Michael Kratsios on the New Golden Age of American Science | EP #276

25:34It started certainly in Trump 1, and that's why the EUV lithography export controls are 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 sort of competitor to our leading edge chip has really succeeded. This episode is brought to you by Blitzy, autonomous software development with infinite code context. Blitzy uses thousands of specialized AI agents that think for hours to understand enterprise-scale code bases with millions of lines of code.

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26:53Visit blitzy.com to schedule a demo and start building with Blitzy today. Let's talk about robots one second. You know, I love robots. I've got my robots on order. We've got a number of great U.S.-based humanoid robot companies. but it's you can count them on your two hands compared to China with 150 plus humanoid robot companies and it feels like they've been really aggressively supporting them funding them using them in national events creating centers for robotic advancement and so forth when do we start doing that I think we have to do more of it. I believe that sort of one sort of manifestation of AI that is going to be critical of future success of the country is robotics.

27:48As you probably saw, we took some pretty dramatic action around humanoid robots just this week, where we essentially limited the importation of any non-U.S. humanoid robot that hasn't already been shipped going forward. And I think that That shows how important it is to us for the US to lead in this domain. Homegrown industry. Homegrown industry. And we have to start sort of building the supply chain to support this. I mean, we believe the 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 sort of build that supply chain muscle to be able to have the supply chain security in the future.

28:27Do 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, I think, in December of last year. And if you look at the numbers of the investment that went into essentially sort of drone supply chain since that action has been pretty, pretty dramatic. And I think that that is kind of what we hope to see here. And I think this industry needs a bit of a push because in just like so many other places, I think that the Chinese are certainly subsidizing and dumping on on 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.

29:08So a mutual friend, Elon, friend of the pod, you know, 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 five 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. We're going to have anything or 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.

29:46The 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 you know a could you imagine that speed of change and you know are is the appropriate members of cabinet thinking about what what the economy looks like yeah in that situation you know it's hard for me even to kind of wrap my head around kind of that velocity of of change but you know I maybe I don't quite ascribe to that particular speed but 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.

30:30I think, as you probably saw, Secretary Besant was very involved in some of the post-methos 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 I think you see a lot of 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.

31:10And I'd like to hit on each one, one at a time. Yeah. 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 is sort of naming ideas and we'll get to those um so the first point you make is that scientific productivity has been declining despite larger budgets uh uh irum's law right moore's law spelled backwards that's sort of like the discovery per unit dollar has has dropped why what's going on here we got better tools yeah i i to me i think we have um been uh unable to or um or or just don't don't unable to to change the way that we conduct science and i think this goes back to kind of one of the one of the main um sort of reasons why why we wrote this report.

32:13The president wrote me a letter after I was confirmed and essentially kind of like charged us with how do we revitalize the science, the science enterprise. And we went back and kind of thought about it and kind of the data that you talked about, kind of this declining productivity was kind of one of the, one of the first things that we looked at. And we asked ourselves, you know, like what, why, like what, why is it? Like 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, in the biomedical field where the NIH, the NIH budget now has ballooned to almost like$45 billion dollars, yet the cost of drugs is more expensive than ever, and kind of the list goes on.

32:45And I think one conclusion we had was like, 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. And I think one of the sort of the main sort of the 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.

33:20Yet, 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 in it. So there's a disincentive for doing that. Could it be regulatory bloat? Could it be, you know, legal bloat? Could it be just the paperwork that's developed over time? It is. I think it's all of the above. So some things that we talk about in the report are around research burdens. So I think there was a very well-known study that the National Academies put out a few years ago that essentially said something like 45 percent of the time that a researcher spends is to do the administrative work associated with their grant.

34:03And 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. Yes. Physicians are spending all their time filling out paperwork. Yeah. And I think that the regulatory stuff does kind of matter too. And I think one example that's 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? And an example of that is it's kind of a regulatory issue where in the U.S. there has essentially been a speed limit for flights over land.

34:38So essentially there was, if you're flying over Mach 1, it's just not allowed anymore. Because the sonic boom is concerned, right? And the reality is, I think research has shown, and I think 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 executive order that he signed, you know, we are now changing that rule to create a noise limit rather than a speed limit. If you can keep it under mock, if you can keep it, if you can keep it quiet, fly, just fly.

35:12I love that. I mean, the breakthrough, you know, the policy changes on both supersonic flight and on eVTOLs just to, I mean, the aviation industry had been stuck for 50 years. And so unleashing 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. Yeah. The challenge I think a lot of young people face is they're kind of stuck in this zone of the way science was done long, long time ago, before the Internet even existed in some ways.

35:52And 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. And I think this structure tends to, I think, not be the way that is conducive to discovery. It's the way to like how you succeed in sort of an academic setting. 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. I think 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 years old.

36:35Oh my God. When I heard it, 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 OK with that. And then we look in the mirror and then 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. I'm going to hit on four of them that I think I'm excited about.

37:06The first one is long duration grants. five-year grants funded on day one. Talk about that one, please. So to me, I think grant duration is something that people don't talk about enough. Again, over time, we've come to this sort of like zone of comfort where most government grants are roughly in the 18-month period. And that's just because of the way it works with academic calendars and just how easy or quickly we can, as a government, be able to review these grants and adjudicate them and give them out. But that's not the pace of scientific discovery. There are certain scientific endeavors that are quick and short and it's a small experiment that only takes three or four months to look at and you can get done.

37:44And there are other ones like you talk about that actually require a longer period of time. That you want a brilliant scientist to be able to explore an idea which is going to take a little bit of time to sort out. And focus on that versus another grant application. Exactly. Because most of these guys, after they've gotten their first grant, they're already working on their second before they even finish the work on the first because they have to keep the pace going. So to us, we believe that you have to, and this is again, how do we support scientists at the core of the entire new golden age report is everything we do is in service of the scientists.

38:18And this is a perfect example of it. It's like there are certain scientists that want shorter duration grants and there's some ideas that need five years to play out. And we as a government need to make our money available to be able to be in the service of those scientists are going to be making the great breakthroughs. The next idea you put forward, which I love, is fast cracks. A few pages, reviewed under a month, you know, sized for the proof of concept. Yeah. And I think we saw this and a lot of excitement around this. And we've seen this historically around times of crisis. And I think this really came to the fore in during COVID.

38:51And Tyler Cowen and others came together and pooled some capital and actually did this on the side themselves. We're making grant decision in a matter of like hours for people who are submitting to work on problems related to COVID. But there's no reason it should be restricted only in times of crisis. There are lots of ideas that if we're able to answer them, then that may unlock other things that we'd want to do later on. And I can imagine, I mean, a lot of these scientists are probably using ChatGPT or Gemini or what it might be to write their grants. And I'm expecting that grant reviews will also use AI as a mechanism.

39:26I mean, time should be massively compressed. I think so. And I think a lot of thought is being taken at a lot of our funding agencies about how we can kind of accelerate that while sort of at all times keep kind of that meritocracy and that merit-based review gold standard. Next one that I loved was experimentation with golden tickets. So what's a golden ticket? Yeah, I think another issue of like back to your question of like why we stagnated. I mean, one reason a lot of people say is like we're just not risk taking anymore. We sort of like the least common denominator ideas are the ones typically get funded.

39:58And people who have kind of out there ideas, crazier ideas, things that may not work, but if they do work, it's pretty incredible. They're just not incentivized to even submit that application because they're not going to get the award. So the question is, like, how do you get around that? How do you incentivize people to be a little more out there? And one is this golden ticket idea. And the concept here is that on a merit review panel, you may have three or four people. each person on the panel gets one, two, three golden tickets. And with a golden ticket, you unilaterally can make the decision to fund a particular grant, independent of what the rest of the committee thinks of.

40:33And because of that, you get two things happen. One, you incentivize people to have a little crazier ideas because you have a chance that if one person believes in you, you'll go forward. The other is I believe, and I think this may be the even better outcome, is you incentivize better people to be part of the review panels. Because they have power. Because you get a golden ticket. So rather than having these people that are sort of like, you know, I don't know, mid-tier people who just do this, you know, for I don't know what reasons, you kind of can bring even better people in to kind of do the reviews.

41:02I do love that. You know, it's interesting. I was talking to a professor at Harvard, I won't name him, who has been extremely successful. and he was saying that he was getting dinged in his reviews because he had gotten too many grants and was too successful and they needed to give other people a chance yeah um the whole peer review process is uh is something that is unfortunately extraordinarily broken you know define a break the day before something is truly a breakthrough it's a crazy idea right so where are we experimenting with crazy ideas it's a challenge it is and i think we have Government, correctly, I think, needs to be a good steward of taxpayer dollars.

41:48And we have to be very thoughtful in the way that we develop our programs and we evaluate them. And I think one piece of Golden Age is this concept of metascience, the science of science, our ability to evaluate the ways that we're conducting science, the ways that we're doing funding, and evaluating whether or not they're working, and then course correcting when they're not. Like you and I in this podcast may really believe that doing fast track grants is a really great idea. But we need to run the experiment. Like let's do some fast track grants and let's see what are the types that work, what are the ones that aren't, and then update.

42:22And the next iteration of them is even better. And we as a government just don't do that. We never do metascience. So one of the things we call in golden age is to launch metascience units. And those have been announced at places like NIH and NSF already. Nice. Okay. My favorite idea. Yeah. It falls into the crazy idea. I can't believe Michael actually wrote this down. You described the use of prediction models, crowdsourced intelligent agents, and decentralized autonomous organizations to fund scientific research directly. I'm going to read a paraphrase from your report because I think it's very powerful.

42:58Imagine a scientific marketplace where funders post bounties for breakthroughs. AI agents identify promising leads, hire autonomous labs, and verify cryptographically signed results. Agents exchange data, hypotheses, compute, and funding through microtransactions, while smart contracts release payments as milestones are met. Prediction markets could guide grant makers. Bounty markets could direct resource towards unsolved problems. Then reputation systems could identify reliable agents. The system would operate continuously at machine speed, replacing slow institutional coordination with market incentives, while human experts remain essential for judgment and biggest results in deciding which scientific questions and breakthroughs matter most.

43:44What you're describing there is a complete fundamental AI native, AI agent up, re-imagining of the entire scientific process. Yeah. Look, this report gave us an opportunity to kind of dream big of where we can end up going. And I think it's something that is possible. And I think it really is. And I think what what we try to get at there in the report or I do is is I think incentives aren't always that easily aligned in the current system we have today. And over time, we have technical solutions to be able to bring those incentives together and to do the information sharing at a pace and at a speed, which will allow all things you just mentioned to come true.

44:23I mean, having DAOs involved, having agents run the cycle arguably millions of times faster than a human would, if not even faster, sounds like a mechanism that could make Elon's 2036 prediction happen. Actually come true. Well, look, my hope is that this inspires some folks. I think one thing that I've observed, and I think you have too, is the level of philanthropic scientific capital is greater today than it's ever been in human history. If you even just look at the OpenAI Foundation itself, it's almost a quarter trillion dollars in today's valuation. So to me, I think we have an opportunity for really smart people to try to push the envelope to try some of this stuff.

45:13And you've got folks like Yuri Milner, Eric Schmidt, Mark Benioff, all funding science directly. They're doing really incredible work. And I think when we think about, and I think kind of one of the underlying or main premises of the whole Golden Age report is that the science ecosystem has changed. In 1950 when Endless Frontier was written by Van Verbusch that kicked all this off, you know, 70 % of R &D was done by the federal government and 30 % was done by the private sector. And that has like flipped entirely today. The majority is done in the private sector and only about 30 % is funded by the federal government.

45:53Companies can take a 10-year horizon if they need to. Yeah, and I think what we see, and you have this flip with private sector being more involved. You also have philanthropy playing a bigger role. So now if you look at all the sort of pieces on the chessboard, people, there's, you can bring all those people together to drive scientific discovery in a way which you could never imagine in a system designed in 1960. And when we think about sort of take, for example, an announcement we made today about four-year PhDs, this idea that we want to get more PhDs out faster and actually have their experience during their PhD program, prepare them for a job in industry, not only in academia.

46:29So the idea that you have a private sector company that is paired with an academic institution to help a student pursue a four-year PhD, I mean, that's amazing. And that's something that is reflective of today's reality, not something you'd imagine in the sort of 1960s. All right. The last mechanism I want to hit on is the use of incentive prizes. So your report leans into prize challenges, advanced market commitments, pay for results, not proposals, right? And you cite the$10 million Ansari X prize in there. Thank you. I appreciate it. So I've spent my, you know, 30 years of my life focused on incentive prizes.

47:03And it's sort of my home turf. Most agencies haven't experienced this area, haven't learned how to use it. So XPRIZE right now, we've launched$600 million of prizes and we've driven about$30 billion of R &D as a result of those prizes. How could XPRIZE help your agencies? To me, I think it goes back to partnership. You know, if there are big national scientific endeavors that we need to pursue or problems we need to solve, I think there's opportunities to try to pull money together and make the prize even bigger and draw people to kind of solve these big challenges. Do you imagine that the government would put out like billion dollar incentive prizes or are these going to be small?

47:51Do you imagine on your grand challenges, you know, I'm talking to Elon about this. I said, let's launch 10$1 billion prizes that focus every grad student, every company. Like, these are the important things we need to achieve. You know, I think that the government spends about$200 billion a year in R &D. If you think about it, about 45, as I said, is kind of sits at NIH with biomedical. I think having a billion dollars may be a lot for a single prize for the government budget to swallow. but I think in the range of 100 million is certainly doable if the project is big enough, for sure. Speaking of large prizes, our largest XPRIZE right now, it's the$101 million XPRIZE Healthspan.

48:34It's a prize, we have 830 teams competing, and the goal is reverse your functional age by 20 years, give you cognitive abilities you had 20 years younger, muscular and immune system capabilities you had 20 years younger i have you know i fundamentally believe and there are a number of incredible scientists like david sinclair and george church and others who agree that if you wanted to impact the u.s economy uh the most in a positive fashion uh you would tackle aging yeah that if you could enable people to have and it's really health span versus aging you know today in the United States, the average life expectancy is about 78, 79.

49:19The average health expectancy is 63. So the last 16 years of your life, you're in poor health. If you could move that needle up, give people an extra decade of health, an extra decade of productivity, it would transform everything. I found longevity lacking from your report. You hit a lot of other great things but well now that you mentioned it uh we probably should have included it i i i think it's something that um that's critically important and i think it ties ties to just general health of americans and i you know we should we should find ways to work together on this and figure out what what programs the nih and other places can kind of accelerate that yeah a lot of folks believe aging is a disease that can be at least slowed if not not cured we had dario say that he could imagine doubling the human lifespan in the next five to 10 years.

50:14And Demis talking about curing all diseases within the next decade. And those are impactful. That is huge. I mean, I remember when I went to the first time Demis sort of told me, you know, cure all diseases in 10 years. I wasn't sure if he was kidding or serious. He's dead serious. And I think he thinks it's possible with where AI is going. Voice agents are just software, but software deserves a real development platform. I'm Nick Leonard, CEO and co-founder of Voice Run. Voice Run is your runtime and development platform for voice agents. On Voice Run, agents are built and configured in code.

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51:33so you know when i look at the six national technology missions that you named ai quantum commercial fusion lunar exploration robotics and next generation semiconductors all amazing i find biotech missing from that yeah is there room for that to come on there There is certainly room for it. And one card may have even been explicitly listed. I will say, I think a lot of the biotech work has been nested under the Genesis mission. So the first national initiative around AI for science. I think we announced about$5 billion worth of Genesis mission grants just last week at the Genesis mission summit.

52:12And so many of them relate to biotech. So I think it's critically important. That was a question my dear friend Alex, AWG, wanted me to ask. You know, my entire Moonshot mates, Dave and Alex and Salim, are jealous I'm here alone with you. We got to have him out next. I wave hello to you guys. Interesting. Some states and cities are far more pro-tech than others, right? You've got states and cities, and we just created a map. I'll show you after this that Max put together looking at this across the U.S. sort of, I call them singularity zones, right? Where they're pro-autonomous vehicles, pro-drones, pro-nuclear, pro-data centers, and so forth.

53:00Yeah. Do you imagine that you could see some type of regions volunteering to be innovation hubs where the regulations are sufficiently relaxed so that they can accelerate research? I mean, we see China doing this. I see other places in the world. Chile did this as well. Just to accelerate the work and actually have the entrepreneurs who are interested in that region move there to build their system. I would love that. I think we as an administration, I personally have been very, very focused on this as a way to drive innovation. The very first piece of paper that I worked on that I got the president to sign was in 2017 to launch the UAS IPP, which was the Innovation Pilot Program and Integration Pilot Program.

53:52And what was so special about that program was essentially, this was 2017, commercial drone delivery wasn't really a thing yet. It was kind of a dream that people wanted. But how do we accelerate that? How do we get people to actually start running the tests of like, what is it like to try to do deliveries? Where does it work? Where does it doesn't? When does it bother people? What like systems you didn't place them on the drones, all that. And the EO essentially called for the creation of this pilot program at Department of Transportation. And FAA then went out and picked 10 state, local or tribal governments that paired with certain UAS operators to run these tests.

54:26Well, you essentially had you had community stand up and say, hi, I want to have this innovative technology. I'm going to carve out and the FAA gave them sort of like regulatory clearance to be able to run these operations. And we've done that again in this administration with our EIPP, which is our eVTOL program. We're going to start seeing testing of eVTOL vehicles all over the country. So to me, I think this is really important. And if you remember back in the campaign of 2016, sorry, of 2026, sorry, 2024, the president also put out a number of videos around some efforts that he was going to be doing in Trump too.

55:03And one of them was actually around this. I think there was a whole narrative around creating these sort of innovation zones and cities where we can test these great new technologies. Yeah. I think on our evaluation state by state, Texas came out number one in everything. Yeah. Just very gross. It's very much it's very much an American. It's very core to us as a country. This idea of federalism in a way where, you know, states can can choose to make decisions and people will vote with their feet and companies will vote with their feet and go to places where they're most comfortable. I think back to this Elon conversation, I think we saw where a lot of the self-driving vehicles that were being tested in California up and left and went to Arizona when the rules changed.

55:45And I think that's a good thing. I think it's competition among the states. Regulatory arbitrage. It's a very powerful incentive for states. And I think some ways, and I think this dovetails a little with some of the issues on data centers, for example, where I think there could be a future world where you're actually going to be having communities competing for data centers. And we should be thinking more, at least the data center operators should be thinking a lot more about what incentives they can provide to the communities that they're entering in, such that communities are so interested in having them that they're commuting amongst themselves.

56:18And the president has taken a lot of leadership on this, putting forth what's called the Ratepayer Protection Pledge, where essentially directed all these big tech companies and AI companies and data center builders to build, bring or buy all their own power. And you're not going to go into any community unless you cover all the costs associated with it. And if anything, you're going to lower the costs of electricity. And that's what the data shows. Yeah. The locations with AI data centers are getting, on average, lower electrical costs. We have to address the water issue as well, which, you know, we've talked about a lot of times on the pod.

56:52You know, you know, golf courses have 30 times more water use in data centers and like almond farming farming is like 50 or 60 times more water use. That one is particularly jarring. Let's talk about education. It's it's quarter report. You hit it on chapter four. And as a dad of two 15 year olds, I am pissed at the educational system today. it is at least in the US still tied to the Industrial Revolution it's not tied for what's coming and we're seeing you know huge resistance of high schools and even colleges to to use this and it should be just the flip we should be it should be AI first across the board you know how do you see this being radically reimagined because I think it does need you know the the public health the public educational system is not serving the our kids future for the world that is racing at us to use Elon's term like a supersonic tsunami mm-hmm to me on education I think it's something that we think a lot about for a lot of tech tech domains.

58:07We always have to put, in my opinion, the parents first. And I think we should be providing parents options with the ways that they believe they can best educate their children. You know, there's amazing opportunities for people on one extreme to be participating in things like Alpha School, where, you know, you do, what is it, three hours or four hours of AI in the morning, and then the rest of the day is on sort of social skills and other stuff. And for some sets of families that works amazingly and people get really hands-on with this technology. I think there are other parents that prefer to have sort of like no technology in the classroom and they want their kids to learn the classics and they can end up, you know, learning about these other technologies kind of in other domains.

58:48I think what, but the reality we face today is that most Americans get neither of those things. They kind of get a broken middle that doesn't provide any semblance of a positive future for those children. There's so many districts around the country where you see that majority of students graduating from high school can't even do basic math. So I think we have a lot to improve in this country. And I think on my side, when I think about kind of how do you integrate STEM into these organizations, that's where my sort of portfolio usually goes. To me, one of the most sort of depressing things about sort of American in education today is just the declining number of American students that want to enter the STEM fields.

59:29And that's not good for our country's health, for our national security, for the future of our economic growth. Like we need people to pursuing these STEM degrees. And I think there's a lot that we can do from sort of a government standpoint to inspire people to go back into this domain and hopefully a lot of work that Jared's doing through space and so many other things. Yeah, I mean, the Apollo program, you know, is 100 % responsible for everything I've done in my life. Yeah. It was Star Trek and Apollo. I mean so but asking the school systems to change Over the course of the next few years, which is I think the time horizon to be talking about is extraordinarily difficult with teacher unions and and public education boards and so forth so you know I wonder is there an opportunity for sort of an AI educational overlay that becomes available where parents and kids who want that can do that in the afternoons or weekends?

1:00:26I think that's possible. I mean, from what I understand, the Alpha School guys, for example, I'd say they started with running the schools themselves in certain locations. And it's not necessarily that cheap. So there's only certain people that can participate in it. But I think the goal is to be able to essentially open source the software or make it economical for anyone to kind of run those programs. So in my sense is a lot of that stuff is happening and hopefully there'll be lots of options for parents who want to pursue that. Okay. All right. Another fun topic, which I love, is the autonomous self-driven labs.

1:00:58So the piece of your vision is, and let me quote this, AI proposes the hypothesis, robots run the experiment, the model reads the results and designs the next one 24-7, no humans in the loop. Yeah. I mean, you're basically running closed loop science at machine speeds. Yeah, yeah. So this is something you and I talk about that Lila Sciences is doing. They're building out a million square feet. You're looking at having this retrofit into the federal labs. We believe that we should be building these and being able to use federal dollars to test experiments on these labs. To me, I think, and maybe you even know better, kind of a long pole in the tent on some of this stuff is actually building the hardware that can run sort of a wide range of experiments as you would want.

1:01:55So I think we'll probably start more narrow domains and then expand as the actual hardware comes itself. But I think that's a future that we want to try to achieve. I mean, I think that what has held a lot of scientists back is just how long it takes to run the experiment. And if you have a vision and you want to test it, wouldn't it be great if you could just go online, put the hypothesis in and hit go and then start thinking about the next one and not needing to wait. And I love also the vision you had where, you know, a high school kid could potentially do that. A college kid someplace could get access on national lab equipment to run the experiment.

1:02:30I remember in high school, you know, there were a few kids who'd always found some way to like meet a professor and somehow get to the university and after school run experiment or get in the lab. And I think now this just democratizes it and it gives it a huge opportunity for anyone that has ideas to be able to test them without the overhead and the burden of a lot of the institutions that hold the keys to the infrastructure. So if this vision gets implemented, one of the questions I have is it is fundamentally doing what a traditional research university does, right? So I've spent in my 10 years in college and graduate work a lot of time in the lab designing experiments, pipetting, plating dishes and so forth.

1:03:17And the idea that it could be done. So do you imagine that this autonomous lab capability is effectively going to also retrofit into the university system? I think universities are going to be probably one of the first folks to build these labs. I think they want to they want to provide the tools to the greatest America. They want to provide the best tools to the great scientists that work at their institutions. And I think they would be doing a massive disservice to their to their academic community if they don't don't have these as resources. To me, I think if you're an administrator at a university, you want to provide the greatest resources possible to your scientists.

1:03:54And I think these are going to be what everyone's going to be demanding. All right. I'm going to wrap this up with this question. And I want to go deep on it. In your report, Genesis talks about doubling productivity. Which I guess historically might have been thought of as ambitious. mm-hmm you know in the moonshots world that I'm in it's like okay 2x is like auntie like you know how do we 10 exit yeah is it 2x because it's politically acceptable is it is it 10x is it 2x because you don't think 10x can happen yeah where do you see the limits here yeah when we were thinking about the 2x number that's actually a number from from last year when we were actually building um what ultimately was building the program that the president signed as a genesis mission in in december and um and it's funny you say that because i've been sort of noodling on that actually myself for quite a few months now and as we were we were finalizing the report i think we had even a conversation internally about whether or not we should rethink that but we sort of already stated that publicly so wanted to keep running with it um my sense is um you know government is is one of the hardest institutions to to change and to move yeah it's linear at best it's linear at best and i think you know elon learned it firsthand and and did and did god's work here to to help help the country um to me i think we should probably aiming for 10 and to be honest with the transformations that have happened in in in ai even over the last six months we should definitely be definitely be pushing for 10 um and and i think even if you if you think back to sort of early this year.

1:05:37Opus wasn't even out yet. Anthropic revenue was at, what is it, 10 billion? Yeah, it was sub 10 and now it's at Opus. Exactly. Fastest growing company on the planet. Yeah, it's unbelievable. And that's just in the last seven months. We also had sort of the mythos moment and sort of the fable release. OpenAI has been releasing their new six model very soon i mean that that the pace of innovation on ai is just is just insane and uh and and i think we uh we got it we got it we got to aim big we got to do 10x i'm looking forward to that correction report uh alex wiser gross and i wrote a paper called solve everything it said solveeverything.org we look at how do you structure the situation such that ai is able to you know it's already to use alex's word cooking math right map as a discipline is being wholesale solved over and over again we're seeing every week reporting on new new breakthroughs new proofs being uh being either dismantled or or proven uh but on the heels of that comes physics chemistry biology material sciences and at least we imagined an inflection point right where you know gpt-6 and whatever follows for uh for anthropic and whatever grok becomes especially now that elon's you know uploaded all of uh spacex's engineering data which was a you know a baller move um we see an acceleration in the rate at which science is fundamentally uh you know sort of i don't say other words accelerated that it's stunning to people.

1:07:25That's what I'm excited about. That is why we did the Genesis mission. You know, we believe that every scientific domain, whether you're in chemistry or physics or math or biology, you're going to see this dramatic transformation and acceleration of discovery and hypothesis testing. And that's going to be because of AI. And for us, and, you know, to unlock that, and back to your question about, back to your note about uploading the data to Grok, our whole insight was that the US national labs have a tremendous amount of scientific data across a wide variety of domains that have not been made AI ready, that have not been uploaded to models, and have not been part of the scientific process.

1:08:04And we have this huge opportunity before us to actually bring all that great data from 70 years of scientific discovery in the US into an AI model to be able to accelerate discovery. By the way, when that data gets brought in, let's say wholesale health data from NIH and such, and breakthroughs occur, does the value of that breakthrough in order to the American people, who gets to get the financial benefit from the breakthroughs that come out of federal data? So I think those are public goods. That's data that is a public good and anyone can use it. Think of it kind of as like as weather data.

1:08:45One of the big sort of actions that the federal government made many years ago was to make all of our weather data from NOAA freely available. So now all these apps are built on top of it. Your weather app or anything else essentially runs on NOAA data. And I think we believe that, you know, taxpayers have been funding unbelievable science at DOE for decades. And let's make the most of it. Okay. One more side question. President Millet, Argentina, comes forward and says, we're going to, no taxes on AI companies. We're going to enable AI personhood for agents here. A pretty aggressive stance. Yeah.

1:09:22I'm just curious, what was the internal conversation when that came out? Like, wow, good on him. We should join in. I think that was a very interesting take on where we're going. I think, I don't think we're quite at that place right now. We're not going to give AI personhood in the US yet. I don't think so. I think for us, what we want to focus on is making sure that the benefits of AI are actually realized with American people. And we have a lot of work to do to make sure that that actually happens. And the president has been very focused since day one to make sure that we continue to lead the world in this technology.

1:10:01And there's a lot the government can do to do that. But most importantly, we just have to kind of, you know, let our horses run. You know, we have the best companies in the world and we need to create a regulatory environment that allows them to just keep making the best breakthroughs in the world. Amazing. Michael, thank you so much, buddy. Thank you. This was so fun. Thanks for your work. Really brilliant. Welcome to the health section of Moonshots brought to you by Fountain Life. You know, my mission is to help you use the latest technologies, including AI, to not just do your work at home, teach your kids, but to help you live a long and healthy life.

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1:12:27Thank you.