I was a kid in the candy store reading the Golden Age Report. What you're describing there is a complete fundamental, AI-native, AI agent-up reimagining of the entire scientific process. And I think it's something that is possible. My sense is this is the golden age of America.
AI is a technology that is going to impact every agency. Whether you're flying drones, whether you're doing AI-powered medical diagnostics, whether you're at the SEC and working on financial services, AI is going to impact every single one of you.
Do you have sort of a longer-term compelling vision of what you think America could be like?
We as a government need to be opinionated about what the most important things are for the future of our nation. I mean, we're putting man back on the moon in '28. We're going to build the first elements of a lunar base by '30, put a nuclear reactor in space by '28. I mean, that's crazy.
Okay, my favorite idea, it falls into the crazy idea: I can't believe Michael actually wrote this down. All right. Now, that's a moonshot, ladies and gentlemen. Welcome to Moonshots, everybody. Today, I have the pleasure of interviewing a friend, Michael Kratsios. He's the 13th director of the White House Office of Science and Technology Policy and the science adviser to President Trump. Michael is the principal architect behind three landmark initiatives that are shaping America's acceleration during the singularity. The first is America's AI Action Plan, the administration's roadmap for winning the global AI race. The second is Genesis Mission, a Manhattan Project-style effort to accelerate breakthrough discoveries. And then most recently, Science in a New Golden Age, his blueprint for rewarding bold, unconventional ideas and dramatically increasing the rate of scientific discovery. So this is the spot.
This is it. Yeah. You go and give a briefing.
Ladies and gentlemen, I've called you here today to let you know that we have now officially approved a trillion-dollar science budget. Congratulations. We're going to be solving every problem on the planet within the next four years of this administration. There you go.
Yeah. Well done. One day we'll make that announcement.
This interview takes place at the White House and I'm asking these questions on behalf of myself and my Moonshot mates. All right, let's jump in. Enjoy. So, Michael, we are arguably living during the most extraordinary time ever in human history where science and technology is hyper-exponential, and you're in the thick of it. You're in the middle of it, right? Ray Kurzweil predicts we're going to see as much progress in the next decade as we've seen in the last century. And that's like going from the Ford Model T to the Starship in the next 10 years.
On top of that, we're on the edge of AGI, maybe the next 3 years, ASI. How does the government process ever keep up with that?
You know, we're trying our best. It's something that I think generally governments have struggled with for a long, long time. And I think what we have to do is make sure that areas where we are seeing this tremendous growth, that we allow the regulatory system around them to exist in such a fashion that it doesn't get in the way of this progress. I typically think of technologies kind of in two buckets: they're technologies that are either born free or they're born in captivity. So born-free technologies are things like what the internet was in the 1990s. And the best thing that the government can do in those situations is to step back, get out of the way, don't jump into it.
I think it happened so fast they didn't have a chance to get in the way.
Yeah. Well, it was interesting. There was a bill passed in 1996 which essentially Bill Clinton was behind it. It was kind of bipartisan, and I think it kind of allowed some of this stuff to take hold. But I think this extends for a lot of technologies: be careful before you start regulating. An example of that is in AI. I think this always comes up when I think about AI regs: the EU AI Act was passed and finalized by the EU Commission before ChatGPT was even invented. So there's no way that what they have today actually applies to LLMs of today. But I think the second types of technologies are the ones that we pay particular attention to because those are the ones that we actually have to take action on, and those are technologies that are born in captivity. Think of commercial drone operations. Think of AI-powered medical diagnostics. These are technologies that cannot be commercialized, their benefits will not be realized by the American people unless the government affirmatively does something. And those are places where you have to be really careful because if you wait too long or you aren't thinking about them, it actually holds up progress. So for us, we kind of think of these two buckets of work and make sure that for technology born in captivity, we're thoughtfully approaching how you can change regulatory structure to allow that to ultimately be safely deployed to Americans.
I mean, I'm thinking about the timeframe you've got if we're going to see this kind of extraordinary progress to AGI and ASI in 3 years.
Do people here in the White House understand the speed of that change and in the agencies? I mean, it's not a little bit faster, it's dramatically faster.
We're trying our best to bring people along to the new pace and velocity of change when it comes to technology. And I think the best sort of manifestation of that is our Genesis Mission. This is where the president stood up with the Secretary of Energy and with me and said, "Look, the most important thing for the nation is to make sure that we're applying this unbelievable technology called artificial intelligence to scientific discovery." And it's not just at one agency; it's across all of government. And I think those are the types of actions kind of from the White House level that are the only way you can really push this down into agencies. But I will say, in most cases, government is not sort of the leading force in the cutting edge of where technology is, and that's going to be obvious.
We've seen recently AI ministers be appointed in various nations. We've seen out of the Emirates 50% of the government operations being driven to AI. We've seen in Malaysia, I think it was, the president has an AI representation be able to speak in all the languages. Do you see that potentially happening here in the US in some fashion on the government side?
I don't think so. What I've always thought about AI policy—and this was sort of kind of our view of the world beginning in the first Trump administration where President Trump signed the first executive order on artificial intelligence in history in 2019, so this was years before ChatGPT and years before it was kind of on the front page of every newspaper—I think our general view and how we think about generally AI regulation is that AI is a technology that is going to impact every agency. Whether you're flying drones, whether you're doing AI-powered medical diagnostics, whether you're at the SEC and working on financial services, AI is going to impact every single one of you. The idea that you can sort of centralize that effort in one person and be able to get the right and best policy answer across all those domains, I think it's a tall order.
I completely agree with you. I guess the question is: will we see AI enter the government in terms of advising on policymaking or advising in cabinet positions where there's sort of an AI instantiation of that member of government to be able to counsel at the speed that we're seeing?
I'm not sure what the future holds, but at least in the short term, what I would hope is that all of our agencies can actually even start using AI. I will say we're sitting in the White House complex today, and currently large language models are not allowed for use on our system here because of the Presidential Records Act. But hopefully we'll change that soon. But that's an example of the pace at which sometimes government tech operates.
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You and I both know that AI is the engine fundamentally that's going to uplift every American, every aspect of an American's lives. And I think we both feel that very deeply, right? The challenge of course right now is that three-quarters of Americans fear AI. Those are the numbers right now. 71% of Americans oppose data centers near their homes, which is a larger percentage than object to nuclear power plants in their neighborhood, which is insane. So I guess, you know, one of my missions is helping people see the optimistic future, reduce fear. So I guess the question is: how does the administration get out in front of this? Why is there so much resistance? How do we demystify AI? What's the conversation going on around those concerns?
AI has a massive PR problem. And I think AI companies realize that. I think everyone that's sort of adjacent or orthogonal to the industry realizes that, and it's a problem. You and I know and deeply believe in our core what great things AI can do and bring to everyday American lives. But I think back first off to how did we get here, and I think back actually to the first AI Safety Summit that was held by the UK government in Bletchley Park two years ago.
Way back. Yeah, two, three years ago. It's all sort of blurry. I think it was maybe the year after ChatGPT came out. And I think what was so fascinating about that when I attended it, almost the entire concept of it was wrapped around fear associated with AI: "What could go wrong? And we collectively as the smartest people in the world and the most important government leaders must come together to make sure that these harms don't impact the world around us." And I think that's an example that the narrative for so long coming from government prior to President Trump has been so fixated on the negative impacts of this technology. Like, of course people are skeptical. The only thing they're hearing from politicians and from people in industry is that there's going to be a bunch of job losses and everything is dangerous and maybe there's going to be bio-risk. Those are the things that people get worked up about, and it shouldn't surprise us that the PR is bad. So for us, you ask kind of the positive take on it, I think we try to look for areas where Americans actually connect with AI in a positive sense, and by far what we have seen, it's in the healthcare domain. And that's where, if we can actually show the impact in changing the way that individuals themselves get healthcare, their families get healthcare, those are the places where I think you can start to push back a little bit on that narrative.
Is there any effort to try and change the narrative from a centralized sense? It kills me that the narrative in China is the flip of that, where 80% are pro-AI. And I just want to get out and shout from the rooftops, like, you have to understand what's going on. Where does that responsibility lie? Probably in the AI labs, sure, but does the administration have a place in that as well?
I think the government can serve as a convenor to bring to the surface all the great stories that are going on around this industry. And I think sometimes we think about AI in a little too narrow of a sense. AI is having this dramatic impact in manufacturing, in hiring across the country, in these huge buildouts that are happening for everything that's sort of supporting the AI industry. These are great stories. I just heard from Jensen—he was here and he was talking about kind of the supply chain that supports Nvidia. He said that the order that he's put into Corning for the chips that he's going to be building in the future is the largest order in the history of Corning. And they're going to be producing more than they ever have in history just because of his—
Yeah, it's lifting up the entire GDP of the nation in an extraordinary fashion.
And those are the stories that should be told. Factories are being built, people are being hired, stuff is being produced. And I think those are the things that can connect with Americans.
One of the biggest fears is AI-related job loss and AI-related loss of incoming jobs. I report on this on Moonshots every week or so as part of the conversations we're having. And it's confusing because there's a lot of people who are putting forward data: yes, there's job loss, yes, there's these layoffs. And others who are feeling like, no, we're going to see more job creation like we've seen with every technology so far. Do you have a sense of what you believe is—
Personally, in the long term, I'm very optimistic about the impact that AI is going to have on jobs. I think we've been thinking about this problem, or I have since the first Trump administration, where the narrative around AI was around automation and there were fears about all this automation-related job loss. If you even fast-forward through that period, that was never realized, and only employment has increased. But I do think it's something we have to think about, and I think we've put in some programs that start to hit at this problem. One of the things that even you mentioned, the data around what is actually happening is not very good. We're trying to launch an initiative at our Department of Labor that was actually called for in the AI Action Plan, where we want to start collecting better data on the impact that AI is having on the labor force. So you can collect data from players that typically don't submit their data to the department, and through there, you can actually start making the right decisions on where to do better reskilling, retraining, and where to sort of do more targeted labor assistance programs.
I remember one of the conversations we had in Miami over lunch at the FII summit was the idea of sort of a parachute program where you incentivize companies, if they are doing an AI-related layoff, to give the employees they're letting go AI upskilling so that they get trained into that environment. Do you think something like that might materialize?
Every company will think about it differently. I do think opportunities like that are interesting. I'm still trying to wrap my head around what an AI-related job loss even really means. I think a lot of folks these days, when they're doing a layoff that they would have done anyway, just like to assign it or blame it on AI because it plays better in the—
And their stock price goes up if they are producing more revenue with fewer people.
On the notion of fear, because it's one of the things I'm always trying to quell, right? Because fear is an awful place to face the future from, especially at the speed of change, and people don't understand AI enough to understand its implications on their lives. We just launched this year something called the Future Vision XPRIZE. It's the world's largest film competition for creators to create a film that shows a hopeful, positive vision of the future where technology and AI is working together. Because part of the challenge for me is that films like Terminator, Ex Machina, Black Mirror—the majority of all the sci-fi films out there are dystopian. And if that's what we're teaching the average American, like, this is what happens when you have robots and AI. So my question along those lines is: do you have sort of a longer-term compelling vision of what you think America could be like on the back of this AI revolution, beyond just better healthcare from AI, which is low-hanging fruit, agreed?
Does that future visioning happen here?
We think about it more in the terms of national missions, which I think we'll talk a little bit about in Golden Age. My general take is we as a government need to be opinionated about what the most important things are for the future of our nation. And there was an era, beginning with the Manhattan Project, going through Apollo, that we had big ideas, we had bold things around them and it motivated young people to go into science. We were looking at a North Star of something that a lot of people thought couldn't be done, but we did it. And I think there are places where we can do more of that. An example of that is all of the space-related efforts that I think you talked to Administrator Isaacman and Jared about very recently. I mean, we're putting man back on the moon in '28. We're going to build the first elements of a lunar base by '30. We're going to put a nuclear reactor in space by '28. I mean, that's crazy. If you told someone, "We're going to put a nuclear reactor in space that has enough propulsion power to send folks to Mars in the next year and a half," that's nuts, but we're going to do it because we're Americans and we can accomplish that. That's so special. And I think that, plus some of the other national missions, can kind of—
Why don't you name—we'll get to them later, but name a few of those big, bold Manhattan Projects, Apollo programs.
The other one is sort of the Genesis Mission, which is our AI for science mission. We essentially want to double the productivity of the entire scientific enterprise in the United States over the next decade, and that's going to have an incredible amount of fallout results there. The third one that the president directed through an executive order is to create a scientifically relevant quantum computer by the end of his term. And this is finally saying, we appreciate and think it's amazing that this incredible basic research has been done in quantum for so long, but we're going to put a stake in the ground and we're going to say we're going to build this machine—
And have it do something.
And have it do something. Yes.
Do you have a sense in the quantum world, because quantum supremacy and all these terms have been as loose as AGI and ASI, what do you hope the first functional, capable quantum computer is able to do? What industries are you impacting most with that?
To me, sorry to keep going back to health, pharmaceuticals is where I'm most excited about. I do honestly believe that the types of calculations you can run on those for the particular molecules and things that you want to apply toward drugs is going to be pretty transformational. And kind of the last one, which is outside of our term, which I think is important for us to keep thinking about, is fusion energy. People have been saying it's 10 years away.
They've been saying it's 50 years away.
50 years away forever. It's always so many years away. But the Department of Energy put out its latest iteration of kind of our national strategy a few months ago, and I don't think any time in history have we had more private sector investment in this particular energy source than today.
My last count, there were 37 venture-backed fusion companies, which is crazy.
So I want to take a moment because it's timely to talk about the conversation that's been sort of dominating X and the AI sphere in DC, which is the open source versus closed source activity, right? So Jensen comes out with the Open Secure AI Alliance. Where is the policy today? How important is it for American companies to develop top-tier open-weight models?
It's very important. As an administration, we believe that the US must lead the world both in closed and open-source models, and that the best thing for the country is that we have a vibrant ecosystem on both sides of that coin that's able to support any type of customer that wants to work on AI or use AI. Right now, I think our open-source ecosystem is one where we could be doing better. We have a couple of very well-known startups that are extraordinarily well-funded that are pursuing getting close to the frontier.
Morad's release was amazing.
Terrific. I think we're waiting on Reflection for their model later this year, from what I understand. But I think that the ecosystem and the tooling around open source continues to get much, much better, and the US is continuing to be sort of the default harnesses and tools around open source. But to me, and we expressed this on the first page of our action plan from last year, the US has to lead on open source. And right now, look, I'll be honest, the Chinese have very well-performing open-source models. And if you're an American entrepreneur and you're cash-strapped and you're trying to bootstrap your company and get started, I can't blame you for using the cheapest model out there, and at this moment, it's Chinese. But over time, I think we'll be able to cultivate a pretty vibrant ecosystem here.
Yeah, that's what America does.
The Financial Times reported that Beijing is out in the world exporting open source basically as an instrument of influence and going to the Global South and providing them access to infrastructure and capabilities. One of your stated goals in the AI Action Plan, which I love, is the world should build on America's AI and tech stack.
And I think fundamentally, because a lot of people are going to use the frontier AI, but the vast majority of the world is going to use on-prem open-source models. How does America think about that? Maybe this is not necessarily your realm, but I'd love your thoughts on that.
No, we think about this a lot. To operationalize what you mentioned in the AI Action Plan, we launched something called the American AI Exports Program. The vision behind it was: look, we have the best AI stack in the world. We have the very best chips in companies like Nvidia and AMD and many other new entrants. We have the best models that we all know about. We have the best applications. And if you're a customer around the world, if you're a government or if you're someone in the private sector that's looking to build AI, there is nothing better in the world than the American stack. We launched this program at Commerce, but it's now become a whole-of-government effort where we put out an RFP and we said, "Great American companies, come back to us with what an American stack looks like and submit those proposals to us." We're now looking at those proposals and ultimately we're going to create essentially turnkey American AI stack options for the world. Then we'll back those with the government financing organizations that can make them economically viable for a lot of countries around the world, so organizations like the Export-Import Bank and the Development Finance Corporation can provide financing to make these more economical.
A complete package. And I think that's something that a lot of governments and a lot of folks around the world want. For them to have to choose seven different vendors to set up their stack, that's probably not what they're looking for. The other appeal that the US has right now is everyone wants our chips. We have the best chips by far.
He wants our chips, yeah. And between the export controls we have in place and other factors that are going on, particularly on EUV, our lead over where the best Chinese chip is continues to increase year over year. So from a foundation of the stack standpoint, we'll continue to have the best product. Now, I will say this AI export program was born because of a lot of the frustration I had in the first administration with Huawei and our inability as the United States to counter some of the actions that the Chinese were taking on telecom, because they had a good enough telecom stack that was run by Huawei and they had it super-subsidized by the PRC, and they went out and proliferated it pretty quickly. I think we're at a moment where we want to avoid that. To us, we have a pretty vibrant open-source ecosystem ourselves, but our open-source solutions plus our closed-source, in addition to the chips we have and the great American applications that everyone wants to use, I think will make our stack more competitive.
Do you think the restrictions on Nvidia's chips to China in retrospect might have been a mistake? One of the things that we've seen in the past—we saw this in the launch vehicle industry, in the satellite defense industry—that when we start restricting our exports, it simply cultivates the competition to build their own capabilities and they come back and compete with us.
I don't think so. I think that was probably one of the savviest decisions that we made as an administration, and I think it was probably one of the most impactful in being able to throttle their ability to make competitive models to ours. My personal belief is that it's been a priority of Xi Jinping to have a competitive semiconductor industry for a long time. It started certainly in Trump 1, and that's why the EUV lithography export controls were so critical. I would say that is probably one of the most impactful export controls in the history of the United States if that hadn't been done in 2019. And because of that, their ability to create their own competitor to our leading-edge chip has really succeeded.
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I think we have to do more of it. I believe that one manifestation of AI that is going to be critical for future success of the country is robotics. As you probably saw, we took some pretty dramatic action around humanoid robots just this week where we essentially limited the importation of any non-US humanoid robot that hasn't already been shipped going forward. And I think that shows how important it is to us for the US to lead in this domain.
Homegrown industry, and we have to start building the supply chain to support this. We believe as an administration that these robots are critically important for the future of the country, for advanced manufacturing, for so many other things, and we have to build that supply chain muscle to be able to have the supply chain security in the future.
Do you see capital going to these companies to accelerate that capability?
I do. I do, and I think the best example of that is we took a similar action around UAS or drones in December of last year. If you look at the numbers of the investment that went into essentially drone supply chain action, pretty dramatic, and I think that is kind of what we hope to see here. And I think this industry needs a bit of a push because, just like so many other places, I think that the Chinese are certainly subsidizing and dumping on robotics.
So I want to return for a second before we head to the new Golden Age and Genesis Mission to the speed of change. A mutual friend, Elon, friend of the pod, when I interviewed him a few months ago, he's like, "We're going to see double-digit growth in the GDP in the next 18-24 months, triple-digit growth in 5 years." And then he was on The Economist—I don't know if you saw the clip—saying, "We're going to be by 2036 basically post-capitalist. Anything you could possibly want will be delivered by AI and robotics." Now, honestly, I think Elon is the most brilliant engineer on the planet. I think most everybody agrees on that, and his predictions are always directionally correct. The timing may be off a little bit, but the speed of change that he's projecting sort of breaks every system. And I'm just wondering: could you imagine that speed of change? And are the appropriate members of cabinet thinking about what the economy looks like in that situation?
It's hard for me even to kind of wrap my head around that velocity of change. Maybe I don't quite ascribe to that particular speed, but I do think things are changing and I think our cabinet and the leadership in the White House recognizes that and is getting in front of it. As you probably saw, Secretary Bessent was very involved in some of the post-Mythos activities that happened in the USG. And I think that's a great example of saying, "Look, if we have a super-capable cyber model that in the hands of the wrong actor could pose a risk to our systemically important financial institutions, we have to approach this seriously and quickly." And we addressed it, and I think that's the kind of action that you see a lot of the leaders in the administration taking when it comes to these rapid changes.
All right, let's turn to Genesis and Golden Age. In your paper, you outline a series of challenges that need to be solved in the age of AI, and I'd like to hit on each one one at a time because they're really important. And just again, as I was saying before we started here, I was a kid in the candy store reading the Golden Age Report. It was like you went much further than I expected sort of naming ideas, and we'll get to those. So the first point you make is that scientific productivity has been declining despite larger budgets—Eroom's law, right? Moore's law spelled backwards. That sort of discovery per unit dollar has dropped. Why? What's going on here? And we've got better tools.
To me, I think we have been unable to change the way that we conduct science. And I think this goes back to one of the main reasons why we wrote this report. The president wrote me a letter after I was confirmed and essentially charged us with: how do we revitalize the science enterprise? We went back and we kind of thought about it, and the data that you talked about, this declining productivity, was one of the first things that we looked at. And we asked ourselves: why is it that we have better technology than we ever have, our budgets are more than we ever have—and I think it's most probably relevant in the biomedical field where the NIH budget now has ballooned to almost $45 billion, yet the cost of drugs is more expensive than ever, and kind of the list goes on. One conclusion we had was we just are not experimenting enough in the way that we conduct science. We're doing the same thing over and over again and just putting more money towards it and believing that the outcomes are going to get better. One of the main core theses of the whole Golden Age Report is we have to be more experimental and more ambitious about testing out new ideas. And why I found it so particularly relevant and shocking in the world of science is you would think that in science, those people would be the most interested and the most excited to try different ways of doing science. Yet funny enough, that community doesn't want anything to change. They want the system to be exactly the way it was 30 years ago.
Yeah. The way I say it, if you're an expert in something and there's a revolutionary breakthrough, you're no longer the expert at it, so there's a disincentive for doing that. Could it be regulatory bloat? Could it be legal bloat? Could it be just the paperwork that's developed over time?
It's all the above. Some things that we talk about in the report are around research burdens. There was a very well-known study that the National Academies put out a few years ago that essentially said something like 45% of the time that a researcher spends is to do the administrative work associated with their grant. And that is one of the most depressing statistics I can think of. These scientists are the crown jewels of our country. We want them to be doing their work 100% of the time.
Same thing in healthcare. Physicians are spending all their time filling out paperwork.
Yeah, and I think that the regulatory stuff does kind of matter, too. One example that is very close to my heart and has been one of my pet projects for a long time is: how do we bring back supersonic flight to America? An example of that is a regulatory issue where in the US there has essentially been a speed limit for flights over land. Essentially, if you're flying over Mach 1, it's just not allowed anymore.
Because of the sonic boom and concerns, right?
And the reality is, research has shown, and Boom Supersonic, a company, showed that they're able to fly over Mach 1 without creating a sonic boom. So our regulations, the way it stands, disincentivize them from ever trying to fly over Mach 1 because they'll never be able to. So, again, due to the president and an executive order that he signed, we are now changing that rule to create a noise limit rather than a speed limit. If you can keep it quiet, fly, just fly.
I love that. The policy changes on both supersonic flight and on eVTOLs, the aviation industry had been stuck for 50 years, and so unleashing it in that way. One of the second challenges you note here is young talent waiting too long before they're given a chance to implement their bold ideas, that our funding, publishing, and credit system was built for a world of human-paced discovery. And I could not agree with you more.
The challenge a lot of young people face is they're kind of stuck in this zone of the way science was done a long, long time ago, before the internet even existed in some ways. Everyone is kind of stuck through this process of needing to do research, and then trying to get the research published in a journal, and then you have to do that a number of times before you can get tenure, and so on.
This structure tends to, I think, not be the way that is conducive to discovery. It's the way how you succeed in sort of a structured system, right? Yeah, and I think there's huge opportunities to kind of reform that. To me, I think NIH is always an example of this, and I think this is very bipartisan. A statistic I heard today which was shocking is that the median age of an intramural NIH scientist—so this is a scientist at NIH who's doing research in NIH, not getting a grant out—is 71.
When I heard, I couldn't even believe it. That is crazy. And you know, the average age of a Nobel laureate's prize-winning work is in their mid-20s.
In their 20s. Yeah, precisely.
And I think we've created these systems where we're somehow okay with that. And then we look in the mirror, and somehow we tell ourselves, well, everything's doing great if we just give it a little more money. And it's like, that's not how you solve these problems.
And that leads to the bloat. So, you identified a bunch of great mechanisms for driving progress in the Golden Age report. I'm going to hit on four of them that I think I'm excited about. The first one is long duration grants.
