The Exchanges

Q So, uh, genai.mil, I think was like a surprise and how quickly, um, it happened. Uh, uh, can you tell us the story of that and what the, like the goal is?

A So genai.mil, because if you're on a, on a, Department of War network. You, you know, even the unclassified networks are secure, right? And, and different levels of security as you go up. So you still have to figure out how to architect using AI in, into those networks. It's not as simple as going to chatgbt.com and, and signing up because those things are sort of generally prohibited because you have to have restrictions on how to use them. So we had to figure out what are the, the policies, how do you architect it in the network? So nothing goes Back into the pool of data that ChatGPT or Claude or any of these companies have, because we certainly don't want, no one in this country wants our data getting out into the general public, right? Into these models. So you have to architect a different, uh, data flow. So, but we moved really fast. I had some like Databricks engineers, former Databricks engineers, former Meta engineers, former AWS people, Tiger team, 60 days, Uh, good, great collaboration from Gemini, uh, from Google's Gemini, who already works at Department of Warsets, some familiarity with our architecture and our systems, and got that launched to three million people. And we've had over a million people Unix use it in the last 30 days, which is kind of awesome. We've got one third of the enterprise on one model. That's 2.5, not three point oh, three point oh is comi…

AI assessment note: “Tiger team, 60 days, Uh, good, great collaboration from Gemini”

Q for or procured. And, you know, that's somewhat different from how you think about innovation in terms of something new comes up. You want to rapidly be able to iterate, to launch it, to deploy it. And so if, how do you think about either flexible budget spend or reallocation of budget over time and how does that relate to the legislative process and how does that impact entrepreneurs ultimately?

A Yeah, it's been, it's been a problem, such a problem that they've given like an awful name to it called the valley of death, which I, which, uh, you'll hear eight ways to Sunday here. And the ways, you know, we've come at it and I've come at it is we have this defense innovation unit, which is rapid contracting, has a billion dollars, has like a reasonable amount of money to do things really fast to get startups off the ground and get them through. We have several other programs that have that same capability, one called AFIT that takes companies that have developed the product, but now need to scale their manufacturing. So there's a different line in the, you know, different point in the process. I have the Office of Strategic Capital, which has two hundred billion dollars in lending authority, um, low cost loans, and that both sends a demand signal to these companies that other private capital crowds around it, equity capital often, and it's, Low cost loans, right? It's treasuries plus a hundred bips. And in the last, I don't know, four or five months, we've done five critical minerals deals, like really fast. Cause that's an, that's a target area and we'll have other target areas. So if you're a company that's in one of the super critical areas, um, we have this huge lending authority there too. So I'm trying to collapse the valley of death by crowding capital around in diff…

AI assessment note: “we're reserving a bit of the budget every year so that we can make in-year budget decisions.”

Q related to moving fast is prioritization. And I think in another interview in the past, you said something like, 14 priorities mean no priorities at all. And you've kind of really honed down into a handful of key areas. Do you mind walking through sort of those key areas from an overall broader innovation focus? And then maybe we can touch on one or two of them as we go.

A Yeah. I mean, so just to analogize to Uber or any company that, you know, we worked on together, Imagine you went to a management team and you're like, what's your, how many product, you know, how's your product line going? You're a series B company. You're like, well, I've got 14 product lines. You'd say, well, what about sort of uninvestable, right? So, um, when I got here, there were 14 critical technology areas. So critical, critical to our national security. So I looked at them. I said, well, yeah, number one, that if, if there's that many, they can't be critical, but number two, Hard for people to hold in their head that many priorities and wake up every morning knowing that they have to get up and execute against those priorities and make progress because you get distracted, you get too much, uh, dispar, you know, uh, separation and therefore not enough resource to any one thing. So I cut them down to six after studying and I made it more action oriented. So we put sprints behind them like you would an engineering team. So, uh, you know, off the top of my head, the, the number one is applied AI. Because we're not building a foundation model at the DOW because there's being hundreds of billions of dollars being spent by the private sector on this. So how do I adapt or use what's being developed in the, in the private sector and apply it to the Department of War use cases?…

AI assessment note: “So I cut them down to six... number one is applied AI... number two is”

Q You mentioned that one thing you have to have, uh, to get these changes to happen is like some talent from Silicon Valley or just talent that is excited about this pace. Like who are you recruiting? Who do you want to be part of the Department of War?

A Big untold stories about Doge, which is, yeah, it did some, some aggressive actions in the beginning that were, um, controversial and all that, but the talent they brought into every department, um, could then be deployed on other projects like the AI action plan, uh, that we did with Gen AI. So, because they were already, like, Elon chose technically sophisticated people. There weren't all engineers, some were lawyers, some were Had from, but they all had a mentality of, of a fixer builder mentality. So I borrowed a lot of those people and then they attract more people on the way in. And then we have this U S tech force that, that Scott Kapoor from Andreessen Horowitz is deployed. And we were hoping to get thousands of people out of college for a two year stint, sort of make it, um, you know, this is your service to the country as a technologist rather than as a soldier. Um, so now we want both and we're going to try to, you know, make, try to make that a badge of honor so that you go back in the industry with some credit, you know, so additional credibility and be proud of your service here. So those are the ways I'm attracting talent and I'm dialing for dollars. I call everyone who's had just left a job and I'm like, Hey, do you have a year to spare doing the coolest stuff you could possibly imagine? Recruiting Tuesdays, I call them and I call my friends like you guys and sa…

AI assessment note: “we were hoping to get thousands of people out of college for a two year stint”

Q Is there a list published anywhere where founders who are listening in can go and see what they should be building or areas where there's more demand than either people understand or is anticipated or where the DOW is willing to help provide capital or other things to accelerate it?

A So the DIU for defensive issue has like four or five categories of things that they look at. So that's, that's sort of a published and public thing. The Office of Strategic Capital is a little more proactive. They're going to say, we have this whole, I'm going to go find companies that already exist that do this. So it's not for startups because it's a lending facility, if you will. So they're looking for companies that already exist and how do I expand their, their production? Um, but it's a good point. You know, at some point, I was talking to the secretary about this the other day. It's like, we should have some forum for, for talking about the things that we need more proactively so investors and entrepreneurs can think about them.

AI assessment note: “DIU for defensive issue has like four or five categories of things that they look at”

Q it. Uh, and like if, if there's a, Massive regrowth of American manufacturing. It will not be in exactly the form it was like 40 years ago, right? It will be because it is driven by automation, better processes, AI, like being able to make things other people are incapable of making versus competing in necessarily a global marketplace for cost. Um, but I think that's totally doable. That's exciting.

A Yeah, but, but the one thing I'd add there is like, who's gonna, who's gonna, uh, dig and weld and electrify all the data centers we're building? There's gonna be people to a large degree. There'll be robots. Doing some of this, but there'll be people and who's going to build all the new housing we need in these cities because of the housing shortage. You know, so there's, there's going to be work. It may not be in an auto plant to the degree we had workers in an auto plant as a percentage of sort of the workforce, but there's going to be other big jobs. I mean, the welding's jobs, we're trying to build ships here, can't find enough. And it's a job that pays six, more than six figures. In areas that are not high cost to live in. So it's like, how do you point people at the right capital, train, do the right training and so on. So I think there's a lot of opportunity, uh, for all categories of workers. Um, but yes, you're right. In some cases, you know, on farms, are you going to have robots, you know, you're going to, are you going to use robots and automation to figure, fill holes that are, that we can't otherwise fill. Like, yes. And we're best positioned to do it.

AI assessment note: “who's gonna, uh, dig and weld and electrify all the data centers we're building?”