Digital transformation sales for government

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In. So where is all that investment going that Intel's making? Because we just got $8.5 billion. Right. We did. We did. We got 8.5. And that kind of goes with 100 billion we're spending just in the U.S. and another around 50 billion in Europe. So we're working as fast as we can to build out the diverse supply chain focused on Western world. Welcome to Embracing Digital Transformation, where we investigate effective change, leveraging people, process and technology. This is Darren Pulsipher, chief solution architect, author and most importantly, your host. On today's episode, Government Digital Transformation with returning guest Greg Clifton and new guest Jason Dunn-Potter Greg. Jason, welcome to the show. Thanks for having us, Darren. Appreciate it. We're at the HPE CTO Summit now. This is going to be a really interesting episode. I'm excited about this. Jason, this is your first time on the show. Greg, you've been on the show. This is your fourth time. Maybe you were desperate for Greg. Greg You were second. You were my second guess. I'm sorry. It's right. You're right. Yeah. The first external guest. I did the first episode and we did the second episode, so it's good to have you back again. Jason, none of my audience knows anything about you. So can you give a little background on you? Sure. Sure. So Jason Dunbar, Solutions Architect under the DADT. You might have seen that a sweat event. You might have seen you in a Fed event. I spent 26 years in the Army. My last job as a White House comms agency, CTO opposite Bill Burton. A decade later. And then I got to tell you, it was a magical ride at Intel. We've done a lot in the last two years and we're very excited about some of the stuff we're doing now. Thanks very much, Jason. We're glad to have you on the team. Obviously. Today, we're going to talk a little bit about Intel's position on digital transformation. It's the name of the show is Embracing Digital Transformation. So obviously it was a good part in and what that means. But Clifton, give us a little bit of a background on our journey, Intel's journey into digital transformation. Sure. Yeah. Well, obviously we've been at the foundation of computer technology, right? Sort of helped found Silicon Valley and computing capability. But throughout the years we've seen lots of different transformations. It was mainframe to client server. Sometimes I'd say cloud is kind of like a mainframe and everybody wants to go to the edge again. Right. And we're transforming again. I certainly transformative. But we're now transforming in how we make the compute that everyone's heard of the CHIPS Act and they've seen the investment the US is making in our semiconductor manufacturing capability here domestically. That's a major change and actually it's a great thing, right? We saw even this past week with an earthquake in Taiwan. Luckily, nothing happened to the infrastructure. But what if it happened? Right. We're so dependent on this compute environment to run our digital lives, businesses and government that we've got to have that diverse ecosystem for security, for innovation to run all this compute infrastructure. So that's a big part of what we're investing in. So where is all that investment going that Intel is making? Because we just got $8.5 billion, right? We did. We did. We got 8.5. And that kind of goes with 100 billion we're spending just in the U.S. and another around 50 billion in Europe. So we're working as fast as we can to build out the diverse supply chain focused on Western world. So we're building in Germany, Poland, Ireland, Israel, and then here in the U.S. and multiple sites in Arizona, California, Oregon, New Mexico and Ohio. Right now, it to me, it's it's one of those must dos not only to deliver the compute capability, but to bring the innovation of advanced manufacturing back to the US. Right. How do you solve problems in manufacture and translate to how do you build new technology? The other side of this is the workforce folks that actually can make stuff in these factories. But the other side of that is actually building these factories is a marvel, right? And having that technology to build these things in the US, not only to operate factories that build it, to me that's a national treasure as well. And something we've done. Yeah. Go ahead, Greg. I was going to say a couple key things that you must know. First off, we went with schoolhouses on a Dairy Queen in Ohio. This is the time. All right, Jiffy Lube, pick your favorite thing. It's going to be culverts. So we're clear. The other thing to think about is that Intel is making a major investment in colleges and universities. We need a workforce. So if you got folks that need to get into STEM and engineering this time, ladies are looking at you. Please help me for the March of last year and Fill offered for scholarships to Ohio universities to get engineering degrees for free. Right. We can't make it better than free. Please apply. We sell your friends supply. We're looking for workers in those spaces. There's a huge gap. We were out at Lyceum last week, a lot of leadership and they identified a huge gap in capability. Now let's talk a little bit about the Ohio. Absolutely. We're building two thirds right now. We do? Yep. And there are 18 in sales, correct? Correct. So 18 eight is angstrom, so 18 angstroms. Anyone have any idea how small that really is? And we do. So here's an example in the people's minds. Right. 18 Angstroms is about 1.8 nanometers the coronavirus 72 nanometer diameter. So we are producing transistors at 1.8 meters. So why do you care, though? That's the point to understand is that we're moving the needle down, which is bringing more performance, lower swap, better performance all the way across. It's the air of Angstrom. If you're not familiar with what we're talking about, it's going to affect you directly, whether you know it or not. But the other thing to understand besides the science of it is, is that it's evolution. We are literally moving forward in technology integration. We've got a lot of R&D going on. I know it was about yesterday with fibrosis and image, but also some of the stuff we're doing Via and how that all ties together. And that's what I think. I think the thing is when you talk about those, make sure they understand it's not a fab foundry. Right. And the people in new there right. Probably heard in the news Intel's actually separated out our businesses. So we have a foundry business and a product business so that both can be as efficient as is possible and deliver leading technology in a cost efficient, cost effective heating technology manner. And the other part of that is how do you solve your problems? You know, we saw today some of the what it's going to take to deliver A.I., the world of just building on the best things or GPUs may not be the best, right? Just for an architect, your competitor, whether that be in government or in business. So what our business model allows is that, yes, you can take our commercial off the shelf products. We've got CPUs, right? Our xeons in our cores and flying and Server have been an institution in the space. We have for years. We have high end HPC and training as well as very energy efficient edge GPUs as well. We've got a I really generative API, large language model customer Isaac Gowdy product line that he's bringing to market later this year. We've got infrastructure processing unit FPGA is we have a breadth of commercial products, but if that doesn't meet your need, you've got to design, you bring it to us, we'll make it or you've got a die. You need us to package it. We'll do that final packaging. You go give it to HP, they'll put it in the server. If none of that works, we will actually design and build it from scratch for you. We will do all the design of silicon validation packaging. Same thing. And it's our friends at HP. They'll put it into a server. And as you said, Jason, none of that works. We'll turn on our R&D engine, invent technology and build that. Yeah, it's really exciting time there, especially when you start thinking about like, like Greg said, unencrypted sketch it on a napkin or do you have an idea or you're already three quarters of the way. The other thing is ingesting our IP, right? Taking our IP, wrapping it with what you're building, making it better, you, you and then also having that fire that sounds separated physically like physically, emotionally and financially from the company so that you can do firewalled off operations. Right. They're going to be a great example. That is we recently signed huge agreement with ARM yes in the past arm and intel computers right it as we were selling. Did anybody see that coming? I've got to ask that. Anybody expect to see an ARM leadership person shaking hands with an intel foundry director on stage in front of everyone? It's a game changer for some of you if you do not understand risk and some of the things that that will involve. It's a huge change of business. Right. So I, I understand all the silicon stuff, right? That's where we make our money and things like that. But our customers don't care about sold. No, never ever. How many how many of you guys out there in the audience today? How many of your customers ask you what process node that chip was put on? No one. No one really cares what. So how does how is Intel addressing the problem of actually solving mission capability, solving problems? So we've done a couple of things. First thing is articulate. If you guys don't know, we we launched a lifeboat with our actual software company called Articulate. It's an AI integration company, the custom built Artificial Intelligence Solutions because it's hard, A.I. Smart. And I want to talk about this for a second. This is something I want to make sure you guys go back to the customer. When I talk about, it's like talking about, Hey, I need to buy a computer because I need a computer, right? I heard about computers. I want to buy computers and to get computers Back in 1984, we should get computers for the office. All right, How about we change the dynamic? They actually get out from the actual problem. Is it a toy? I.e., we're exploring. We're going to assess. They are and see what to do. Is it a tool like we know what we want to solve and where to use it to leverage? Or are we going to bring a teammate? I'm going to offload some of the things I'm already doing and move it over because I know I know enough about A.I. to get there and there could provide me direct services and take advantage of things that I don't need to do on a day. I got to tell you, the daily updates or the weekly upgrade that I'm like every week are to be really nice. We just took my outbox, figured out what was important based on the volume of emails sent and help me formulate that outbox. I'm looking forward to that, like tomorrow so we can start like I actually have an APC right here from nothing to do the right now. So that was morning. So it's real. Anybody from Microsoft in the room? Yes, sir. Microsoft Copilot. Are you kidding me? Yes. If you do not know what we're talking about, this is where APC is going, right? That is one of the thousands of tools that are coming to you right now. You can download it now on your own box. By the way, I tried. It's good, but it's better on that. Yeah. So, all right, you talked about software, but let's talk about like real problems that people have in the Department of Defense or Department of Homeland Security or how how is Intel engaging with them on that? Because we still talk to those in customers and they don't really care about. So they do. So one thing we've done is we've actually gone out to the field. So that's the other thing. Everybody knows Intel's in the field now. You see us at all the events. Anybody that students are up in the field outside of this form, every form you go to, you will see an intel rep somewhere walking the floor. If you haven't seen them, find them or send a to. He'll tell you this because we are going to go to every trade show running to talk to every senior leadership position we can and we have done all of that. I got to tell you why. If people don't care so they don't, but they care about solving the problems. Right. And that's where we gather that information. So we have a couple routes to market for you guys. First is we're taking that information back to Intel labs, 12 laboratories and all the engineering work. We meet with them on a regular basis now to get the voice of the customer. What does what's broke that we can't fix? The other thing we're doing and some of you know, I have literally got to you and say, hey, you need to partner with somebody because they bring a solution that augments we're solution and I'll package based on government feedback. Here's the other thing to think about. Lisa, jump. We're one degree back from the government, so I don't have to fight the RFP issue. They can tell me things they can't tell you directly because we're not in the direct food chain. So we have the ugly conversations, the white boards about what's in the realm of possible so we can serve as customer advisors. We do thought leadership to them. What's the realm of possible which helps position you, especially when you have solutions? I know we're working on a bunch of efforts at headquarters to like funnel all of the folks that say, Hey, on an zero trust rate, there's like 64 parts of that. Great, how do I map To which part are you solving? Who's our partners in that space and what can they provide Just like you alluded to, something I think is really important for us to touch on. Sure. Our ecosystem is incredible. Absolutely right. And it's you guys that are in the room with us today. You are ecosystem partners of Intel and you are vital to getting the word out on leveraging silicon to get solutions to your customers. So it's vital that you work with Intel. Accounting sets the field, the field reps that are out there, because we are showing the future to your accounts, to your customers. So you talked earlier about your machine learning. A.I. What's the question? What's the answer I'm trying to get to? So even though you don't really care about the silicon necessarily, it's a key ingredient to make it happen. So I think the ask is, Yeah, let's continue partner, and let's continue asking our customers what their challenges and then how do we solve that. Right? And that's where you kind of look at the broad set of hardware software that you put into play. So I mean, I'm like 20 or 30 training calls a week. So if anybody's not taking those, we do those too. Every partner ecosystem, I don't care the size of your company. If you want to know about something we're building or something we're doing. Also, we've given glasses on. What is the Air Force to some of the new account reps? Anybody with a new account try to figure out what's in the account. We understand the mission set, so we're here to enable all of that. Right. So something interesting you brought, you said the software, the hardware. I saw the three pillars that Sam brought up earlier. We have 6 a.m. so sorry, but you mentioned all six of them in your presentation. We talk about ads. We talk about we call it ubiquitous computing, which is really hybrid cloud security, which you have on the bottom, advanced communications. And the last one, which is my thing, is data management, which you brought up earlier data is gold, right? It's the oil. We're we're in oil. We're in the oil world. You're right. It's the oil of this century, and we're not managing it very well. And one of the problems that I have see is a lot of times when we go and engage with our customers, we're creating not only gate and silos, we're creating technology silos. And I'm seeing the exact same thing happen today with a lot of people are buying I'm building a high cluster labs in the state because when I moves off of GPUs onto infuse, what are you going to do with that GPU cluster that you have? And what was mentioned earlier today was the GPU. We can't generate enough to keep up with the demand, but new technologies are are coming into play like the memristor or neuromorphic processing units and things like that. So putting yourself into a box like that is very dangerous. So what we're proposing and what we're really trying to push forward really hard right now is to go back and look at enterprise architectures. But how do I establish an enterprise architecture so I can consume new technology quickly, I can manage my data across all these technology silos, and I can break down the data silos that are already existed. So we've done architecture. It's hard, though, right? So that's that's where we're here to help, right? It's art. There's a lot of to I mean, I'll be honest, I'm going to apologize. I'm in the room. We're moving in a rapid space, like five nodes for years and more and more now. Right. How do you keep up with that? How do you know what the customer needs? Based on what we can now offer? We could not for 20 minutes ago. If you don't understand, with Xeon and some of the acceleration we've done with that, we're taking on some some AI workloads without you, which was amazing. But then also we're doing things like with Netflix where you're like, Hey, I can do transcoding faster, better, cleaner. And so now it's a3x return on investment. If you haven't seen that go on a YouTube Intel based Netflix, it's an amazing story. They took some of our GPUs they they mapped out their transcoding solution so you can go from tablet to form to TV on the house and then they turned around to use the exact same architecture to accelerate their AI algorithm, determine what do you want to write, How do I deterministically figure out based on the last 20 things watched, How do I figure out what to recommend to you? So the content delivery teams at the local level, folks, this is where we come in super handy. We can show you some of those scenarios and use cases where you can figure it out and you can go back to your customer and say, Look, we've already solved this is solvable and we have a prime solution baked in and built in. Okay. So what I'm kind of hearing a little bit is the days of a hammer nail are gone. Yes, right. They just cause problems. Right? Right, right. So we have the world of heterogeneous computing where have specialized compute for different types of workloads, whether it be or inference. And there's a big difference between inference in air training. sure. Doctor versus doctor in school versus doctor in the field, by the way. Hey, Doc, thanks for coming on board that up there. And you couldn't be more. Right. But the other thing is we gave some tools to the field. So anybody who's not familiar with our Intel developer Cloud last year, Greg Lavender, the CTO of Intel, announced, Hey, we've got this developer cloud. You know, your kids in high school can try that out for like 30, 60 days for free. Put some stuff in there, test out workloads that they're in the software space. Guys, stop buying giant non-production systems. We're here to help you. We actually have built that for you so you can go in and do a workload benchmark. So when you go there, customers say, Hey, if you're a software ISV or whatever, I ran this, this is the results and this is what it actually looks like in the real running on Goudie Running on Xeon, right. Or whatever or whatever accelerators or whatever accelerator. And we are in the midst of trying to get that certified. A lot of it's just things you don't necessarily need. You're not put in place by the house owners just test later. But for those that can't use the cloud and all we are even looking at in on prem version, but with HP, try to give somebody that capability so they can take it in their environment, in their lab to do that testing. So before you deploy into production, you've really looked at the compute options, the maximum which will be So you mentioned free. I really like that topic. We we we're very excited about some of the most social stuff that's going on across the DOD. We're huge fans of agnostic computing. You can migrate from A to B, the story of the multi hybrid cloud you talk about that would be and some of that green integration right? The other thing I was really excited about was simple. That's why I see all how we do the conversion for you on that on one API, on the one API story. So if anybody is not familiar, see my C is the acronym is a software set that allows you to run software applications. Intel does not have a licensing model for that. And I try to explain to somebody, they're like, they're freaking out about like, well, it's not real. It's mostly freeware has no value as like when you buy an intel CPU, it's just like when you buy an intel CPU, you get the software because you bought the hardware, we just pack it in. It cycle is by design. Same thing. And by the way, I'm not going to tell you that if you run it through the benchmark workloads, you'd be surprised. It runs on everything, not just Intel. JP Yeah, there's something really cool about one API in cycle. I can target it for CPU's champions in Pugh's FPGA and even custom uses. So what that means is if you're a software developer and you're developing algorithms, I don't target to a specific piece of hardware. I write a generic a generic algorithm, and the one API compiler optimizes it for the different hardware that you want to target it too. Yeah, I will tell you about Incredible. It decreases. Yeah, right. It was a great thing for Argon, right? We are going to make the transition. We're working on Project War with HP and we're really excited about all that. They were super excited about that. They don't have to recode everything to slide over to the software, right? It just slides over to our machines. So as you guys can see, there's lots of really cool technologies all involved in this digital transformation of that. Intel is really enabling. And I said this a couple of times, it might sound a little bit humorous, but it's true. We don't predict the future. We create it because the chips that our labs are working on now, they're going to be available in 5 to 7 years and you guys haven't said anything yet until you see some of that, some of that stuff that's produced. You know, I think I talked about it in terms of what we're doing here in the US, but we're also looking at doing some enhanced security capability as well. So not a whole lot we can talk about in a public forum on that, but we are certainly working very closely with our government partners, understanding what they need, what they want so that we can deliver and secure capability. And then obviously we'll take it, give it to you all, take it all and finish that complete packaging for as well. And even the traceability aspect of that is is critical. And that's actually built into our chips today. Well, the other part of that, too, is the confidential computing. If you want to talk about that real quick once you actually get the device. And so, yeah, this is an interesting aspect. Confidential computing. How many of you are aware of the term confidential computing? Well, a handful. All right. Yeah. Well, it's been a real quick so confidential computing basically takes the whole idea of encryption into memory. So right now, if first off, if you're not encrypting your data at rest, do I mean, I can't believe you wouldn't be. And people say, I take a hit in performance, you don't anymore because all of that encryption is happening and it's now. Same thing with data in transport, but there's a vulnerability with data in memory, right? If I'm running on a box and someone has access to that box, they can dump the memory and get access to all my data, including, you know, top secret algorithms and things like that. So Department of Defense is very concerned about this. They wanted to be able to run their algorithms in encrypted memory. They were looking at polymorphic encryption very slow. So I'll break this down because a lot of people get confused. This is not about you're not worried about a cloud provider being vulnerable. It's more about worried about your cloud provider being just as vulnerable as you are with all you got going on, Right? Yeah, that's and it makes it more complicated. And I try to explain it really simply. It's like having a refrigerator in your house where you go in all the food is your food in the thing you like, your time with your your lunch. However, at the end of the day, everybody shares the same tools in the kitchen, right? You pull out your food, you make your sandwich, you clean your tools, you put them away and you put your your lunch back in the thing. This keeps everyone else out of my food chain, right. Process. But we all share the same kitchen, right? This is really important, especially if you don't have the memory. Right? Exactly. So that's the whole point of the structure, is that you cut off pieces of that. We we talk about this. We really apply to things like financial records. h.R. Medical field, right? Anywhere you have to have pii. Right? This is critical for cloud architecture. We're really sad we haven't gotten there already. I will tell you, when sharon looked at last year at our intel public sector summit, she came right in and said, i need more. I need to know everything. I don't know why we didn't do this before. We didn't have the right questions because we didn't know. We didn't know you could do this right. So now everybody does. The other thing you're protecting against this Junior. Add this. We all understand that sometimes you get those nuances in their research and around the government data. That is not going to end well. All right. This takes advantage of this specifically the gates also. So the key here is that this is available in all the cloud service providers. Yes. It's also available already on any of your HP servers. Yeah, it's already there. All you have to do is turn it on. So, yeah, one of the coolest use cases I see I can think of is one that we did with the FDA on clinical trials. One of the biggest problems with clinical trials is you have to protect patient information and you also have to take the algorithms that researchers are using to identify new drug interactions and cures and things like that. So what we've done is we set up these secure enclaves in clinical in clinical sites, not exposing their patient data to the researchers. And the researchers can drop their algorithms directly into the secure enclaves so no one can see what's inside the lockbox except the results coming in on the other end, which have been completely sanitized, really cool case. And it's actually helping quite a bit on drug discovery. Yeah, And I will say we can't get a classic case and level stuff, but there are several government agencies that are looking at this for other reasons. Right? Think about a classified operations where you silo off people and information. This allows you to do a lot more flexibility, especially globally, using all kinds of solutions. Thank you to Jason and Greg for coming on the show and a special call out. And thanks to HP for letting us record at their latest government CTO summit. Thank you for listening to Embracing Digital Transformation today. If you enjoyed our podcast, give it five stars on your favorite podcasting site or YouTube channel, you can find out more information about embracing digital transformation and embracingdigital.org Until next time, go out and embrace the digital revolution.