analytics, for consumer purposes and the like. I really think there's no way to avoid moving to a cloud infrastructure in the long run. >> I know you said you were a recovering lawyer, but you are the founding director of the National Security Institute at the Antonin Scalia School of Law. How are you thinking about educating the next generation of lawyers who could indeed become policy makers or at least work on these committees, to think about these threats that we don't even know about yet? >> That's a great question. So one of the things we're doing, is we're working through the process with the state commission on establishing a new LLM and cyber intelligence national security law. That'll be a great opportunity for lawyers to actually get an advanced degree in these issues. But we're also training non-lawyers. One of the interesting things is, you know, One of the challenges DC has, is we make a lot of tech policy, a lot of it not great, because it's not informed by technologists, so we've got a great partnership with the Hewlett Foundation where we're bringing technologists from around the country, mid-career folks, anywhere from the age of 24 to 38. We're bringing them to DC and we're educating them on how to talk to policy makers. These are technologists, these are coders, data scientists, all the like, and it's a real opportunity for them to be able to be influential in the process of making laws, and know how to involve themselves and talk that speak. Cause, DC speak is a certain thing, right? (laughing) And it's not typically consistent with tech speak, so we're trying to bridge that gap and the Hewlett Foundation's been a great partner in that effort. >> On that point about this collaboration, Silicon Valley's been taking a lot of heat lately, obviously Zuckerberg and Facebook in the news again today, more issues around irresponsibility, but they were growing a rocket ship, I mean, company's only 15 years old roughly. So the impact's been significant, but tech has moved so fast. Tech companies usually hire policy folks in DC to speak the language, educate, a little bit different playbook. But now it's a forcing function between two worlds colliding. You got Washington DC, the Silicon Valley cultures have to blend now. What are some of the top minds thinking about this? What are some of the discussions happening? What's the topic of conversations? >> Well look, I mean, you've see it in the press, it's no surprise you're hearing this talk about breaking up big tech companies. I mean, it's astounding. We used to live in world in which being successful was the American way, right? And now, it seems like at least, without any evidence of anti-trust concerns, that we're talking about breaking up companies that have otherwise hugely successful, wildly innovative. It's sort of interesting to hear that conversation, it's not just one party, you're hearing this in a bipartisan fashion. And so it's a concern, and I think what it reveals to tech companies is, man, we haven't be paying a lot of attention to these guys in DC and they can cause real trouble. We need to get over there and starting talking to these folks and educating them on what we do. >> And the imperative for them is to do the right thing, because, I mean, the United States interest, breaking up, say, Facebook, and Google, and Apple, and Amazon, might look good on paper but China's not breaking up Alibaba anytime soon. >> To the contrary. They're giving them low-interest loans and helping them all to excel. It's crazy. >> Yeah, and they have no R&D by the way, so that's been- >> Jamil: Right, because they stole all of our IP. >> So the US invests in R&D that is easily moving out through theft, that's one issue. You have digital troops on our shores from foreign nations, some will argue, I would say yes. >> Jamil: Inside the border. >> Inside the border, inside the interior, with access to the power grids, our critical infrastructure, this is happening now. So is the government now aware of the bigger picture around what we have as capabilities and criticalities that were needed now for digital military? What is that conversation like? >> Well I think they're having this conversation, right? I think the government knows it's a problem, they know that actually in a lot of ways a partnership with tech is better than an adversary relationship. That doesn't change the fact that, for some reason, in the last three, four years, we really have seen what some people are calling a "techlash", right? A backlash against technology. It kind of strikes me as odd, because of course, the modern economy that we've so benefited from is literally built on the back of the innovations coming out of the Silicon Valley, out of the west coast, and out of the DC metro area, where a lot these tech companies are developing some of the most innovative new ideas. Now they're, frankly, helping government innovate. So Amazon's a key part of that effort, right? Here in the public sector. And so I'm hoping that education will help, I know that the arrival of tech companies here to really have that conversation in an open and sensible way, I hope will sort of waft back some of this. But I worry that for too long the tech and the policies have ignored on another. And now they're starting to intersect as you say, and it has the possibility of going wrong fast, and I'm hoping that doesn't happen. >> You know, one of the things that Rebecca and I were talking about was this talent gap between public sector and private sector. These agencies aren't going to go public anytime soon, so maybe they should get equity deals and get a financial incentive. (laughing) You know what I mean? Shrink down the cost, increase the value. But as you get the collaboration between the two parties, the cloud is attracting smart people, because it gives you an accelerant of value. So people can see some entry points to land, some value out of the gate, verus giving up and abandoning it through red tape, or in other processes. So you starting to see smart people get attracted to cloud as a tool for making change. How is that working? And how is that going to work? Cause this could be coming to the partnership side of it. People might not want to work for the government, but could work with the government. This is a dynamic that we see as real. What's your thoughts? >> I think that's exactly right. Having these cloud infrastructures gives the ability to one, leverage huge amounts of computing power, but also to leverage insights and knowledge from the private sector in ways that you never could have imagined. So I really do think the cloud is an opportunity to bring real benefits from private sector innovation into the public sector very rapidly, right? So, broad-clouded option. And that's part of why John Alexander, my boss, and I have been talking a lot about the need for broad-clouded option. It's not just innovative in technology, it's benefits to the war fighter, Right? I mean, these are real, tangible benefits pushing data in real time, the war fighter, You know John Alexander had one of the biggest innovations in modern war fighting, where he's able to take civil intelligence down from weeks and months, down to minutes and seconds, that the naval and our war fighters in Iraq and Afghanistan to really take the fight to the enemy. The cloud brings that power scaled up to a huge degree, right? By orders of magnitude. And so the government recognizes this and yet today we don't see them yet moving rapidly in that direction. So I think the EO was a good move, a good first step in that direction, now we got to see it implemented by the various agencies down below. >> Well we'll kep in touch, great to have you on. I know we're wrapping up the day here, they're breaking down, we're going to pull the plug literally. (laughing) We'll keep in touch and we'll keep progress on you. >> Thank you so much, I appreciate it. >> Rebecca: Jamil, you are now a CUBE alumn, >> I love it, thank you. >> Rebecca: So congrats, you've joined the club. >> I love it. >> I'm Rebecca Knight for John Furrier you have been watching theCUBE's live coverage of the AWS Public Sector Summit. (electronic music)

>> live from Las Vegas. It's the queue covering del Technologies World twenty nineteen. Brought to you by Del Technologies and its ecosystem partners >> Hello and welcome to Day three Live coverage of the Cube here in Las Vegas Fridel Technologies World twenty nineteen I'm jut forward, David Lot They Davis del Technologies world. This is our tenth year If you count DMC World twenty ten first ever Cube event where we go out to the events and extract the signal from the noise. Now we're the number one and tech coverage. Howard Elias has been with us the entire way. Our next guest. Keep alumni Howard allies who is currently the President of Services and Digital for Del Technologies. Howard, great to see you. >> Great to see you, John. Dave. Always great to be back with you. Thank you. >> You've been with us throughout our entire cube jury. It's our tenth year has been great ride and one of the benefits of doing the queue besides learning a lot and having great conversations is as the industry of balls from true private private cloud to, you know, big day that meets technology, all the different iterations of the business. We're gonna have the conversation and look back and see who's right. You >> get to go back and see what we said and holds you >> accountable. Not that you guys said anything crazy, but you were unique because we've had many conversations and most notably during the acquisition of the M. C. You're on the team leading the effort with your partner in crime from the del side to make sure the acquisition goes smoothly. And, you know, a lot of people were saying, Oh my God, icebergs ahead. We're pretty positive. So history treats us fairly in the queue way. Tend to got it right. But you said some bold things. That was pretty much the guiding principle of the acquisition, and I just I just tweeted it out this morning. So you got it right. You said some things. Looking back two years later, almost two, three years later. >> Well, look, you know John first, I appreciate that. Appreciate the opportunity to be back with with you, and it's amazing. It's been ten years, but yeah, so, you know, over the last couple of years, I did help Kohli the integration, and we said, Look, first and foremost, we're going to do no harm the way customers transact with us byproducts. The way we service them, that's not going to change. But then, that's not enough, right? It's not just about doing no harm. It's how do we add value? Over time, we talked about aligning our teams in front of our customers. Then we talked about unifying the approach not just in the go to market, but in services and in technology and ultimately delivering Mohr integrated solutions. And we've accepted here down that a CZ you rightly say so thank you for pointing that out. And you know, this week was a great embodiment of that. Because not only are we listening, Tio, what our customers want we're delivering on it were actually delivering these integrated solutions the Del Technologies Cloud unified workspace for client, these air things that we've delivered over time, you know, we stitch it together, and now we're unifying it, integrating it, actually now even embedding services into it. So that's the journey we've been on. And we've been very pleased with the reception, >> and Michael to also was very bull. But the key on all the conversations we had on this was and we'LL get to the current situation now because that's important is that you guys saw the growth opportunities on the synergies we did, and we kind of had those conversations. So a line you align the team's unify and integrate you're the integration phase. Now we're starting to see some of the fruit come off the tree with business performance significant. Well, we appreciate >> that we're gaining market share across the board, and we had a hypothesis with, you know, coming together. We had a complementary product, portfolios, complimentary customer segments way. We're very thoughtful and how we organized our go to market, and we're seeing that we're seeing that and market share games. But more importantly, we're seeing the customer conversation saying Thank you for that. Now I want more. How do you deliver more value faster? So I think we're past the integration stays. Now we're into the accelerating the value stage. >> Howard, you've been through and seen a lot of acquisitions, large acquisitions. I mean, I think of the compact digital, you know, not a lot of not a lot of overlap. HP with compact, much more overlap maybe didn't go so as well. Or maybe a smoothly massive acquisition here. Why do you think it worked so well here? Because there was a failure. A fair amount of overlap, you know, definitely some shared values, but maybe some different cultures. You've been on both sides. It's just seems to be working quite well. You seem to be through that knothole of maybe some of that uncomfortable early days. Why do you think it works so well? What was kind of the secret sauce there? >> I think a couple of reasons. First, the hypothesis of coming together was all very customer centric. Customers wanted fewer more strategic partners. They ultimately from infrastructure, want Mohr integration. Mohr automation. They wanted a CZ. Pat said yesterday on states they wantto look upto absent data and somebody else worry about looking down and taking care of the infrastructure. So the hypothesis was very strong. Michael had a bold vision, but the boldness of actually execute on that vision as well, I would say second we have. Yeah, while the cultures, in terms of how things got done were a bit different, the values were frankly not just similar. They were identical. We may have talked about this before, but When we did the integration planning, we actually surveyed half the population of about Delanie emcee. The top five values in order were the same from both team members. Focus on customers Act with integrity. Collaborate When is a team results? Orientation? It was phenomenal. I would say. You know, third, it's just the moment in time. Uh, and it's really a continuation. You think about the ten year partnership that Dell and GMC had back in the two thousands that actually helped us get to know each other, how we worked and helped form those shared values. So and then, finally, approximate one hundred fifty thousand team members signed up to the mission. You know, the tech industry is starved for star for tech talent. On the fact of the matter would that we have approximately one hundred fifty thousand team members of prostate all technologies signed up to our vision, signed upto our strategy, executing every day on behalf of customers. It's just awesome to see >> So digital transformation, of course, is the big buzz word. So we're gonna put on you guys what do you do it for your own digital transformation? You know, proof of the pudding. What gives you the right to even talk about that? What do you doing? Internal? >> Yeah, you know, it's a great question. And to your point, we talked with customers all the time. In addition to looking after our services businesses worldwide, I also am responsible for Del Digital inside of Del Technologies. That's our organization. We purposely named Adele Digital because we are on our digital journey as well. And so we are transforming everything that we do the way we do. We actually call it the Del Digital Way. We've had a couple of nice breakouts. Our booth in the showcase has got Ted talk style conversations around this, and it's really embracing this notion of agile, balanced team's getting close to the business, actually, the business in the dojo, with our developers moving more to a product orientation versus a project orientation, and it's really focused on outcomes on T. You hear us talk about this all the time. Technology strategy is now business strategy, and whether it's in sales or marketing or services. Doug's doing great work and support assist using telemetry and artificial intelligence and machine learning recommendation engines in our dotcom. The on boarding within hours. Now with what we used to take weeks with our business customers in our premier portal, Wei are looking at every opportunity everything from the introduction of bots and our p a all the way through machine learning. Aye aye and true digital transformation. We are walking that talk. >> Really? You're going hard after our p A. That's what Do Yu result. We've >> actually been doing arpa for many, many years and for you know, especially when you have a complex system complex ecosystem As you're rewriting and developing either re platform, every factoring or cloud native, you still got to get work done. So I'll give you a great example. You know, in a online world of today, it's amazing to know that we still get millions of orders by email and facts. And instead of outsourcing that and having humans retyped the order, we just have robotics, read it automatically translated. And >> so the narrative in the media you hear a lot of coordination is going to kill jobs. But I've talked to several our customers and they've all said the opposite. We love this because it's replacing mundane tasks it allows us to do other things. What's your experience you are >> spot on? I'm a technology optimist, and I believe that a machine learning robotics will do the task that humans are either not good at or don't want to do or don't like to do and allow humans to be more human. Creative thinking, creative problem solving, human empathy, human compassion. That's what humans are good at. And we need more people focused on those things and not row test. >> One of the things that Michael Dell on key themes in The Kino Day one and Day two in some day. Three lot of societal impacts of I Love That's kind of touchy feely. But the reality is of Reese killing people. The skills gap is still a huge thing. Culture in the Enterprise is moving to a cloud operation was his favors your strategy of end to end consistent operational excellence as well as you know, data driven, you know, value of the AP player. Great straight, but we've been seeing in the queue with same thing for years. Horizontally, scaleable, vertically specialized in all industries. Yeah, with data center so good. Good strategy, gaps in culture and skills are coming up How are you guys doing services? You mean you've got a lot of people on them on the streets? A lot of people that need to learn more about a I dashboards taking the automation, flipping a new opportunity to create a value for people in the workplace. We >> have this conversation continuously inside of our teams and inside of our company. Look, we have a responsibility to make sure that we bring everybody along this journey. It starts by painting the vision being that technology optimist. Technology is a force for good on how do we apply the technology and the digitization and, you know, creating our digital future, bringing our team members along. So setting that vision, it is about culture behavior. Set the tone from the top. But we also have a responsibility and retraining and re skilling and bringing you know, team members. New opportunities, new ways to learn our education services team, for example. You see it here, the certifications, the accreditations. We do the hands on labs that we do. It's all about allowing opportunities for people to up skill, learn new skills, learn new opportunities that are available, and customers need this higher value. Helping support? What >> about the transformation that's been impacting the workflow on work streams of your services group with customers as they are? Maybe not as far ahead as you guys are on the transformation. Maybe they're They're cloud native in one area kind of legacy in the other. How was the impact of delivering services? One. Constructing them services, formulating the right products and service mix to delivering the value. How is technology change that you mentioned Rp? What if some of the highlights in your mind >> Well, it's It's a journey and you know it. Mileage varies here, right? Depends on what you're trying to accomplish, but we never do wrong by focusing on what's right for the customers. So what our customers looking for? What are their business outcomes they're looking for? Uh, here's a great example in the unified workspace. You know, we've been doing PC has a service for a while even before PC has a service. We're delivering outcomes, delivering Peces, doing some factory into get gration Cem image management, lifecycle management deployment services. But now what we've done is really taken not just the end and view, but we packaged it and integrated it into a single solution offering across the life cycles. So now, once we understand the the customer and users personas weaken factory, image the configuration, ship it to the team members deaths not just to a doctor the place but right to the team members desk have auto deployment auto support telemetry back and manage that life cycle, we package that up now. End to end this a new capability that customers are really looking for >> before I know. Do you have a question? I want to get your reaction to a quote I'm reading from an analyst. Bigtime firm New Solutions launched at Del. World Show that worked to align seven businesses for the last eighteen months is starting to pay off. We just talked about that. Cross Family Solutions minimizes time on configurations and maintenance, which opens up incremental, total addressable market and reduces complexity. Michael Dell yesterday said that there's a huge swath of market opportunity revenue wise in kind of these white space gap areas that were servicing, whether its image on PCs and you kind of mentioned peces of service analysts. E this is tam expansion, your common reaction. >> I couldn't say it better myself and look. The to integrate solutions we announced this week is a great example of that of the seams. It's workspace won its security from SecureWorks. It's the you know, del Endpoint management capabilities. It's the PC hardware itself. It's the services life cycle from Pro support Pro Deploy Pro Manage, all integrated in the end and easily Mohr consumable were even Do any are consulting business with our new pro consult advisory offer offer. But look at the Del Technologies Cloud del Technology infrastructure. With VM wear we'LL be adding PC after as a service. On top of that, this is exactly what customers >> So what's your marching orders to the team? Take that hill. Is it a new hills? The same hill? What's the marching orders down to the >> teaching orders is Get out and visit customers every single day. Make sure we understand how our technology and services are being utilized, consumed and impacted. And where do we add more value over time? >> So I wantto askyou for from a customer standpoint, we were talking about digital transformation earlier, and, you know the customer's always right is the bromide. You guys are very customer focused However, when it comes to digital, a lot of customers is somewhat complacent about obviously technology companies like yours embrace digital transformation. But I hear from a lot of companies. Well, we're doing really well. You know, I'm gonna be long gone, but before this really disrupts my industry, it's somewhat of a concern. Now, do you see that? And and how do you I mean, I think one of the reasons just so successful in your careers you take on hard problems and you don't freak out about it. You just have a nice even keel. What do you do when Because you reached you encounter that complex, Eddie, do you coach them through it? You just say okay. Customer's always right. But there's a concern that they'LL get disrupted in there. Your customer, they're spending money with you today. So how do you get through breakthrough? That complacence >> adds a great question and you know, one of the other marching orders I give tow my team is that things were going so well is time to change. And so this is what we have to take to our customers as well. And, uh, look, way have to be respectful about it. But we also have to be true telling, and so we will meet with our customers, hear them out and where they're doing well, well pointed up. But where they're not or where we've got different examples, we'LL just lead by example our own internal example, other customer examples in a very respectful way, but in a very direct way, especially at the senior levels where that's what they need to hear sometimes. >> So you have a question, because I got I wantto sort of switch topics like >> one of us falls on the one problem statement I heard it was really announces a problem statement, but it was a theme throughout all the breakout sessions in the keynotes, and you guys are aware of it. So it's not a surprise to the Del senior people. You guys recognize that as things are going well on the acquisition and the integration tell technologies there's still a focus on still working better with customers taking away the friction of doing business with del technologies. It's a hard problem statement. You guys are working the problem. What's your view on that? Because we hear that from your customers and partners we'd love work with. Kelly's going to get easier. We >> still have more work to do. Actually, Karen Contos and I are partnered up our chief customer officer on easy doing business and look it it. We are a complex company. We have a lot of different business units. Technologies brands were working toe, bring them together, and Mohr integrate solutions like we saw this week. But we still can be complex, sometimes in front of our customers, and we're working on that. It's a balance because on the one hand, customers want Maura line coordinated, sometimes single hand to shake. We get that. But the balance is they also want access to the right subject matter experts at the right time. And we don't want Teo inhibit that either. Either way, so whether it's with our customers directly with our partners were on that journey, we will find the right balance here. We've got new commercial contract mechanisms in place now to unify our Cordelia, AMC as we're packaging Mohr VM were content more security content into the offer and be able to delivered is a package solution. In one quote one order one service dogs doing some great thing and in the back end of services connecting our service request systems are CR M systems, actually, even with VM wear and Cordelia emcee technicians co locating and support centers to solve the custom of customers problem in one call, not in three calls. We still have a ways to go, but we are making progress. >> So I wanted to switch gears a little bit, and you and I, Howard have known each other for decades, and you've never wanted to talk about yourself. You always wanna talk about the team, your customers, your company. But I wanted to talk about your career a little bit because John Ferrier did an interview with John Chambers, and it was an amazing interview. We talked about when he was, you know, Wang and one one twenty eight. There is no entitlement, and you've seen a lot of the waves. You started out your career, your electrical engineer back when, you know that was like *** physics assembly language. It was sort of the early days of computer science, awesome, and then you had a number of different roles. You as I mentioned there was digital, there was compact. It was h p and then you'LL Forget RadioShack Radio second. Alright, That's right, Theo PC days on. And then you joined the emcee in two thousand three, which which marked the next era. We were coming out of the dot com boom, and You and Joe Tucci and a number of other executives built, you know, and the amazing next chapter of AMC powerhouse. And then now you're building the next new chapter with Del. You've really seen a lot of major industry shift you see have been on the wave. I wonder if you could reflect on that. Reflect on your career a little bit for our audience. >> I'm just amazed and blessed to be where I am. I couldn't be more pleased. Sometimes I wonder how even got here. But when I do reflect back, it is my love of the technology. It's my love of what technology Khun do for businesses, for customers, for consumers and, frankly, my love of the customer interaction. This is, you know, from that first time in the Radio Shack retail store and you know, the parent coming in and learning about this new TRS eighty and I've heard about this and what does this really mean and being able to help that person understand the use of the technology? How Teo, you make it happen for them, it has always given me great satisfaction. And so, you know, from those early days and I've worked with a lot of great people that I just, you know, listen and learn from over the time. But, you know, when I mentor, you know, people coming up in their career, I always say, Look, you know, it's not at work. If you get up every morning, you love what you do, you see the impact that you make you'LL like the people you're working with. You're making a little money and having some fun on DH. Those things have always been true for me. I have been so lucky and so blessed in life to be able to have that be the case >> and your operational to you understand, make operations work, solve problems, Day pointed out. It's been great for my first basic program I wrote was on a TRS eighty in high school. So thank you for getting those out here and then I've actually bought a Tandy, not an IBM with a ten Meg Hard drive. I bought my motive. Peces Unlimited. Some small company that was selling modems at the time. Michael, remember those date Howard? Great to have you on The key was the Distinguished Cube alumni. Great career and always we got We got it all documented. We have all the history. There you go, calling the shots. Howard Elias calling the future, predicting it and executing it Living is living the dream here in the Cube More keep coverage here, del technology world after >> this short break

>> Narrator: From Gillette Stadium in Foxborough, Massachusets, it's theCUBE, covering VTUG Winter Warmer 2018. Presented by SiliconANGLE. (upbeat music) >> I'm Stu Miniman and this is theCUBE's fifth year at the VTUG Winter Warmer. 2018 is the 12th year of this event, always love when we get to talk to some of the users at the conference which's why I'm really happy to introduce to our audience Sue Morrow, who is a network manager at United Methodist Homes. Thanks for joining me Sue. >> No problem. >> First, tell me a little bit about yourself and what brings you all the way from Upstate New York to come to the VTUG. >> Well, I like to go to conferences whenever I can continue my education in IT. I grew up with computers in my house in the '80s. My dad was a physics teacher and a scientist so we always had a Commodore 64 or an Amiga in our house, growing up, when most people had Atari, we had computers. >> Totally, so Commodore 64, classic. I myself was a Tandy Radioshack, the TRS-80 Model III. So, in a similar era. >> Yep, I actually took a basic coding class on a TRS-80 when I was around 10, I think. Anyway, grew up with computers and somehow stumbled into IT later in life. So, that's why I'm here. >> United Methodist Homes, tell us just a little bit about what the mission of the company is. >> United Methodist Homes is a longterm care corporation. We have four facilities, two in the Binghamton area and two in Northeastern Pennsylvania. We have all levels of care from nursing homes, skilled care, up to independent living, and everything in between. >> Okay, and as network manager, what's under your purview? >> Well, it's kind of a silly title, actually. In longterm care or in healthcare or nonprofits, as we are, you often wear many hats and so that's, sort of, a weird title for me, but I supervise our help desk which we serve centrally from our corporate office. We serve about 600 actual computer users and, all in total, about 1200 employees who interface with the technology, in some way. So, I supervise the help desk, I make sure our network is running well. IT has changed over the years so that we're now providing more of a service and making sure that everything is up and running, network-wise, for everyone instead of keeping our servers running all the time. >> Yeah, reminds me of the old saying, it was like oh, the network is the computer, things like that, so you've got both ends of it. >> Sue: Yes. >> What kind of things are you looking at from a technology standpoint when you come to event like this? Did you catch some of the keynotes this morning, there was a broad spectrum? >> Yes. >> What are the kind of things that you're digging in to and find interesting? >> Yeah, the keynotes are really interesting. I think the first one that I went to with Luigi and Chris was great just to, kind of, expand your thinking about your own career personally, and where you want to go with your life was really interesting. I also watched Randall do his coding which is completely outside of what I do everyday, but was fascinating. And then the last major keynote was fantastic. I think that from my perspective in my company, we're kind of small and we don't do a whole lot of, we don't run apps and things like that, so the things that we have ritualized is mostly storage, so I'm looking at better ways that we can manage our storage and stuff. Most of the applications that we run now are SAS applications hosted by somebody else and their cloud, or a public cloud, or wherever, so I'm not so much looking at the cloud technologies like more businesses are that are providing an application for their company. >> It sounds like cloud and SAS's being a part of the overall strategy, have you been seeing that dynamic change in your company? How does it impact what you're doing or is it just a separate organization. >> It's definitely been a shift in the last few years, we used to run all of our applications in-house. Longterm care has caught up now, with the hospitals, so we have our electronic medical record which is a hosted application, whereas, up until five years ago, that was an on-premises application that we hosted and had to run and maintain, and update and upgrade, and make sure was available. That is definitely been a shift, that everything is now hosted. So we just make sure that our network is up and running and support our users and all of their issues when they break things, flip their screens, drop something, provide hardware for them all that sorts of stuff. >> The constant pace of innovation change. On the news this week they were saying, okay, medical records on your iPhone is up for debate. Does regulation impact your day to day activities and what are some of the challenges in that area? >> Absolutely. One of the other things we have to do is interface with the providers. We have medical providers that come in from the outside and they need to access our EMR also, so we need to provide access for them on, sometimes, whatever device they bring in, which is not always compatible, so we have a whole other set of challenges there. Where we can manage our computers for our employees by pushing out policies and things that are required for the application. When someone comes in from the outside, it isn't, necessarily, setup right, so we have that other set of challenges, and regulation-wise, yes. The government is always pushing out new and updated regulations for healthcare and we have to keep on top of that too. Of course, we have HIPAA concerns and things like that, which is also comes into play when you're talking about cloud host, and any hosted application. We have to be concerned about HIPAA, as well. >> Yeah, wondering when I look at the space that you're in, the ultimate goal is you want the patients, the people at your company, be able to spend more time, help them, not be caught up in the technology of things. Could you, maybe, talk a little bit about that dynamic? >> Yeah, one of the things that I always say is, we need to give our employees the tools that they need to do their job most efficiently. A nurse needs to be ready to go at the beginning of her shift on her laptop, ready to pass meds, and when they can't remember their password or that computer isn't working, my team needs to work as quickly as we can to get them back to work. We serve our users, really. We're not there being all techy. They want us to fix them and get them back to work, and that's what we do. We put tools in their hands, any device that they need to make them more efficient. I try hard to provide a variety of devices, people have different preferences on how they do their work. Some people prefer a laptop, some people prefer to stand at a wall-mounted touchscreen and document, some people want to carry a tablet with them. I try to provide a range of devices so that they can have whatever suits them and makes them most comfortable to get their job done. >> Love that, it's not, necessarily, about the cool or trendier thing, it's about getting business done, helping, and in you're case, enabling your employees to really help the people that are there. Anything you want to highlight as to things you're excited to look at this show, or just technology in general? >> I'm just kind of here for the general nature of it. I enjoy the networking and getting to talk to people, and keeping current in what's happening in the industry and my career, so that's why I come. >> Alright, well Sue Morrow, really appreciate you coming, sharing with our audience. >> Absolutely. >> User groups like this, all about the users. Happy to have lots of them on the program, so big thanks to the VTUG group for bringing us some great guests. We'll be back with more coverage here. I'm Stu Miniman, you're watching theCUBE. (upbeat music)