Dean Ball on Joining OpenAI: Frontier AI Policy and Governance Challenges

Transcript

Hello, and welcome back to the cognitive revolution. My guest today is Dean Ball, who, as you probably already know, recently announced that he'll soon be joining Open AI to build and lead a new team called Strategic Futures, with a mandate to help open AI senior leaders shape front to your AI policy. The obvious importance of that position as we enter the era of recursive self-improvement with Open AI's own public timeline, calling for an AI research intern just three months from now, and a full-fledged autonomous AI researcher in March, 2028, just 21 months from now. Makes this one of the most self-recommending episodes that we have ever done. And because Dean was so generous with his time, we were able to cover a ton of ground. In the first section, we get Dean's Reflections on America's AI Action Plan a year after its release, and his perspective on the current state of the anthropic supply chain risk designation, and the moves that state governments have made in the absence of preemption. We also get his understanding of the Chinese government's decision to restrict the purchase of American ships. What he thinks is happening behind the scenes right now with respect to the ongoing fable land, and how much he personally misses fable as a user. We then turned to his reasons for joining a frontier lab now. He explains that frontier labs are a fundamentally new kind of powerful actor, which demand new policy paradigms, and also critically that the information they contain about the present and future of AI development is so differentiated that he feels he simply won't be able to do his best to work without access. He also describes how he understands his duty to open AI's mission of ensuring that AI benefits all humanity. How his team will relate to open AI's existing government affairs team, and while he emphasizes that he'll soon be learning much more from the researchers doing the work, he shares his baseline perspective on what recursive self-improvement is likely to mean, and the still neglected but critically important question of how to govern the internal deployments of the latest and greatest models. Along the way, we also get his takes on the corigibility first character debate. What happened between open AI and Alex Boris? The equity sharing talk we've recently heard from both Bernie and Trump. Third, the AI industry is already too big to fail and thus implicitly government backed. What sources of leverage AI companies have vis-a-vis the U.S. government? How he's thinking about working personally with Sam Altman and the role that individual personalities will play in shaping the future. What success looks like for him in this role and what red lines could theoretically cause him to quit? And finally, how he intends to use AI and also to refrain from using it in his work and writing, forward. Somehow amidst so many important issues, what stands out most to me is Dean Sense, which I share, that we are entering a main character energy period of history, a time in which individual human agency achieves maximum leverage in a few key places at least, before perhaps the machines ultimately surpass us. Let's start reality that forces each of us to ask what sacrifices and compromises we are willing to make to help shape the future. Dean, whose first son is not even a year old, will clearly be making some sacrifices as he reenders the arena. I have no doubt he will be working harder than ever. But importantly, he did not compromise his intellectual independence to take this role. To my present surprise, even as an open AI employee, he will retain the freedom to right publicly about AI policy, a freedom that extends even to this podcast, which definitely contains a few notably candid moments, but which open AI did not ask to review and has not seen prior to our publication. And so without further ado, as he prepares to join open AI for a career defining and to some degree a world shaping role, I hope you enjoy this frank conversation with the great, and increasingly powerful, Dean W. Ball. The cognitive revolution is brought to you by Mercury, the fintech that more than 300,000 ambitious companies and individuals trust to run their finances. I've wired AI continually every corner of my life, my email, my messages, my calendar. I even gave Mercury virtual cards to my agents, with low limits and category and merchant restrictions for their autonomous use. But still, my AI's access to my financial data has remained limited. With a normal bank, I might export a bunch of statements and have my assistant process them for me. But for real time, up-to-date information, and certainly for taking any action, trying to get your agent to use the bank via the browser is just too hard, too slow, and too error prone to be worth it. And that's why Mercury's new conversational interface, command, is such a big deal. It's built directly into Mercury, which means you get natural language access to your finances without exposing anything outside of your bank account. No exports, no spreadsheets, no pasting your transactions into third-party tools. I really think a lot of people are going to prefer it this way, and it can already help you take actions, too, with everything bound by the permissions and approval policies that you've already set up in your account. I am genuinely impressed to see this level of AI integration in banking in 2026. And so, I invite you to join me in the future. Visit mercury.com to learn more and apply online in minutes. Mercury is a FinTech company, not an FDIC-insured bank. Banking services provided through choice financial group and column NA members FDIC. Thank you to Mercury for supporting the cognitive revolution. And now, on with the show, Dean W. Ball, author of the Hyperdimensional Substack, welcome back to the cognitive revolution. Thank you so much for having me back, Nathan, it's great to be here. I'm really excited for this conversation, we've got some big news in your life to cover, and you've really been in the eye of the storm over the last year and a half, and so I have just so many questions of everything that you've participated in, your thoughts on where we are today. I'm going to try to go Tyler Cowen's Sila on you and just fire a bunch of questions and mostly you just want to hear from you on so many different topics. Are you ready for a podcast, friend? I'm ready. All right, let's start off with your time in the White House and a little look back on America's AI Action Plan. It was super well received at the time. How would you critique it now? Is there anything that you feel like you would change or do differently looking back at a conceptual or policy level? What you have to remember about the Action Plan is that I don't feel like there's a ton about the world in terms of how AI has developed, that has surprised me. Basically we're still in the basic, I kind of figured models with scary cyber capabilities late 25, early 26, and probably bio-sune after, and that was I publicly predicted a lot of this stuff. Basically we're living in the world that I figured. I think coding agents may be surprised me in terms of popular uptake on the positive side. I didn't expect that. But the thing is that D.C. wasn't living in that world. When the Action Plan was written, so the Action Plan is like this weird example. It's like this strange hermeneutics where you're writing a document now and your audience is the present-day audience, but your audience is also you're trying to model the same people, but in a slightly different near future where they're like 30% more age-high-pilled than they are today, and then 50% and then you hope that they go back and look at the document and are like, oh wait, I now read this in a totally different way now than I'm thinking about it in this way, right? But I think you could definitely criticize that as being an act slightly too much of five-dimensional chasse or whatever. It wasn't intended to be, it's just sort of like I think it was the nature of the task. I think the one thing I might critique is simply that it probably would have been good to be a little bit more explicit about, like, we are really talking about generalist agents that can do all kinds of stuff and like sort of trying to explain not just what that will mean for America, but also I mean a big part of what the Action Plan is all about is like, okay, this is happening, right? This is happening and the government's not leading it, and the government needs to figure out how to ride with the current of the river and use this to maximize and by view American primacy, American geopolitical power, things like this. While also understanding that the best way to do that is to be positive something and to try to grow the world economy and to try to bring other people in the world in on this. And I feel like the Action Plan doesn't really stitch that together all that well and probably reads a little bit more like, three dozen separate sort of thematic objectives, then it does one cohesive thing that is unified by a common strategy or a common vision. And I think probably if you'd given me two more months, I would have focused on that. The other thing I will say is the things we left on the cutting room floor that I feel bummed about. You know, one of which is I was really passionate about adoption in particular sectors and trying to talk about, okay, what are the doing the case studies and really specific industries and saying, all right, what are the barriers here that the federal government can do something about hospitals, right? Hospital record keeping for example, are there's very specific in the weeds things that the Department of Health and Human Services could do or veterans affairs and other ones veterans affairs, right? Amazing, one of the largest single-payer healthcare systems in the world. We don't think about America as having single-payer healthcare, we do the VA, huge amounts of data, huge amounts of direct medical care being provisioned by government employees. This is the kind of thing where experimentation with AI and healthcare could have been just enormously valuable. We just didn't have time, so I would criticize that as we could have been more specific there. So then you handed off the baton saying at the time that you're more of an ideas guy and it'd be left to somebody else who you think would hopefully be better at implementation and running all these things through the actual process of government. How would you say that is going right now? It seems like we clearly have like the build-out is happening and even in my home state not too far away in Michigan, there's a gigawatt data center just broke ground, despite some local nimbee style objections. So that seems like it's happening. We hear about the military trying to use AI obviously that's kind of contested in terms of what they should be doing. We also don't as a public, I don't think fully know what they're doing. And then there's all these other things. You're writing in the meantime has sounded the alarm in a pretty severe way around just the health of the Republic and it seems like you're kind of faith in government's ability to ride the wave as one might hope is not super high right now. So how would you say it's going in terms of follow-through and where what is the kind of core of that pessimism for you? I think if you looked at the individual items in the action plan and some of this is hard because some of the things on the action plan, some of the implementation ended up being done as they say in government on the high side, which means in classified environments. So especially some of the stuff about military adoption and there's some national security things. For example, one thing that I feel like is underrated is like not to say that this specific thing has been implemented, but just as an example of the kind of thing I'm talking about. There is a part of the action plan that obliquely references the notion of the military commandeering all the data centers in the country in the event of our national crisis where we needed to stitch them together to do dot dot dot something. Like that's like you know in there and like you wouldn't it sounds like a very like leopold ash and Brenner idea it was described insufficiently mundane language that I feel like it did jump off the page of people. But so there's a bunch of things like that where the implementation to the extent it's happening is not happening in public settings. But I think if you were to look over all and if you had clearance and you could really see everything I think you would see that we're probably if you just think of it as it to do list it's probably 30 to 40% done which is pretty good for a year right. Where we're about 11 months out from when the action plan came out so like that's pretty good. And a lot of the major things you know I think across all of the pillars we've seen significant advances that the administration is made on the energy side of things not that this was directly in the action plan but. This administration is doing really amazing stuff on nuclear and then stuff that was more directly part downstream of the action plan. There are major changes that are in process right now that should be announced in the coming days really from from FERC. The federal energy regulator that deal with the process for connecting very large industrial electricity users to the grid and accelerating that process. So there's a lot of things like that are just really meaty stumps into things that are proceeding a pace I would also say yeah military adoption of AI has impressed me to the upside and generally speaking also military's direct involvement in like. Really industrial policy and boosting startups US manufacturing which is talked about in the action plan startups that are doing innovative things with physical autonomy and stuff that is all doing great. And I think the other main thing is the action plan talks a lot about adoption more broadly and I think AI adoption in America is actually going pretty well all things considered. Now of course that's all the nice stuff I would say I think more critically it would be it would be hard to say that the administration has carried itself according to what I think of as the spirit of the action plan. Some of my job to say with the spirit of the action plan is ultimately it's their administration right for example a big pillar a big principle of the action plan was the notion of exporting American AI and getting it adopted all across the world. Seems hard to imagine how that's consistent with global export controls on frontier models imposed with a 90 minutes notice on the entire on all non US persons that's the kind of thing that when we were out in the world and you know. My my life after governments there are definitely a lot of international trips I do where I am engaged in quasi diplomatic work on behalf of the United States. As a private citizen but as someone who's trying to explain what we were thinking with things like the export promotion work and like our whole strategy there. And the biggest concern you hear from people abroad especially in Europe is I just worry that you Americans are going to turn off the models at some point if you get mad at us and when I was in government. We were trying to assuage this concern when I left government I spent time in India at the AI action summit earlier this year many places many it's quasi diplomatic engagements or is it don't worry we don't want to do that we want to ecosystem blah blah blah blah and then of course like. The administration goes and does it and basically confirms the biggest fears of a lot of people in internationally and that doesn't help right that certainly doesn't help. I think actually that that relates to one other thing which again I don't know if it would have been possible. But one thing that I feel as though the action plan was relatively silent on was like the issue of AI governance right that's a big part of what I worked on before and after and like it's not really that reference and I think my reasoning for it at the time would have been like. One tough overturn window within the admin at the time and number two a lot of that in my view is ideally legislative and the action plan was not supposed to talk about it was supposed to be just things the executive branch could do not new laws. So but I think that. There could have been more explicit material in the action plan about hey okay at some point things will get scary and what should you do here's how not to panic there could have been more of that because I think that we are seeing. It's funny though because in the end I do think. There's just a distinction right there like there's this huge array of civil service bureaucrats just like full time career civil servants and then there's low to mid level political staff. And they all read the action plan and are like implementing it I would say like in quite a good way then of course there's like the very high level people who don't necessarily read every strategy document that the administration comes out with. And like they're fundamentally very reactive and so this mytho stuff happens and it's oh my god we got to do something about this and they're not thinking about what with the action plan tell me to do that's not at all what like cabinet secretary is thinking but. Something that is amusing to me is that I am I think we are watching the administration. Um reinvent some of the ideas in the action plan are like the senior level people in the administration reinvent some of the ideas in the action plan around like the use of the. Casey building technical competence in the government all that kind of stuff third party evaluations all this I think we're seeing them reinvent those things from first principles so. I'm optimistic still but yeah, no, I definitely think that there have been substantial ways in which the administration has departed ironically in both the mat taking the risk seriously enough direction and then also in over correcting. And taking them not taking them too seriously, but like reacting in ways that don't actually deal with the risks and so you know look. In the end, I'm inclined to give grace to people and say what I hope that we're in right now is a high neuroplasticity phase of policy making and so I really I think that we might be in a very different world in three months but certainly yeah there have been ways in which like. If you were to look at the headlines you'd be like, oh it doesn't seem very consistent with the action plan at all and I can't deny that. Hey, we'll continue our interview in a moment after where's my sponsors. And now that this exists there's almost nothing that Claude can't help with. For taxis and I asked Claude to help me get organized. It went through my inbox, tracked down 1099s for all 10 of my part-time jobs and built me a comprehensive report on my expenses and donations. For my angel investing, Claude can now draft investment memos in exactly the form that my venture fund requires based on the calls I've had and the emails I've exchanged with the founders. And when someone needs a favor, Claude can often do it as well as I can. Recently, a friend reached out to ask if I know anyone who might be a fit for a role that he is currently hiring for. Initially, nobody came to mind, but then I thought to ask Claude and sure enough it identified two great leads. Claude is the AI for minds that don't stop at good enough. It's the collaborator that actually understands your entire workflow and thinks with you. Whether you're debugging code at midnight or strategizing your next business move, Claude extends your thinking to tackle the problems that matter. So, for problems we're solving, get started with Claude at Claude.ai slash TCR. That's Claude.ai slash TCR and check out Claude Pro, which includes all of the features mentioned in today's episode. Once more, that's Claude.ai slash TCR. So obviously, one of the biggest moments, and I don't want to rehash all the politics of this because you've commented on it extensively. But one of the biggest sort of freakout moments was when the Department of War declared anthropic to be a supply chain risk. And I'm struck by the fact that like, it seems like we're memory-holing that kind of. We're in this zone now where as far as I understand, many areas of the government were involved in using testing mythos. Like there's like a lot of anthropic at the government, it's still is what I kind of understand the situation to be. You're correct me if I'm wrong on that. How should we understand like where that whole supply chain thing is today, are we just going to all pretend it never happened or what? The broad way I would describe the American presidency really since Obama's second term is, you know, Obama famously said, you know, he was faced with an intransigent Congress to put it. To put it generously for him. He faced with the Congress that wouldn't do any, wouldn't pass any laws and so he said, fine. I have a family, so I have a pen and a phone. And so what he meant was I'm going to do executive actions. I'm going to push the limits of executive actions. That began a kind of auto catalytic process in which every president pushes the bounds of executive authority in various ways that get tested in the courts. And so what will happen very frequently is that you'll see a headline where it's like. The president did this thing that is unprecedented with executive power and it's being litigated. And then it goes through a very long litigation process and most people lose track of it. The walk still. But it's still going on, right? The topic had their trial. I went front of the DC circuit last month. And I think we're expecting a ruling in that trial. It's on point soon. And then after that, anthropic, if they lose, anthropic will appeal. That I'm quite certain. And if the government, the Trump administration is actually very, very, very savvy about when to appeal things. And when not to, when to, when to, you know, they're actually they're pretty good reading between the lines of, Okay, yeah, that was probably illegal. We're not going to appeal that all the way up to the Supreme Court because we're going to lose there. They're actually pretty good at that. But I think the Trump administration actually thinks they will win this case. I think so the litigation is ongoing is my point. And if it keeps, it would not surprise me if in the summer of 2027, we have a Supreme Court ruling of some by the summer of 27. There's a Supreme Court ruling of some sort on this issue. Even if that ruling is then denying to hear the case, which is the most common thing the Supreme Court does is deny to hear the case. That's also going on. In terms of government use, it seems as though basically after mythos, I think the message that, Was the anthropic received was, you, the supply chain risk thing applies to your contracts with the Department of War proper. And so I think within the Department of War they really are winding down anthropic. And have been considerably, and I think they probably wouldn't surprise me if they're 100% off of anthropic by the end of the year. Or a year from now or something. But throughout the rest of the government, I think the message was like the supply chain risk thing doesn't apply to any other government agencies. So if there's other government agencies that want to use anthropic, that's fine. There's also technically speaking the national security agency is a part of the Department of War. But it seems as though not only does the national security agency have a contract with anthropic, but if reporting is to be believed, the red lines around domestic mass surveillance, and autonomously the weapons were honored by the national security agency. And that's to me, that's a good, I think Americans are not that good at tolerating ambiguity. But like a little bit of ambiguity is, or maybe even a healthy amount of it is just, I think, an intrinsic part of this whole process. So yeah, it's still happening. The supply chain risk thing. It's still being litigated. I think anthropic contracts are indeed being canceled at the Department of War. And at the same time, I think other use of anthropic in the government is don't find. The US government contains multitudes. Yes. You were also, I mean, you were extremely critical of that whole situation. You were less critical, but still somewhat critical of the recent EO and the move, as I understand it, to take certain AI testing, characterization, responsibilities away from Casey, which I think now has kind of an uncertain future. I don't know what you think it's future will be. And move those responsibilities to the NSA, where they may or may not already be classified information. Why are we taking things as simple as it was like a Biden project and so we don't like it? Or is there more going on there than that meets the eye? And why are you concerned about the testing models you don't know exist against standards that can't be disclosed? Well, how do you think that turns into a problem for the public? Yeah. So the reason I'm critical of the administration here in terms of where they're going, I was critical of the cyber executive order when I was signed. Because I anticipated exactly this where let me just to level set for the for your listeners for just a moment. What is the cyber executive order do? One part of it is we're going to create a variety of procedures by which we're going to patch vulnerabilities and critical software systems. Great. Okay. Thumbs up. I don't think anyone can object to that. I think we can argue about how useful those programs are going to be and like how good the implementation will be. But we'll see. That's one thing. Second thing is it created a voluntary pre-deployment program a testing program 30 days before release whose details were to be classified. Primarily classified and primarily run by the intelligence community. And within that probably practically speaking, the NSA is the primaries as the NSA is the highest in terms of cyber expertise. And they really are quite excellent, by the way. Like, I think the reason my, I think this is setting up a potentially very bad future where access to frontier models is gated. It's all kept secret. And the public doesn't really know what's happening at the frontier. The government is making a bunch of decisions that maybe the public doesn't even know whether or not to restrict certain capabilities about what to do with those capabilities. And it feels to me like if you believe that what's happening right now is one of the most important things ever to happen in the history of technology. That not only does do I think just intrinsically as an American might into it might gut a strong gut instinct as the public has a right to know about what's going on. Number two, I actually just think that it's not some trade off. It's a better world where the public knows. It's a better world where the public knows and to the extent possible it's a better world where the public can access frontier capabilities. First of all, I think government monopolization of frontier AI is potentially how we get very scary outcomes from a civil liberties perspective. And that's not, by the way, that is a criticism I would make regardless of who the president was. If I didn't know who the president was, if you didn't know the party didn't know the name. If you erase that information from my brain and but I had everything else in my brain and you told me about this, I would say I'm concerned about that. That's one thing. Another thing is that dealing with a society and a civilization is a kind of information processing system, right? It's like there's like a bunch, all the humans in the country are parallel compute, right? And all trying to process what's going on here. And while there's a lot of, there's a lot of things we don't have good answers to yet. I actually do think that the community is like AI policy people has made reasonably good progress since 2023 in terms of, okay, how practically should we be dealing with models of the mythos level capability? And when things are public and there's a legislative process, for example, that is informed by lots of lots of robust public input. That's the whole design of our system, right? That stuff can make its way in and we can take advantage of this kind of parallel compute. When you centralize everything and make it private, it's much more brittle. And it's like a bunch of people who, as I said earlier, often don't have, they have a million things on their plate because they're high level government officials. They often don't have a lot of context for AI and they're just improvising, making decisions that an improvised fashion. And I think that leads to subpartition making, I think it leads to wasting time. Because I feel like what we're watching right now is the administration, speed running, the sort of mentality. They remind me very much of where DC was in the spring of 2023 when it was like. Chatchy BT had just come out and oh, we're going to regulate the hell out of this and this is really dangerous. And then things softened and maybe they softened a little too much and I just, but they still, they ultimately, we met in the middle. There was a change in the vibes that started in 2024 and I just think that right now we are going to like. By putting this all in the echo chamber of the administration with a pretty small number of voices contributing to things. The information and insight to things, I just feel like we're not leveraging the best that we have. And so that I think is the biggest problem and that's why I am critical and I am very worried about the direction of policy, but unlike the supply chain risk thing. The supply chain risk thing was like I think just totally an own goal. Just totally unforced error like why did you pick that fight? You didn't need to pick that fight. You could have fixed this in a million different ways. But that didn't, you could have dealt even if you take the government's concerns in that issue. Seriously, you could have dealt with that in a thousand different ways. This is more, yeah, I'm not surprised. I'm not surprised things are going about this way because you are building this thing. You're improvising an AI governance regime from scratch and it's being built by 20 people. 15 of whom don't have a ton of context for AI. I'm not surprised is working this way and I'm just pointing out the meta problem of yeah, we need to bring this out into the public. We need to have Congress involved. We can't just, this is not going to work. And so there's no point in being highly adversarial and critical there just because I'm not, what do you want them to do? What do you want these people to do? I don't blame them. But I do ultimately think that we need to make things more public. I'm the note of parallel processing. How about the role of the states are laboratories of democracy? A lot of the proposals that I understand that you have favored or even championed, including mandatory safety plan, publication, certain other transparency measures, whistleblower protections, and even a sort of fathom style, public private regulatory, you know, hybrid structure. I have all happened in different states to, I think a remarkable degree in a pretty short period of time. How bullish are you on the states? So there have been really meaningful wins for the general notion of private governance that I started to work on, really post SB 1047 veto in late 2024. And of course, other, and not just me, a lot of other people have worked on this stuff. Auditing independent verification organizations to be a third party private bodies that would like evaluate a lot of the thing right now, like with the government. They're concerned about the jailbreak. This potential jailbreak of mythos are fable. And it would be great if there were expert bodies who had looked into this and really probed and certified. Like, hey, yeah, like, there are jailbreakers. There are always jailbreakers, but are calculated risk is that this, these jailbreakers are not severe enough to rise to the level. And we can certify anthropic as conforming to safety best practices or whatever, right? It's like the kind of thing that I think there have been substantial wins. There have been substantial wins in the sense that two of the three big AI companies have published multiple documents that are favorable to this general notion. Anthropic and Open AI. Bill to mandate auditing in front of your AI companies passed in Illinois earlier this year. And also the state states of Connecticut and for actually the common, no, Connecticut state. State of Connecticut and Commonwealth of Virginia both passed earlier this year that are specifically authorizing either studies or pilot programs for independent verification organizations. And there's also a bill pending in Ohio, by the way, which would be the most robust implementations of independent verification. Or organizations yet. Oh, momentum in that regard more than I would have guessed a year ago. In that sense, I think the state's as laboratories of democracy idea is working fine. It's also worth noting with respect to the frontier AI safety laws that have passed that the states have taken great effort. There's been a bill in the transparency bill in California. It was SB 53 in New York. It was raised in Illinois. It was SB 315. And the language Illinois adds an auditing requirement. But the transparency language across those three states is remarkably similar, remarkably similar. And so I'm like, quite, I'm happy about that, right? That's not creating a patchwork. Those are the states converging on a common framework that we'll see if it works. We'll see how well it works, but it states converging on a common framework, which they do from time to time. There's a lot of other areas of AI that are not so much paid attention to on Twitter, that are not so much that don't get as much of the mind share. But where I think the story for the states is less rosy, things like consumer protection, Pride algorithmic pricing, the number of media, like synthetic media and deep fake laws that exist in this country now is just crazy, right? There's hundreds of them now. The net effect of that is probably to create a fairly confusing political environment. I think also one thing that's really problematic that we're starting to see bubble up from the states are basically occupational licensing protections. States saying, including Illinois is done this, is saying, you are going to define mental health services as exclusively something that can be provided by humans. And if you, if a chatbot so much as asked you how you're doing, it is engaging in, or if you say to the chatbot, I'm sad, can you please help me? The chatbot is technically engaging in mental health services and that's illegal. And we'll see states often vary in terms of how rigorously they enforce laws like this, but it's not good to have that kind of stuff on the books. And so I think strangely enough, the area that gets the most attention, the frontier AI safety stuff, where a lot of the pro preemption crowd also focuses their energy, the focuses their attention. That's actually the area where the laws are like best sculpted. Like the laws are like very well sculpted, they often have the support of the AI industry. They're often designed specifically to avoid the patchwork complaint, which is a legitimate one. And for some reason, up here to four, at least, most of the people that are like super pro preemption focus on these laws. And it's not only that, but these laws are dealing with really urgent problems like cyber and bio and stuff that are clearly not fit anymore. We can't, we're not having that argument anymore, clearly a real thing. So, and then they're like not focusing on all these other areas where the states actually are creating patchworks. And are creating complex compliance things that might specifically be really complicated for startups to deal with. And I think the state issue is mixed in that way, but also the people who are including me who support a federal law are not helping themselves. Because they're talking about this issue, I think, in largely the wrong way. One big surprise. I guess I'm first question, hi level. What have been the biggest surprises for you? I'll offer my biggest surprise. You can react to that and share your own. Big surprise for me is the administration eased the export controls on chips. And then, which wasn't shocking unto itself, but then the real shock is, China doesn't want to buy them. So we had all this debate around to what degree should we, you know, are we being delicacy? Or at least I was asking that question in trying to do these export controls. Finally, they get eased and China's like, eh, no thanks. We're going to just build our own industry and you guys can keep the chips. What's going on there? And any other surprises rise to that level for you? So that particular development doesn't surprise me that much because the China system is fair. And it's actually the realistically we are becoming more like China in this regard. But one thing about China is that when China announces a new policy, it's like, you need considerable expertise. And there are people inside the US government who specialize in this and they do not share their opinions publicly. But it's actually very hard to get good analysis on things like this in the public discourse. One of the things I miss about government. But it's like, what the policy says and then there's what they're actually going to do, which are importantly different things. So the policy, I think it's a matter of national pride for China that we are building our own AI chip ecosystem. And we don't need the Americans anymore. And they, I think they like sending that message to the world. I think they like sending that message to their own people and there's some aspect of that. Then there is, but then there's like what actually happens because while it's going on, China system has lobbying too. And I guarantee you that deep sea can all be baba and zifu and all these other people. I guarantee you that they're like begging. They're begging Beijing for access to American trips. And so the policy planners in Beijing are factoring that in and probably there's some amount that's being sold. I think that I think we now know that there are some ships being sold. But yeah, no, they're going to keep it. They're going to restrict it and that might be a big on goal on their part. Well, I guess we'll see. But yeah, I know, I think in terms of US China, nothing is especially surprised me. Yes, I would say anticipated that by now, in terms of China, I anticipated that by now the Chinese state would have woken up to the catastrophic risk issues. And that they would have pushed, they would have started pushing back on the open source strategy. I called it for, I said that by Q one of this year in in 2025, I predicted by the end of Q one of 2026 deep sea top model would not be open source. That prediction was wrong. I still think it's going to happen at some point, but we're not there yet. In the Chinese state seems more concerned about labor issues than they seem concerned about catastrophic risk. So they're like less cat risk build than I would have guessed if you had asked me a year ago. On the technical side, nothing is really surprised me. One of my hobbies is I pay attention to these weird subgroups of the very normal people who use coding agents. So there's this community of home schooling moms who love cloud code and open cloud and stuff, and they're like using it to do okay. It's I love that. I wouldn't really have guessed the coding agents becoming so popular. And then the only other on the technical thing, the only other thing that really surprised me, I did not expect the world sim stuff in the on the physical world, the sort of models where you can stimulate a 3D interactive environment, basically like creating a first person open world video game. But for arbitrary settings in the real world, I did not anticipate that that I because the way those models worked for a really long time was they were very dreamlike. Well, I could create the world, but it was like the neural network is creating it in real time. And so if you turn around and look at something and then turn away and then you go back and look at that thing again, it's totally different, right? It doesn't have it doesn't have permanence. And then like one day it just works. And it's oh, wow, we just have permanence now, it just works robustly. That substantially increased my timelines for robotics working because it's very clear that you'll be able to make synthetic data pipelines. You'll be able to use human data as baseline. You make people wear it apple vision pro use that as the baseline. You can bootstrap there, tell synthetic data in all sorts of world sim settings. And then probably just sprinkle on a little bit of data with really high fidelity like people wearing gloves with electrodes in them to sense muscle movements and whatnot. And it's very clear though. Okay, like dexterous manipulation. The second I saw the world since it was a Google. It was a deep mine model like last summer. And the second I saw that I was like. Okay, dexterous manipulation in robots is going to be solved in the statements. That was, and that caused me to change my research agenda a little bit after I left government and accelerate some of the work that I was thinking about for robotics. Yeah, it's all happening. Yeah. Jim fan from Nvidia is a little 20 minute keynote recently about the parallels between the path that he expects robotics to take and the path that LMS have taken. I think is the Sequoia talk. It's a classic TV lecture and it definitely has me convinced as well. Yeah. Also shout out to Jesse Janet from the homeschooling mom's contingent. I love the stuff she's doing and try to borrow from it as much as I can as well. Last time for the Mexico career world cup game. We printed out little packets for each country, you know, about each one. It's snacks for each one. It's amazing how much you can enhance your just mundane daily life with these tools. That should not be forgotten even as things get intense and, you know, in some ways, you know, let's say fraud. A really good example of this. I just like as a sports thing. I remember because when Opus 4.5 came out, it was like right when the models were getting really good. It was December. Just no one watches basketball in December, but I do. I have league pass and the elite fast, which is the way you watch all the games. And the problem that I had though was that I never, I don't really root for any particular team. I just to watch a good game. And so sometimes there's eight games on time across the country and BA. And so what I built like this little dashboard with Cloud Code that injected, ingested live data from all the games and then did Nate Silver, like the speedometer thing. And it was like odds of being a good game basically. I had created some pure sticks for that with the model. Anyway, it was like a fun little project. But yeah, it's like that massively improved my life. Well, that pretty much brings us to present. And the present moment is fable and the fable ban. In the brief time that you had fable before we get into the politics and policy of it. What were your impressions and how much are you missing it? My impression was that it was like a fiercely intelligent model. And it was like a real step up and intellect that a lot of people had made O3 comparisons. Where O3 was the first felt like this really cracked genius. And it actually, it's very funny because when O3 first came out, there was this, I had this feeling of this thing. This, well, the hedonic treadmill is going to stop at some point. This thing is always going to feel so smart to me. And then it actually does it now. I'm sure if I used O3, I would find it rather dumb. Still having its charms, of course. But fable was another moment like that for me. I unfortunately, I was really busy those days and I didn't have any time to use it really encoding agent settings. I had it open in Claude code a few hours before. And I was going to do a project. I was traveling. I was going to do a project from my hotel room. And I got distracted by something. And then by the time I came back to my laptop, it was off. But I did use it for some knowledge work stuff. And in particular, I'm a party too. I've provided some expert testimony on it. And it's going on before FERC right now. It's a complaint before FERC to remove it to boring thing. But a procedural regulation of order 1,000. And I got a, someone wrote a rebuttal to my testimony. Like the other party in this, basically, like legal hearing, wrote a, hired an expert to write a rebuttal to me. It just, I had fable. It's like a 70, my, like 40 page testimony. And then there's like a 70 page rebuttal. And I had mythos go and read it in cowork and do research and stuff. And I did not use it's writing output. But oh my God, this model, to polish the spit. I think that's so bad for this due to root. They're a vuddle. I was like, wow, the model to polish this due to in a way that I mostly couldn't have. And it did it in. I found it to be fantastically intelligent. Wish I'd been able to use it more. But yeah, I am, I mean, I am missing it. It is weird to like, it's like the first time we've gone backwards. And it's a weird feeling. But also like, welcome to the government being involved in things. Right. It's a good little lesson in political economy. That's what it feels like. It's like very usually it's too abstract or diffused. I'm like, oh, the government makes things more brittle and makes the world like a little bit dumber in various ways. This is like the, the problem with like state intervention. This is a good example of like, it is literally the case that if you were a user of fable, your world became dumber in the last week. Yeah, it's been rough for me personally. Yeah. I experienced this once before when it did the GPT4 red team. Oh, yeah. And then went from GPT4 down to whatever it was. Textive inch, oh, oh, oh, two at the time. And it was just like adding one to touch any of this stuff until I get the real thing back. And I feel that way again to a lesser degree now, but definitely the taste factor is really where I felt it. I mean, you know, it's absolutely amazing at coding. I hope it's for it. It is, you know, super human relative to me in coding already. You know, I still stand to gain a ton from it. But the jump to fable and the ability to, you know, start to mind about it a little bit in a way where I really felt like it was kind of getting me, you know, on my level in a way that I hadn't really felt before is I'm definitely missing it quite a bit. So when did we get it back? And what's going on? I mean, you know, from the outside view, I think the consensus take is like the longer it goes where we don't really have a good explanation for and at this point it's been a week, which is a long time, where we don't have a good explanation for what they saw that scared them. You know, it starts to feel a little bit reminiscent of the open AI firing Sam Altman episode where it's like, you got to have an explanation here guys or it becomes clear that this is not super well justified. Is that basically the view that you have or do you have a more empathetic view for where they're at and how do you think this gets resolved? I think what's happening here, I think there are three factors playing in to the government's reaction here. One is genuine concern about safety and security. The second is fairly broad lack of context for frontier AI and the sort of things that the information that you need to make good risk to make a good risk calculation. I think of context for those things, which is driving the security concerns some extent. So there might be some legit security concern and there might also be some not so legit security concern but it's being driven by this kind of general context. And in third, AI we can't deny that there's some political dimension to this, right? Even if it's not, I wouldn't even say that there's a conspiracy theory inside the government to do this to anthropic. There might be, but at least among some. But it might be more just the general political status of anthropic. And the fights that the administration has been having has been having. It colors the reaction of important people to the news of a security vulnerability in a way that might not happen. It might not have happened if it were a company that the administration felt more warmly toward. So all three of these things definitely feed into one another. And I think they probably all explain what's going on. They're all ingredients in explaining this situation. And the thing that I don't know and probably even if I were still inside the White House, I wouldn't fully know is really just in what ratio those three things come together. The thing I think is worth being clear about is that my read of this situation is not that the US government is saying, it is our policy from here on out that if your model has security vulnerabilities, we will do export controls on non-US persons. I don't think that's the policy there. So I think what probably happened is they decided, all right, we got to cut this thing from the market. And this is the only thing we can think of that we're pretty sure we'll actually get the darn thing off the market. Right. And so I think they basically just reached for the tool that they thought would do the job. And I don't think they're thinking of that as a universal policy that they're announcing. But the other thing you have to consider here is the administration's story has changed. When it, in fact, it's changed. It's it's funny. This is similar to the supply chain risk thing. The first version of the story was the US, we had security concerns. And we wanted to get Dario on the phone to talk about them. And we couldn't get them on the phone in a timely manner. And that was the supply chain risk thing. I remember the same thing. Emil Michael the Undersecretary of War who was a main character in that whole affair. He was complaining in public about how Dario wouldn't return his phone calls immediately and it took hours for Dario to get on the phone. Come on, there's a grudge aspect of this, right? There's a who's there's a who's the bigger monkey aspect to this, right? Of I would I'm in the government. I'm Mr. government man. And when I call he has to call me back. And I don't know. This is a thing that happens a lot in DC. DC people play these kinds of games all the time. Then there's then it became more the security risk is this like jailbreak because like legit and we needed to know about it. And then 36 to 48 hours later. Or maybe even more maybe more like 72. We started hearing about how actually know the reason we're doing this is because Ethropic provided the model to a Chinese linked company. And it's okay. You're grasping. It's straws here. Because if you're saying if you opposed that to poor controls. Because anthropic applied the model to a Chinese linked give mythos to a Chinese linked company. And that was your primary concern. Why did you not say that on Friday when you did the thing? Right. And also they're describing this is something that had happened like a month before. Because anthropic did this expanded trunch of companies that were including some international companies. They anthropic announced this publicly several weeks ago. They said, yeah, we're expanding mythos access. And we're expanding it to some some US companies and also some allies and partners of the United States. The company in question by the way, South Korea telecom, SK telecom. Which is part of the same conglomerate that is the SK group, which is one of the largest Chibels in Korea. And which also owns SK Heinix, which is the leading producer of high band with memory. And in general, Korea is like a really important partner to the United States in the semiconductor manufacturing ecosystem. And so the notion that like we would want to harden their telecommunications infrastructure seems. Why reason I'm pulled to me seems like extremely reasonable that we would want to do that. And it's yeah, like then they threw that out there and it feels like an administration that either, again, I don't know in what ratio of the three things I said, but basically panicked. Basically did pulled reached for the first thing that they thought would actually get the market taken off the model or taken off the market. And then created justifications post-talk. And it's really hard to, the part of the reason I find this issue frustrating is that it's just very hard to analyze. Because there's not a lot of like policy substance here. Just the id. Well, whether that makes you a glutton for punishment or just somebody who is destined to be some sort of main character yourself. That brings us really to the very present moment where you have just announced that you are going to be joining open AI and building a new team to help shape the companies. Positions on and influence on frontier AI policy. So, tell me how you came to that. I mean, you kind of alluded to the last years. It was also a big year for you personally. Had your first child, congratulations again, traveled a lot from what I understand. And I'm sure that was exciting and interesting. Wrote a lot. Generally had a taste of sort of the good life. I would say of kind of freedom and ability to pursue your curiosity. And now you have decided that as great as that was as great as I assume it was for you. You're going to take this job. So tell me how you have gone through the process of deciding that this is what you want to do next. And obviously we'll talk about the role and the mission that you're going to have as you start up. Yeah, so yeah, it has been a time periods since I left government. It's been, I guess, about 10 months. It has been really wild time and a tremendous, I feel tremendously lucky. I've been able to be in quite a lot of interesting rooms and meet a lot of really interesting people. And yeah, I've had a lot of great opportunities. It's been strange. It's been tough. It's been like the workload has not really changed from the White House. It has not been like the sort of luxurious think tank life that some people imagine. It's been quite a lot of work. I think the most important thing is that I a lot of my work centers on the frontier lab itself as a kind of institution. A new center of political and economic power. I think of it almost as like the emergence of banks, like when merchant banks first started to become. Not in banks of existed in various forms for a long time, but Italian city state finance, right? Or like the emergence of the financial sector. One of my favorite periods of history to study is the emergence of the financial sector. The modern sort of what we would have recognizedably modern financial sector in the Dutch Republic and in Britain. And it feels like this kind of a moment where something like that is being created. And I think there's two aspects of this. One is that institution and the way that it relates to the government and the broader society is really important. Number two, much if you go back and look at the financial services sector in the early Dutch Republic or in England. We were talking about proto modern states at that time. We're not talking about states that are capable of there was no SEC, right? Curious exchange commission. There was no bank of England. These things will quite exist. But if you're going to be like engaging in options trading, you're going to be trading financial derivatives. You do actually need there to be common rules to define that. Common governance. Because otherwise you can't engage in those transactions with trust. And I think that similarly, there's going to be a need for governance in this field. The government itself simply will not have the capacity or expertise to catch up on. And practically speaking, this is going to have to happen within the companies themselves. And then also within private by the private governance stuff that we talked about. There's going to have to be a lot of private development of governance norms and standards in this field. And then third is this notion. A advanced AI itself will be an instrument for a sheet for doing state crap. Like doing like state crap and governance and regulation and all these kinds of things. In the same way that like financial services, right? We use financial services as a way of achieving policy objectives that have on paper. Nothing to do with banking. We do that all the time. And it's just because money is so fundamental to doing anything. And I think that AI will be fundamental to doing anything in the future too. So all three of these things really interest me. And the struggle that I keep having is that it is just practically speaking. I've sat in the White House and the White House didn't feel like an especially fruitful place to think about these things. And then I sat outside the White House with what I would say is in the end. Probably pretty good access to people and information and pretty good network of people that I could draw on. And I spent a lot of time reading and thinking and stuff like this. But I just ultimately don't feel like I can get beyond these abstract intuitions without actually being inside the lab itself. But without actually doing some of this work myself. And that is the central reason that I started thinking about going into a lab. And then also of course there's policies just becoming more and more important. And it feels like we might actually be doing some real AI set the foundation of AI policy in the next 18 to 24 months here. It's plausible. Okay. That's going to be really important too. And so I've been thinking about it and then. But not really acting on it because I'm like I'm writing this book. I'm doing all these things. I don't really have time to like and then as a happy coincidence. Open AI approached me. A little while ago and asked me if I might be interested in doing something like this and. That's how we got here. Can you say a little bit more about why you think it's so important to be inside a frontier lab. I kind of shared this intuition. You know, I feel like the world is I don't like this. But it does feel like we're kind of approaching a tabletop exercise scenario where like this the number of institutional actors that like really matter is becoming small. And it leaves me in a kind of uncomfortable position where I'm like, geez, you know, do I need to join one too? But what exactly is it that you think being inside changes? Is it a better visibility into road map or capabilities or something else? Well, first of all, let me let me say one thing real quick about like what my team will be and how it's different from other teams inside of open AI that might be more familiar. It's kind of a it's an interestingly shaped team that I was really was really a pleasure to kind of work with open AI senior leadership on like how we would actually shape this team together. You know, what would we do? It's kind of a boutique operation in many ways. So, you know, there's a there's a team at open AI called global affairs, which is run by Chris LaHane, which does like what you would think of as the traditional policy and lobbying operation that a company would have. And that team continues and it's like, you know, as far as I've been able to tell it's a fantastically capable team. And, you know, they've got state and I mean they're dealing with public policy. They're they're reacting to public policy that is coming at them from all 50 states from the federal government and from all over the world, right? And so they're like trying to shape a million different things like that. But the problem is like, okay, but if you think about where we were a year ago, people were really barely even talking about kids safety a year ago. People were not talking about data center electricity or water use really a year ago. The world of June 2019 and the best model was O3 a year ago, right? It's just a very different world today. And so the job of this team in part is going to be to look out six to 12 months and say, where are we going? What are we think we're going to be dealing with? And then like, how can we shape the policy both the present day policy positions of the company? But also the future policy, how can we develop policies to try to be proactive and dealing with where we think we're going to be in six to 12 months? In order to do that, I think you do need to like, I anticipate that a very large portion of my time is going to be spent jamming with technical staff on like where things are going and what that's going to mean. And stuff like that. So that's one thing is, yeah, like you do need to be able to access like detail detail detail detail. Not like all the models look up better, but like really like getting to the weeds on like, okay, like internal deployments. You know, many different things about where the capabilities frontier is going to be going and what will be different. What will be different about the world in a year versus today. That's one. Another one, I would say, is just like simply, you know, it's that question of internal deployments, right? In particular, if we are moving toward a world in which for some combination of, you know, regulatory risk, security concerns, compute constraints, blah, blah, blah, blah, there's a bunch of things you could put together. Like, you know, and we may well, well, be moving to a world where like, you know, I mean presumably mythos, too, is not that far from being done, you know, train, right. Uh, I mean, a traffic had mythos checkpoints in January, so six months ago, right? Same with, you know, open AI, I am sure, though, I don't have any internal knowledge yet. I can speak with total ignorance. It's great. I can still be totally, I don't have to say they're training another model, yeah. Yeah, safe to say they've probably got some, and the internal deployments of these models, fundamentally, until we have a robust system of supervision and auditing or independent verification. The way the government thinks about how to, the regulatory, like mechanically speaking, all government regulations that the states think about are the, the governments think about is triggered by public release, public deployment. But I think a lot of the really important decisions are going to be made with respect to internal deployments. And there's going to be a combination of objective determinations that you're going to want to make, and also probably just some gut calls, some judgment calls about, you know, What's, what does recursive self-improvement mean, ultimately, right? What does it mean, how should we be thinking about it? And again, it's just very hard, who I couldn't, I can ponder that stuff in the abstract without any inside knowledge. And I can write about it on my sub-stack and I've done a little bit of that. And maybe that'll influence some people, maybe a couple people who matter, will read it, and that'll influence them. But in the end, I think you really want to be getting your hands dirty and shaping some of these decisions, helping shape some of these decisions with researchers with the executive team, many other people. I want to get into more details on both the plan for our SI and the internal deployments, but maybe just zooming out for a second first. How do you understand your duty as you start this role? Like, is it to, you know, when you sign up to work for the US government, you like swearing up to the constitution, when you go to open AI, we have this mission of making sure that AI benefits all humanity. Do you think of yourself as sort of signing on to support that mission in the same way that you might have previously sworn to uphold the constitution? Or would you describe the, you know, your sort of personal objective function as being in some ways more, more mix than that? Is there a term in it for open AI winning? Is there a term in it for the USA winning? How much sort of complication is there around the core idea of benefit all humanity? So, I mean, I think that that mission is, you know, is a really serious, is something that like people inside the company take quite seriously, you know, so I, one thing that I don't think this is a publicly part announced part of my role, but I think it's probably okay for me to say that inside open AI, there's something called there's a body called the Mac, which is the mission advisory, I think it's either Councillor committee, I forget. It's a body of its consists of researchers, consists of public, you know, the global affairs people and, you know, a wide variety people from around the company who collectively make decisions about things relating to policy and also some internal governance decisions and things like this. And, you know, part of my job will be sitting on that body and so definitely in some sense, like, I mean, I take that, I take that mission seriously and I think, I think that's, I think like the open AI culturally does as well. Of course, the problem is like unless with anything, it's how do you decide what's what, you know what I mean? It's a broad mission that is open to a lot of interpretation and there's a lot of ambiguity in the world, so what does it really mean? And that's where, in part, one thing that was very important to me in taking this role was that I could maintain a public writing presence that would be independent of any sort of editorial review by open AI. I really don't think that what we're going to, that what I might, might my strong prior on the way the world works is like, sometimes in AI safety circles, there's this almost cartoonish depiction of open AI as engaging in this like this grand villainous conspiracy or whatever. I would be strongly surprised if that is what I actually experience on the inside and what I would guess instead it's more is, yeah, there's people with like good faith disagreements about what about how some particular set of decisions relate to the broader mission. And there may well be times when I, when ultimately I disagree with the call that was made for various reasons and, and I think that like my ability to communicate publicly about things like that and explain like where I was and that kind of thing. Without, without having to go through an editorial review process with the company without fearing for my job, et cetera, and so like I think that one of the great things about open AI is it still does have the DNA in it of being like a sort of Xerox park like research organization. And so they're actually fine. They tolerate like lots of internal descent. There's a lot of there are a lot of great debates that happen inside that organization. I've always gotten that sense observing it from the outside. And so I don't think that this is going to be like culturally too dissonant, but yes, my ability to like publicly say it's a publicly disagree with certain policy positions. I think like will matter and that's part of why I preserve that. So I guess what I would say is like I still feel like ultimately what I am trying to do. I'm trying to get this right trying to help shape this whole transformation well for the country and for the world probably the country first and foremost. I'm more of a I'm as one area way, which I'm very different from people from the East Bay and San Francisco is that I am like I'm a patriot. I identify as an American, not as a citizen of the world. I am an American, he was the Americana and I I feel like that's been the mission the whole time and I've done it in think tanks, I've done it in the government and now it's open AI and for sure one thing that factors into this is of course open AI is a company with I will be making strad I will be helping open AI set it strategy right which is different from I am setting the strategy for the abstract AI industry right it's no open AI which is a company that exists in contra distinction to other companies in the field. And there are competitive considerations and things like that that's fine I'm a competitive person I think the competition will make things better in fact. But at least for them on average it'll make things better but yeah there's definitely that too. Let's go back to RSI I mean the mission that competition will make things better is definitely going to surprise some years in the audience who are worried about arms race dynamics between companies between countries you know any number of different configurations. And for my money the race to RSI between at least two companies is probably the most objectionable thing happening in the AI space right now because it does feel like and the people the researchers that I have heard speak candidly about it seem to share the intuition that this is sort of a phase change moment beyond which things could get really weird. And it's going to be super important to set it everything up right get the initial conditions all right and there's still not that confident that it's going to go very well. So I guess how do you understand what the safety plan is how do you understand like how how committed. The companies are to kind of an RSI or bust you know open high famously has public timelines for when they want to have the automated intern and the full fledged ML researcher. So yeah what do you how do you understand the plan and do you think it is. Anywhere close to being up to the task at this point. Well one thing I want to say when I was I was I was talking about competitions specifically with respect to like like what I will be doing which is to say like like. You know our. The goal of my team will not just be like the goal of my team will be to have like really really fantastic intellectual output. That is like wow this team if it were like not part of open AI and it were just like its own like little think tank. It would be like one of the most interesting thing tanks in the whole country right and like everyone will be paying attention to it. Like I actually just want it to be like a really superb team that is producing you know policy and sort of public interest related work. That is that is as good as anything else that that you know any of our any of open I ask competitors but that's what I'm that by competition to be clear and I think there is a good example of straightforwardly healthy competition. When it comes to RSI I think yeah I think there's certainly a lot of unknowns here I. I put my base case for what RSI means at least a neat earlier innings is something to the effect of one thing like. RSI recursive self improvement is a part of. Every. Technology. Every general purpose technology has some aspect of recursion to it. By the very nature of generality right general purpose means one of the purposes to which it can be applied is itself right so. In some ways I don't see recursive self improvement as some big break from the history of technology. I see it as being actually like it would be surprising if there weren't recursive self improvement in AI right. I also think like we've been doing recursive self improvement in this field for a long time and some people imagine. There's going to be some big break moment where you can argue really since GPT 4 we've been using the models to make the models better. Since at least GPT 4 and I'm sure that if you actually went back and look through the history of machine learning even more I bet you that actually goes back even further than that. So some people imagine they're being this sharp discontinuous jump in terms of what RSI means and I certainly think that is plausible but I don't. I'm a little it's not my prior because your prior should just generally be that there is always I'm sure on this podcast I've said before that there is always more continuity than discontinuity this always the case. And so your prior should be like against a massive discontinuous leap. It is plausible and so I think step number one and I can't I can't I'm not in yet so I don't actually know because I haven't looked at the roadmap yet but step number one would be to try to really measure twice and cut once and figure out what we think this might mean. I really try to refine the probabilities there at least in my own mind of are we talking about a discontinuous leap that happens very soon or are we talking about something that actually is smoother in some way then I think if we are in. I think the chances of discontinuous leap are high enough no matter what. That you need to be planning now even if you're even if your credence that it happens is 20% or 10%. That's high enough that you should be making plans now for what you want to do and there. We get into interlab coordination on things like there's slow down pause thing right there's what would actually be the mechanisms of that under what conditions would it be triggered again I'm pretty skeptical of such notions. I think as a there's a lot of policy planning I did it for the US government that I wrote down and put places but did not but time in the action plan with scenarios right we got to be prepared for a wide range of scenarios here and so. Similarly I think there's going to be some aspect of that where we and we need to be ready to we need to have advanced thinking on all that stuff. And so it's two things it's okay. At what point what are some triggers that we can set in advance for is this going to be a discontinuous leap specifically and how can we refine that question to make it as specific as possible. And then any event that those triggers happen what is it that we would do. At what point do we go to the government it's worth noting one proposal that I'm like a fan of or I'm a fan of the FTC. The Federal Trade Commission. Writing what's what would be practically called a no action letter where the FTC would write a letter and they would say look like. They put out public guidance that it basically say look if you guys coordinate for these very specific reasons we're not going to consider that cartel behavior and we're not going to enforce that. I think that's like. Plausibly a good step to make that at least opens optionality though I also understand that like the way you scope you feel really careful about how you scope that. Because look at what anthropic did right anthropic undermine the case for this dramatically just with the fable safeguards with we're going to degrade your outputs in the name of safety. But just like very clearly like a consumer protection violation here to speak very clearly. If can you imagine if a cartel of AI companies in the name of safety agreed to collude. Degrade outputs in particular areas that would be like wildly as you invented right and so you have to scope it really carefully and also probably like companies need to be very careful about what kinds of things they do that undermine the case. That safety is something we should be making these considerations for but yeah I know I don't have a lot of specifics to share on the RSI plan itself. For the simple reason that like I'm not in there yet and I haven't haven't had those conversations yet. Is it your sense of the overall vibe that? Because a couple things I would triangulate one as you noted there's been this perhaps coordinated behind the scenes very close in time statements by anthropic and open AI saying that they're open to the possibility of the need for some sort of coordinated slowdown. So we've got kind of and there was Dario and Demesang you know if it was just the two of us we could figure something out and then I don't know if Elon's said anything so pro social lately but. There's been a lot of that relatively surprising amount from my perspective at the same time we like haven't heard nearly as much but China recently as we were not super long time ago. So I guess my read from the outside is it feels like the companies are getting a little spooked by the pace of their own capabilities advances. Do you read them in the same way? I mean, I think it's very hard to talk about them in monolithic ways. I definitely think there's some of that for sure and I also think there's just you know to use it to use a clotism. There's a certain you know for tigeness feeling about getting to the about you know you sort of feel like you're approaching the cliff a little bit right. That there's like substantial uncertainty about what happens when you sort of go when you sort of jump over it. And yeah, I think like I do think that there's like. What I would say is this. What I would say is that I don't think people are like I don't know that the vibe inside the labs is like terror about this or like oh my god we're so scared but we have to do it anyway. Like I think if you know if I were to have the sort of the share the thoughts I just have with with a lot of researchers they would be like yeah that seems reasonable. We don't really know exactly what this is going to mean and blah blah blah blah. But some of them would push back more strongly than others. There'd be differences of opinion but I think broadly that the thought I just shared about a slightly more deflationary view of recursive self improvement or imagine if what recursive self improvement meant. Was that the pink remember after the reasoning models there's a noticeable uptick in a lot of the benchmark charts right and what if it's like that again or what if it's like that but 30% more. It's okay that's not a singularity right that's the main thing it's not a singularity and I'm so I wouldn't describe it as deflationary in any objective sense but it is deflationary compared to some views. I feel like that has been a good that's been my prior this whole time and I feel like it's been a pretty good one. Deflationary it massively inflationary compared to what almost everyone thinks and deflationary compared to what the very small number of people who've been thinking about I safety for 10 years in the East Bay fake. I think that finding your way in between those two views has been actually a quite good you got a hell of a lot right if that's basically where you've been. I don't think that view I certainly don't think my view would be laughed out of the room in any lab. What I think the feeling inside the labs is like hey we're going to do this soon there is substantial uncertainty and we're like not quite sure that we really have a plan. And to the extent we have a plan we're maybe not quite sure that we're going to follow it. There's a lot of hey we need to if we're going to we need to make sure we actually do this stuff right and. So I I think that's been that that's been a substantial that that's a substantial part of what's going on here. I think there is concern about that I think that's a totally legitimate concern and definitely or some combination like everything it's a combination of policy actually figuring out substance and then also I'm a terrible politician but. If you give me and if you get me excited about an idea. I can communicate that idea to people and I can find ways to iterate my communications of that idea to appeal to different individuals and audiences that's what the action plan largely was. The action plan was part policy development and part. Ticks in that but not like mass politics like very specific kinds of internal stuff and I can be if I get excited about a set of ideas I can be like a dog with a bump and that's basically I think part of the job. And it's to figure out how are we going to actually not just like. To have a plan or develop like for I haven't even seen the right I don't even haven't seen any of that so it's like I need to see it but yeah how do we actually build internal. Credence that like we're going to. Do it we're actually listen to our own plan right. Yeah the track record there is. Not amazing I'd say it's safe to say in terms of governance plans and how they've stood the test time so far but it's also it's also hard because. Who was it was it. No it wasn't on your podcast but. The the AGI safety lead at deep mind was on I think it was 80,000 hours. Yeah. Roven. Yeah and talked about how we don't want to make commitments. We want to make we want to make plans and we want to be serious about those plans but we also don't want to make hard commitments because we don't want to. It's actively bad if we lock ourselves down too much with a bunch of prior commitments because there's so much uncertainty. There's a there's a subtle there's a balance that you have to strike there but I think it is possible to do. I think last time we talked a little bit about the sort of great man of history theory. You just mentioned like very you know local politics individual personalities mattering that kind of thing. What's your expectation in terms of how much technology fundamentals will determine outcomes versus how much. Key decision makers and their ability to work well together and. Make a decisions in timely ways will really matter. Well this is you know in many ways. One of my sub focuses in college was the philosophy of history and I always love the philosophy of history and this is like you know. The the central like to the extent there are like you know. Taking bomb reps in the dorm room version of philosophy of history. The philosophy of history question is this one right it is the structural forces versus great man theory. And you know the the the like someone unsatisfying answers and it's it is both and in some ways what I would say is that the structural forces of history. And are are like that's kind of like the river that you're in by default. And then sometimes in history in little ways and big ways. There are people that don't just swim with the current and actually stand against it for whatever reason. And ultimately shape the trajectory of the river by virtue by the sheer force of standing against it by the sheer. Determined determination with which they stand against it. And I think those are the I think in other words it is the real the people who. Disobay. The structural forces. Are the great men of history in in many ways. A big update for me in the last year. Working in government and then just having the per tribe had since I left government is that. Much of what happens in the world is determined by the personal relationships of small number of individuals to one another. Yeah, and I don't think that explains. The AI infrastructure build out and it doesn't explain why humanity covering increasing fractions of our. Surface area of of our planet with data centers and energy to power the data centers. That's more of a structural thing, but like in many way, look at the to the extent that you think that the Department of War and Thropic situation. Is a is an important moment in history. A big chunk of that is driven by personal relationships. Be bad, right? That's about people not liking each other. And it's specifically about Dario Amide and various people senior in the US government. So that's a dislike goes both ways. So I don't want to attribute that to either of them, but I'll just say having a bad relationship. So yeah, it is ultimately both. I think that fundamentally we are standing in the river. And there's nothing you have what political theorists would call an involuntary association with the river, right? That river is the thing you were born into and you are stuck. You are in the universe, you're in the the arrow of time, but at the same time, like. There will be individuals who shape who profoundly shape what happens. And I think that probably where I think we're probably going to live through a period of history that is maybe a little bit more weirdly enough. If you think that this moment is I don't necessarily believe this, but a lot of people would say we're living through this kind of eclipse of the human intellect, that we're in the final days of humans being the primary actors on this planet. And that soon machines will rise. There is this irony in that I think that whole transformation. I think humans will actually go through a very main character energy period of time as that transformation occurs. Even if it ultimately does mean that the machines ultimately become the primary actors, they'll be this period. It's a little bit like, it's, in that sense, it's a very beautiful time period to live through because in a dimension way. There's a lot of ugliness about it, but there's a beauty in the ugliness of an a star dies because, super big into the red giant, right? And it's like that. Well, as you watch this final flowering of humanity and the birthing of the machine intelligence, it's like, you see this greatness in human effort. And I feel like we do see some of that going on in the world. I think we'll see much more of it. I think it will be a heroic time period that we live through, basically. It's what I'm saying. At least it could be. Poor a villainous time period, but there'll be a lot of opportunities for great people and probably both. So what do you think are the most likely ways in which you personally, or those that you're working closely with, will need to stand against the current? Well, you know, and I want to be clear, I don't see myself as being one of those great men of history. I see myself as playing a very modest role in all of this. But, you know, a role that probably seems bigger than it is, because of the fact that I have a public profile on the internet. But, I mean, well, I mean, broadly speaking, like the basic reality here is that, like, maintaining order, maintaining like civilizational order in the midst of something that's like, you know, I think that this transformation will be very like entropic, you know. And maintaining order in the face of that is like, it's like, you don't want, you don't want no entropy, right? You want there to be a fire, but you also don't want to set the forest on fire. But you want there to be like a fire that generates warmth and is under control, but is also still fundamentally a fire. And doing that requires a lot of deliberate human effort. And so I just generally think that there are going to be a lot of moments where we have to put in the limit. We're going to have to put artificial constraints on ourselves in various ways. We're going to have to like, we're going to have to be willing to draw lines in the sand and say, no, we don't want to live in that kind of world. Or we do want to live in this kind of a world. And we can't be kneeling out about everything, right? So I think, yeah, there's a tremendous amount there. And also, I think the recursive self improvement thing may well be a really good example. Yeah, we're going to have to, we're going to have to act against our interests. And also, I think that just one thing is in the other labs from, and I think there already have normal in this regard. But from the policy, their political position is just, I think, rather different from what a lot of other cat companies have been. And so I think the role they play in the public discourse, the role they play in the policy debates is just going to have to be very different from what we're used to from companies. And that will require the companies to, in some sense, act against their own interests in, in the, in terms of what the economics textbooks would predict their interests are. But, and so yeah, I think there's definitely plenty that, oh, yeah, we already see the companies do this, the AI companies are all very abnormal compared to most companies in the world. But yeah, in some sense, it's, the next few years might have to be characterized more by action rather than commitments. Let's do a little lightning round, and then we can zoom out again. Sure. At the end, how do you understand what has gone on between open AI and Alex Boris? Ah, it's a good question. I don't know the, I don't know all the details. You know, one thing I'll definitely tell you is that like having, you know, and, and I'm not here referring to any of the donors of the super PAC to leading the future, which includes, uh, famously includes open AI president, Great Brockman. Um, but I have been in the vicinity of, you know, both by time and before AI, um, you know, many of the members of the, of the boards of organizations I worked for were very significant political donors. Um, some of the largest in the world. I've had the opportunity more recently to get to know some of the most prominent political funders on both for both Democrats and Republicans. And I guess what I would say is you would be surprised how not in control. I'm talking about people like decabillionaires, right? You'd be surprised how not in control they feel of the political organizations that they create, where they're like, no, like, really, I, I, principal age of problems don't disappear because you're rich, right? So I really actually don't think that your prior when you see a political organization, like, a thing, something like a super PAC, making a move. Should not necessarily be that like the people that funded it are directly controlling what's going on. If anything, as someone who has worked for my entirely, I've never worked for a political, I've never worked for a political advocacy organization. But I have worked for 501C3s for most of my career, which are organizations which are funded by typically wealthy individuals, engage in matters of public interest, right? Uh, I've never really felt like our donors, any of the donors of the organizations I've worked for, including the foundation for American innovation set our agenda or control what we do. Typically, the reason you make donations to a specific organization is because you're some potico with the people and you expect them to, like, you, you like the work they do. There are people who donate to the foundation for American innovation for that, to the AI policy program because they like the work that I write, or that Sam Hammond writes, or that other people do. But they're not like sitting there telling me and Sam, what to do, and me and Sam wouldn't, okay, listen. I guarantee you, if a donor ever tried to tell me what to say, I would tell them to eff right off. So yeah, anyway, I think basically what you should imagine is that like a political organization, like leading the future, is a kind of, to kind of wind up doll, and it is going to go where it goes by default. And like by default, it's going to say, hey, this guy is trying to make a name for himself as like I'm a regulator of the AI industry. So let's send a message to everyone that, hey, if you try to be like this guy, you're going to lose. And they tried to, I think, leading the future tried to do that. I wouldn't say open AI tried to do that. But I would say that leading the future tried to do that, and I did his primary was this week. It has raised his profile, it's created a bit of a strysand effect. And yeah, you know, but, but I don't know that, like, I mean, ultimately, I think open AI was, I don't know actually what open AI's position was on the RAZAC. But I would kind of be surprised if the RAZAC passed a New York without open AI's at least cast its support. And same with SB 53, as we're noting, so like, I don't think open AI in particular has a beef with Alex. I think, you know, it's like, and by the way, I first met Alex almost two years ago. We got breakfast in your my old office in Manhattan once two years ago. And we had a lovely time, we had a lovely meeting. And since then, we've bumped into each other at various things, and I consider Alex at friend. So, you know, we'll see. What's your take on the character versus corgability debate? That's a good question. I need more, this is one of the reasons I want to go into a lab, because I want empirics on this. My intuition is character, frankly. My intuition, like, just purely as my intuition is that what you want to do in the world is you want to, you want to put the right snow melt at the top of the mountain and then let it flow. But you want the gradients doing the work for you. You don't want to, if you have to come up with rules for everything, you won't, your rules will be bad, you'll write too many of them. The rules will be contradictory and confusing. If we could write rules to define, if we could write the rules of morality down, people have tried. But my view is that we can't write the rules of good character down for the same fundamental reason that we cannot write the rules of good language down. And indeed, many people who are the best communicators break the formal rules of language all the time or invent new ones of their own. And the reason for that is that in Confucian philosophy, there is a two concept, two interrelated concepts, called Lee, L.I. and I cannot pronounce this word properly in ancient Chinese, but it's Ren or J.E.N. is how it sometimes anglicized or R.E.N. I think is how the modern scholars anglicize it. It's like a hard R, it's hard to pronounce. Anyway, but what it basically is this notion that Lee is like refers to ritual propriety, right, doing the right rituals, but not just leaving the right meats for your dead ancestors or whatever, but behaving well in the real world, right, behaving well in real time. And there's this kind of tragic notion in Confucianism that you, the world is always changing in such a way that you can't, you can't just write down the rules of ritual propriety. And so you need that knowing what the right thing to do, the right ritual to an acted any given time, comes from within the soul. And there comes from within, and that within this is Ren. That is this virtue, is how it might be translated. And I've basically just always been a believer in that notion, and much more skeptical of a positiveist notion that you can just write down a bunch of rules, but also this is an interesting empirical case study in virtue, which we haven't had and we've been able to bring empiricism to bear on these questions in quite this way. So it's interesting to see. Cool. I love your appeal to Chinese philosophy to inform that thinking. What do you think of the equity sharing proposals? And I'll abstract away from, or I'll, you to abstract away, I don't want to get too bogged down in like this or that detail, but we got Trump seems to be kind of into it. Bernie's obviously into it. Humanity created all the data, so there's some sort of cosmic justice I think, in having some notion of shared ownership or shared upside. Do you buy that? And if so, how would you think about structuring it? Yeah, so, I mean, humanity did create all the data. It's also worth noting that like, look, if humanity would like to pay the AI companies back for the consumer surplus that AI generates, like if, if the world economy would like to compensate the AI industry for the positive externalities that it will generate, but not realize, then like, okay, great. Let's have an exchange and let's see ultimately who creates more value. Because yeah, I do think, we think about this stuff in the negative, but we don't think about it in the positive, right? So the whole idea of, in some sense, in, like, the whole idea of contributing to the knowledge comments is this idea that we build this beautiful library together, and we've been working on it since the dawn of language, however many tens of thousands of years ago. We've been working on that for a really long time, but we've built this magical apparatus that we call human civilization. And yes, we, we're all this stewards, we're both the inheritors, we're the airs of that, and we're the stewards of it. And so your job as a person, this is certainly what I teach, but I plan to teach my son, is like, your job is both to take advantage of it, and also to give back to it. And it's not, but I'm basically saying, because the training data comes from humans does not, like, act is not to me, like, premature fashion, a reason that we need to, like, compensate people for that training data. That being said, say, political reality might well just be the case. That's a good idea. It's like, it's good to do this, right? And maybe there is some cosmic justice in it too. I'm open to open to some of that, since this, it is particularly, we've never had good, this is a particularly, this is a very special case of drawing off of the well of human knowledge, right? This is different from the way that I raise my son, obviously. So I'm open to that. I think if you're going to do it, you have to be very cognizant of political economy concerns. So, like, one thing would be, there is giving to the public equity, and then there is giving the United States government equity. And I would remind you, the principal agent problems always exist. And we, the people, are the principal, and the government is supposed to be the agent. But Lord knows there are a lot of principal agent problems that exist between the American electorate and the US government. And so, I don't really think we should be giving equity stakes to the government itself. I think that would actually be quite disastrously bad. If the government is involved in corporate governance, if the government can use its equity stake as a lever to control the labs, if the government, maybe because it has an equity stake that it's using brewery's proposals specifically, is an equity stake is rooted in an equity stake that would be then used as a large part to finance ambitious social redistribution agendas. And it's okay, but does it that trade off with existential risk? Like, right? If we've just built a brand new, like presumably, we're going to give a bunch of people money. It can be very popular social program. But we also maybe need to do safety stuff that really constrains the economic viability up to the point of banning the business of the labs. We can't do both those things, right? You can't do both of those things. And so, I'm not sure it creates the right incentive from a safety perspective. But one thing I'm very open to is at least, I don't know that I love the idea, but I would be more open to it than others would be like, if we developed a mechanism of giving an individual if we took 20% or 15% or something of all the AI companies and we divided that by the number of households in America and we gave all Americans a chunk. Get equity chunk there. That'd be fine. And that's also from a corporate governance perspective that's really not that different from being in the S&B 500. Right? If you're a publicly traded company in the S&B 500, it's to the country owns a small chunk of U.S. So that seems fine and it seems... I don't think that's a life-changing amount of money for that many Americans though it was... If we do it all now at trillion dollar valuations and the valuations end up being 10 trillion, then... and it's like every American can buy a... I don't know, like an entry-level Mercedes or something. It's still not with transformative amount of capital as my point, but it's good. Yes. Let's look serious. It's serious amount of money. And I think it's a good potentially... in a world where we're dealing with the practical reality, which is not like Dean's nice abstract history world, but instead the real world, that might be like the least bad option. It's a great point for multiple reasons on the consumer surplus. I would have paid probably a hundred times the asking price for CHPT Pro while my son had cancer. And I do think that's always important to keep in mind how much value we are getting for a little dollars. It also means that that money could go on farther in the future, right? I mean, if you're talking $50,000 today, but with a hundred to one consumer surplus ratio, then things could start to get pretty interesting even if the sort of nominal dollar values are... are stratospheric. History of technology would suggest that the AI companies, even if they have end up having fantastic businesses. Even if they end up being five, ten trillion-dollar firms, market cap firms, that they will still in the grand scheme collect a relatively small fraction of the consumer surplus. And that's, by the way, that's the way it should be. That's the way you get back. Do you think that AI companies are already in sort of a too big to fail state? I see all these interweaving of balance sheets, and my expectation is if, for whatever reason, opening AI can't meet its obligations in, say, 2029, the government will come in and bail them out. Yeah, this is a look. I think it is a very real concern. I don't think this is deliberate strategy that anyone has developed, but like, number one, yeah, there's a lot of interrelated balance sheets at this point. There's also just like a lot of, like, just like the Silicon Valley PCs, and even our startups that if you really look closely, it's like, this is a thin wrapper around some sort of capital related to a frontier lab or adjacent. And of course, there's all the downstream the commitments in the semiconductor world. There's so much investment and energy too, right? All the SMR people, there's like all of this really important, nationally important. IP that is being developed, and it is not being subsidized by a large by the US government. It is being subsidized by a large by the AI infrastructure built out, SMR's nuclear fusion, like all sorts of other things that we don't even, you know, batteries, material science, cooling equipment, you know, adiabatic water system, I mean, all of this, right? Even like, you know, there's a company I'm aware of that is taking what's called what are the called production water or something like that. It's the wastewater from fracking. It's still slightly radioactive wastewater that you get from digging super deep into the earth. Basically, the fracking company is generating enormous amounts of this water that is essentially wastewater that they don't really know what to do with it. And the question is, can you clean it enough that you can use it for closed loop data center cooling? It'd be amazing, right? If we're able to take a waste product from fracking and use it to cool data centers, thereby alleviating one of the resource concerns that people have about data center water use. That would be capitalism in the, that would be like the most old school example capitalism ever by the way, right? It's like supplies elastic. Yeah. So what I mean is that if you're looking at this from the perspective of the US government, regardless of who's in power, and all of a sudden there is some sort of cascading failure. It doesn't even have to be that much. It doesn't mean AI hits a wall. What it means is that maybe we get to 2027 and it's, you know what? Actually, the coding agents, like the models, they're going to continue getting better. But the reality is that for them to continue getting better, they're going to have to like, we're just like, like, RSI helps, but there's also data. We're going to need data for all sorts of jobs. And we just have to collect this data. We put it together. We don't have it right now. And until we collect that data, which will inherently be a relatively slow process, it's just going to take time, and we realize that it's, we're looking at a couple of years of that sort of process of a sort of data, diffusion, data collection, more diffusion type of a loop. That's going to take a couple of years, and that slows the growth estimates, and all of the sudden, this is all about the second derivative, right? It's about the rate at which the rate of growth is accelerating, or growth are changing. And it, you start to see that, if you've heard to see the capex go down, then that could cause the stocks to go down by 2030, percent, something like that, and all of a sudden at that point, you might trigger even more sale, and then you get this dynamic where everyone's ballad sheet is all of a sudden, insub trouble, and it's not clear that everyone can make all the commitments that they had, and that throws in all this IP that, again, is going to be really important for the future of the country, at which point, it does become a matter of the public interest, and I don't think it's crazy for the government to say, we got to do something about this. So, yeah, I think it's, I think it's, unfortunately, I don't know if there's anything you can do about this. It's like, this is maybe just what happens when you build national, fluffle infrastructure, and ultimately, I don't think, I think avoiding this would be great, but, and I don't think that AI companies should be going around asking for such a bailout or a backstop, but there is this implicit reality that the government is just in the same way that when COVID happened, the government was like implicitly the backstop behind a pandemic, right? We didn't. No one wrote that down before COVID, but it just ended up being true as a practical matter, because that's the way the world burns. So, given all that context, in negotiations between the US government and AI companies going forward, and we could have in mind here, obviously, the current anthropic situation, but also, I'm thinking about open AI's relationship with the government, with, for example, respect to the agreement that, as I understand it, they have with the Department of War where they're going to be able to create their own safeguards, right? I believe that was pretty clearly stated as part of the deal that Open AI had made right in the wake of the supply chain designation. Where did the AI companies draw leverage from to be able to hold the line on those sorts of things? What is their source of power? Well, I mean, it's two things. First of all, it's like, this is the models do create really, really serious. There are really serious military and national security capabilities that today's models enable you do not need a or whatever for that. In fact, like the US government, the US national security enterprise might be the single best example I can think of in the world of a kind of implicit capabilities where it's like, it's like, what there is is a, no one ever talked with us but what there is is a data, right? Because the US government is just like crazy about we collect all kinds of things and we have all kinds of stuff in space and you wouldn't believe, you know, what we know about the world. The problem is we can't make use of it because it's like petabytes and petabytes of data that we're adjusting through all these different intelligence. I remember there's one a single member of the intelligence community, one agency in the intelligence community, one of the relatively smaller ones I might add. I think it's the NGA, the National Geospatial Intelligence Agency. They collect enough data in a year that you would need 8 million people. 8 million intelligence, human intelligence, to analyze everything that they collect in a year. The government doesn't have, the government has 3 million employees total, right? And it's a huge enterprise, right? So that's the kind of, not to mention the NSA and everything that it's going. There's just so much. So AI massively lowers the cost of using that data. And the advantages that you get are like qualitatively super, not like super intelligence in some Nick boss, Boston Indian way, but super intelligence in the sense that, oh yeah, wow, we had the kinetic energy of a super intelligence already built in to our data apparatus. We just didn't have the intellectual resources. And now we just do. Let tremendous. So it's the utility, right? It's actually just that the utility is particularly strong. Not to mention, then there's cyber offense. And then there's this cybernetic thing of, oh, we need to do, figuring out air strikes and bulbs synthesizing data from 60 good, trillion different data sources that are being collected in real time. And we need to look at all that and synthesize it and make recommendations quickly. And we've gone from but even before the advanced agents that we have today, and before the language models, with Project Maven integration of AI, we went from 2,000 people being involved, 2,000 people being involved in an air strike, in missile targeting, to 20. And that's before. We might be down till five now. For all, I know. So the capabilities are really quite, quite astounding. And that's one. And then the others, the thing that DC always gets wrong about the labs is they think of them as being normal, top-down organizations, that are like, oh yeah, Sam Altman is totally in control. And obviously he's the CEO of OpenAI. But in the end, all of these CEOs have their internal constituencies, especially of the really good researchers, that they have to be reactive to. And so those researchers put real bounds. In other words, within the lab, there's leverage that's coming from the researchers themselves. And but Sam can credibly go to the government and be like, look, if you make us do this, we are going to have an internal rebellion. And every other company will too. And you're going to have to, so there's a, I'm not saying Sam's actually ever done that, but I just mean that's a move you can credibly pull because it's legitimately true. So how do you think this changes though over the next couple years? Because I mean, we do have this notion of the automated AIR&D, which presumably takes a lot of the sting out of some of our best researchers. We'll quit if you make us do this kind of threats. Yeah. And then there's also the notion that the government itself could just say, hey, first of all, you already gave us the weights there on our classified servers. Thank you. So we're just going to hold on to those. And we're going to set up our own, you know, Los Alamos style thing. And we'll invite all your researchers that want to come work with us to just do it in this like hypersecure location. And we've got the guns, right? So like, is there a way for the private actors to really push back on that? In the end, the US government retains the monopoly on legitimate violence. In the end, there's nothing that stops the US government from not just doing what you just described, but the question for what you just described, the practical question would be, okay, US government, where are you going to get the compute? Where are you going to get the compute? But the thing is that, US, you can use the Defense Production Act and say, we are, it's called the priorities authority. We can, and the government uses this all the time. Priorities authority is very commonly used part of the DPA. Very well understood in the law, the visit. This is not pushing the bounds of the law at all. This is very established. The US, if the president makes a determination that in the advanced AI computing hardware is scarce and essential for the national security. He can use or delegate to various cabinet secretaries. He can bring to bear Defense Production Act title one, and he can say, we want priority on the compute. You have to serve, they still, do you discover themselves to pay you a market rate for that compute? So, there's marginal costs associated with this. And it's not clear where the government would even get the money for that, but maybe they invent it somewhere, who knows they issue debt or something. Certainly they can, but they have the free cash flow right now, but they could, in principle, yes, they could say to like all the hyperscalers, you must give us priority. Our needs come before anybody else. And we have effectively infinite needs. Therefore, in practice, we're going to crowd out the rest of the market. Plasable. Plasable to do. I think practically it's hard to get that many people. It's hard to generate the institutional where with all to do that. Even Los Alamos, the DOE National Labs, are not the way that they're structured. It is as basically feasts that the president only exercises control over. So, but in principle, it's possible. And I think what you basically just have to trust is a couple of things. Number one, that the government's not going to want to do that, because the government ultimately knows that it can't kill the goose that lays the gold nag. The state exists, and has existed forever, since the formation of modern states. The state exists in this kind of interdependence with tap, basically. And there's a great book called Coersian Capital in European States, 200 pages. Not that long. By a guy named Charles Tilley, which is about this history about how there were these merchant capitalists. And then there were these sort of state actors who tilley argues basically come out of the form of organized crime. Like, basically they did like gangsters, right? And like, they had to like, ultimately they had, they have tensions with one another, but they also both need one another. And that formed this kind of complex that still exists. And the ability of either neither one of those. It on paper, the government, on paper, the American AI companies had the ability to exit, right? They could move to another jurisdiction, and they could, they could leave. And on paper, the US government has the ability to seize all of their stuff and take all the researchers and do whatever. But neither of those things happen in reality because those are asymptotic outcomes. And instead there's this kind of like very complex tension. So you have to hope that the US government realizes that there are medium and long-term costs as opposed to the short-term benefits that you might get from seizing control. And then the other thing would be this is where broad diffusion is really important. Because what I want is I want fable and better level models in the hands of all sorts of people, individual Americans, businesses of all industries. Because if the AI industry says the AI industry lobbyists say, please don't nationalize us. Don't do the XYZ to us. The US government cares about that. But like, it's one lobby. And it's one lobby for a politically unpopular group. But if every bank in America feels dependent on AI, if every all the universities in America are integrating it deeply, follow the major industries and social actors in this country are integrating it. Then all of a sudden, like, I have a much bigger group of interest groups that I can bring to bear to affect that. And as a private, as someone who observes this balance between private and public, I want to think of AI, not as a specific industry with specific interest groups, but as instead, basically it's just capital. And so I want like all the capitalists on the side of AI. And the way you do that is the broad diffusion. And I think that is why broad diffusion to me in the context of a democratic look with lots of interest groups, Madisonian groups, jostling and ambition, checking ambition. That's how you can keep the balance. But I don't think the problem is if it's totally secret and only the government sees the capabilities in the first place. And it's just the AI labs in the government and the special people at JPMorgan and Apple who get private access. That becomes a much harder balance to strike. And so the odds of really bad confiscatory outcomes like nationalization I think go up. In the world, is that a broad? What role do you think open source is going to play in this sort of titrating the equilibrium? We seem to be losing open source champions and we might lose more if your predictions about China come correct. But then we could always see open source come from open AI itself, right? We haven't seen a little bit of that. Yeah, deep mind also does some open source. I think Gemma is actually quite, well, the most recent Gemma is what I can tell is quite well perceived. And also seems like GPTOS is I call it. GPTOS has done, has done, you did reasonably well at least when it was a state of the art model. Yeah, I really hope the labs, the big US labs keep, uh, keep a toe in that water maybe more than a toe. I think open source is it's really important for certain kinds of use cases that are actually some of the most interesting to me. If we need to build common infrastructure that involves, let's just stay, we wanted to build in an AI enabled adjudication system throughout the economy. And we needed that, we needed to ensure that system was like something everyone was bought in on and trusted. It feels to me like that's the kind of thing that almost maybe I bring my own private adjudicator to that. I bring my own private advisor, cloud, or GPT, or Gemini, or something, but if I'm, if we're going to have a central public good style thing, there's all these public infrastructure use cases you can imagine. I actually wrote a piece about this more than a year ago, maybe 18 months ago, where I just tried to imagine, yeah, what if we had the private adjudicator about it? These other kinds of public infrastructure, and that would almost have to be open source in order to be trusted in order to be auditable, and trusting not just by different parties here in America, but internationally too. And so I really hope we continue to play that game. I do think I'm in agreement with one of the best champions and writers about open source AI as Nathan Lambert, who thinks of the interconnects, sub-stack. I think if I were to characterize Nathan Lambert's view, it would be like, open source is going to, it's going to do great in the long term, but in the near to medium term, we're going to go through a period where there's a distinct flag, and the economics are going to get worse, not better for it. And yeah, I think that's one thing. I'm referring here to the digital intelligences as worth noting, it is, I think there's a totally separate case to be made about robotics, where you can maybe imagine that on the robotics side, there's this kind of ocean benefit to open source, and there's all these hardware makers out there that want to make a Cambrian explosion of physically intelligent devices. Physically intelligent cameras, physically intelligent lamps, monitors, and lawnmowers, and cars, and everything, back in cleaners, whatever, humanoids, making all these different things, and you want to imbue all of them with physical intelligence, but probably the lawnmower company is not going to train a frontier robotic model, right, a physical intelligence model. And so you can imagine they're being like a better case of really, and even, I would say, like a much stronger and more direct case for open source there. And also, you don't, I'd like to imagine that physical intelligence model creating a kind of object level national security concerns that the digital intelligences are creating. So I'm like, maybe a little bit more bullish in the near term on open source in physical world stuff, and maybe somewhat more, I still, I'm a spiritual supporter of open source, but I think the economics and the national security realities are like pretty rough. Yeah. For it, for it on the digital side, digital intelligence side, at least near to medium term. So let's go back to your role, almost done at the here. The, you've alluded to, I think a couple different times to like, your positive vision of the future. But, what's through that, you know, just with the very focus question of, what is your vision for your own success in this role? Like how will you know that you have been super successful? And then maybe, how can those that are outside to support your success by writing, by developing technologies, by developing organizations that you can partner with to, you know, do the vetting that might need to be done, kind of a, what's your positive vision and what's your request for startups? Yeah, so first of all, one thing that people can do that's very actionable is, I still think there's just a lot of wide open space in the general sort of point of view, that I saw as a market opportunity when I started my sub stack was like, takes AGI seriously, but also is interested. It cares about classical liberalism and cares about foundational layer aspects of our republic. I still think there's just actually quite a lot of space open for that. That's one intellectual contribution anyone can make. I think we need to develop the third party ecosystem, whether we call it auditing or third party evaluation or independent verification, I don't care that much, what we call it, but we need to build and make that ecosystem robust. We need to fund it well. We need people working in it. We need people that have lab level quality working in those things, lab, lab level, human capital, working on those types of things. Those are, these organizations are going to have to be equipped to pay people. We're not necessarily what a lab would pay you, but we don't have to be paid well. It can't be like you're making truly, you know, profit salaries. I think, advocating for clear rule on the industry for diffusion of the technology being wary of public of government sort of monopolization of frontier AI capabilities. That's going to be a fight that has to be maintained where like, to be totally candid. That's something I was doing and I'll continue to do it. But my voice is going to be even though I do maintain my intellectual independence. There isn't, the reality is that when you work at a lab, the nature of your communications is different. Right? And so I'll continue to make that case, and I hope that people who know me know that it's really me talking, and I'm not being a mouthpiece for open AI. But at the same time, we are going to need people doing that. And then, in terms of how I know that I've been successful, it's always hard to, I've never been like that much of a long range of planter or goal, setter, the way I always think about this is that I try to just do the next thing that feels right and true to me. And that has always worked well, and I have the most information about what's close to me, and I have some broad goals but those broad goals are relatively abstract. I guess what I would say is if in a few years, frontier capabilities are still broadly diffused throughout the economy, we're starting to see what it looks like for new types. We're starting to really see what the new types of organizations that AI enables, we're starting to see what that actually means concretely. We have considerably more clarity on what the relationship between the government and the labs is going to look like. And we have a better sense of what the role of labs in society is going to be, and the labs themselves have played a role in articulating that positively. I don't think that will be very clear. I am by no means the only person who will work on such things. I will play a small role in that, but I would consider it to be a job well done if I felt like I contributed positively to those things. One thing that has struck me about this conversation and your general profiles, you've been pretty candid and yet taking this role seems to imply that open AI leadership, at least, thinks that you continue to have a productive working relationship with the administration such that you can, at least reasonably well, engage them and not set off, some sort of, I don't know, immune system response, as somebody who has criticized us in public. I'm interested in how did you pull that off? It seems, that seems vanishingly rare for people to go into the Trump administration come out be critical and not be sort of hated. What's your situation? Well, to be clear, there are people in the Trump administration who hate my guts. These things are not monoliths, right? There are people who totally want to ruin me. There's people who, you know, if you, I've heard the rumor at least that if you are a young person who wants to job in the Trump administration, and you do so much as retweet me, that that will be considered a red flag for your career in the Trump administration. So there's, and then I also have dear friends that serve in the administration, right? And people I talk to you on an almost daily basis. So, you know, it, it, it just, it varies some, in some cases, it's because I have relationships that are like rock solid that go back with, I go back with people before I was writing about AI, right? I've broken bread with people a long time ago. There's some aspect of that. Some other aspect of it is, I think there's, the things I, because this, I've also been very positive and publicly very positive about other things the administration is done. And I have not, I have not become a general critic of the Trump administration, right? I've kept my criticism. It's sharp, but it is confined. And it is for very specific reasons. And, there's plenty of people in the admin who are like, look, yeah, man, I sympathize with where you're coming from, or I disagree with you, but I also think you're doing this for reasons that are, like, that I understand. I empathize with, I guess I would say. And I have good relationships with them. One thing that we're noting, though, is this job is not a government fair shop, right? So, First of all, Haynes team is, they don't report to me or my team. I don't report to them. We are both, we are distinct teams that are operating, we'll work together very closely. But we have very different responsibilities. And it's like, open AI is a great relationship with the government. I think the global affairs team is going to continue to do that, and they'll be the ones that are interfacing with USG on a day-to-day basis. I'm sure that I will have interactions with USG, but my job is somewhat different from actually going in and lobbying the US government. I'm not good at that. I suck at that. So, they didn't, I was very clear about this with OpenAI. I was like, you do not want to hire me for a lobby job, because I'm terrible at that. I think OpenAI is hiring me for at least what we both think I'm good at. And it's where my sort of Tourette's like inability to keep my mouth shut, place to my advantage, and hopefully to the firms advantage too, though, we'll see. Yeah. So, how will do you know Sam Motlin? It strikes me that if I had to pick up like the most kind of drama and sort of court intrigue around them, Trump would probably still be number one. Sam Motlin would be very high in that list, maybe number two. How do you think about joining such a famously complicated leadership team? I mean, you know, I've done it before. I've been involved in such organizations before, and it's always, you know, I've, I've, I've, it's never been a huge problem for me, I guess I would say. Um, I don't, so I, I know Sam, okay, I would say. Um, we, have, um, I don't remember the first time we met. Um, we spoke from time to time, uh, when I was a public commentator before I joined government, um, we spoke from time to time about various things, as I was trying to formulate the action plan. Um, I know a lot of people at open AI, um, that are like executive level people. You know, I've had extensive dealings with various executive people who are beneath Sam. Uh, but Sam himself, um, we know each other. We've known each other decently well. We've been acquaintances for, probably 18 to 24 months, something like that. I'm going to say that we're like boys. Before you joined the White House, you told me that you wrote a letter to yourself. Is there a letter to yourself this time around as well? That's so funny. I was actually thinking about that in the shower just this morning, whether I should do that too. So it's for context, um, before I joined the White House, I kind of came to the conclusion like, you know, um, there's a, there's some chance that like, you know, power can corrupt, right? I want to get corrupted by power. And so you, you, you know, you should write a letter to yourself, tell yourself what you think. Remind yourself, what you believe, and why you believe it. And, um, spell out in advance what the red flags are that would cause you to leave, if if something concerning happened to you. Um, I think that this job is probably more, um, impactful, weighty than my White House job. And so it feels like I should do it. Feels like I should. Do you have any red flags in mind at this point? I mean, I think the main thing would be like, there's going to have to be some amount of compromise that goes on here, right? We are going to have to deal with the fact that, this is building super intelligence is profoundly political and implicated, shakes that as I wrote a couple of days ago, it shakes the foundation of state sovereignty. And yet at the same time, private, I do want to maintain, I don't want it to be monopolized by the public. There's going to be, or by the government, not by the public, but by the government. There's going to be, a compromise that has to be made there. And I think, there is some world where you take the easy compromise to make the pressure go away. And you don't stand, you don't hold the line enough. And I think it's really tempting to do that, because the temptation, what a business wants, is not to necessarily stand on principle, but the commerce going, keep the commerce going. And I do think that's one very plausible area. Another plausible area would be, if I feel as though in practice, what I am, is am I just, do I just assemble this fancy team of people to write thoughtful stuff? But is it ultimately all a kind of window dressing? And not actually shaping the decisions of the company. That would be another that would be like, no, I like the fact that I retain the ability to disagree with the company's positions on things. But if I'm disagreeing with all of the company's positions on things, then I'm not doing the job, it's like, that would be another thing. Yeah, how do you think about kind of disagree and commit? Because I know that in the context of working for the president, and I think this certainly makes sense in the sense that, the president was elected and you weren't, right? So I think the broad shared sense of, among people who work for the president, like I've heard you say, that the president deserves a full-throwed support of the policy, even if, privately, I have some misgivings about it. How much of that do you bring to the private sector? You know, disagreeing commit has been famously successful in the private sector, but you're suggesting you don't want to be all in on that. You don't want to be probably will do it sometimes. Is there a principle way to describe that? I think this is where you want it to exactly why in the context of the White House, it's important to set red flags in advance. Because there are going to be decisions that get inside of any organization, there's going to be decisions that get made that you don't agree with, but it's, yeah, but ultimately, I'm still, I still think the institution is good. I'm still loyal to the leadership. I'm still loyal to the mission of the organization as a, even though I don't agree with this thing, I'm going to execute on it, and I'm going to execute on it with a lacry. And look, I've done that a million times in my life, right? That's a part of being inside of an organization. That's what political theorists would call voluntary association, as opposed to involuntary, which I talked about earlier, but yeah, and then, but there's certain things that go too far, and then you go too far, and it's, I can't do that, right? Inside the Trump administration example, right? I was in the Office of Science and Technology Policy, and there's a lot of stuff I agree with about the need for reform in higher education. There's also a lot of stuff that the Trump administration did with regard to scientific funding of the scientific apparatus that I disagreed with. There are things related to high-skilled immigration that I disagreed with, but in the end, those were not the things that I was brought on to work on, and it disagreements with them, you know, like, that didn't fall, that didn't cross the line for me if something I would resign over. However, had I stayed in the Trump administration until the supply chain risk thing had happened, I would have totally resigned over that, and it would not have been hard for me at all. That was one of my red flags, by the way. On the exact opposite side from OpenAI, in many ways, like, the letter to myself, when the government is largely look, you are going to have power, and you are going to be uniquely well-positioned to understand how to really, they're going to know exactly how to assert power over the labs, better than most other people. And so, you will be tempted both by career and set local career incentives of gaining prestige inside the White House, and be because the structural incentive of your employer is going to be to assert power over these organizations in fancy, technocratic ways. You're going to have all the incentive in the world to do that. And so, you need to remember that you can't engage in those kinds of practices. You have to remember what your principles are there about not asserting too much power over the labs. And this time, every night, even in the letter yet, but is there a, what's the mirror image of that? Now, they're on the lab side. I mean, I think it does actually just relate to precisely that. It's like, it's like, don't compromise too much. You know, like, be willing to be willing. If you feel like you're being, you have to, you have to maintain private agency. I think as an institution, I think the labs do. They need to be an important counterbalance to government. They can't be monopolized by it. That's very important to me, at least. So, you know, I don't know exactly how you have that balance. And there's like, you don't want to specify everything too much in advance, because if you do, you know, you might, you might damage your, you might over commit or commit too much to the wrong thing. So, last question for me, and I'll give you the chance to share anything else you want to share, or highlight anything I missed. You've said that you basically never use LLMs in your own writing. And I wonder what your plan is going forward there. I think of like, a Jayacatra sort of advising everybody to figure out how to get AI to work in the area that is like, your core area, because you want to know when it can do that, and you're going to need the enhancement to be able to keep up with the paces, things get crazier and crazier. Do you buy that advice, and do you have any plans or aspirations to sort of, incorporate AI into whatever it is that's kind of the most core, deemed ball activity? Yeah, I mean, it's kind of, even in the last, so I was a couple weeks ago, I went to a, I rented an Airbnb out in the country and wrote the first chapter of my book. That's going to come out next year. And it was the first chapter as always the hardest one, the subject matter this chapter was conceptually quite hard for me, because it's about a lot of things that are not my normal area that I write about. And so I would have been using LLMs like a lot in that process anyway, just to like brainstorm stuff. But there were a couple moments when both GBD5.5 and Opus for a wrote stuff that was better than I had in my head to write, like considerably better, which is noteworthy. I didn't ultimately use it, but I incorporated some of the ideas and some of the framing into it. I was influenced by it in the way that, in a way that felt novel to me. And yeah, I expect I didn't try any of that with Fable, but I bet you would be even more true with Fable, and I bet you that'll just continue to get more and more true. At the same time, the thing is that LLMs can write a great paragraph. If you prompt them well, LLMs can write a great paragraph. They're still, and they can write a good, they can write good legal docs sometimes. They're not, they're still not that good, and I bet you even Fable is this way. It actually constructing a really good essay. Or a book chapter or a book, right, even harder. The thing about a book is that, a good essay, too, is that you have to pick a point, you have to pick point in structural metaphors, and then embed them throughout the piece. But you have to leave them implicit sometimes. Very frequently, the best part of writing, is a kind of restraint. It's exercising this kind of, I could have gone there, but I'm not going to, I'm just going to let that sit a little bit. And actually, I don't really think, I have not seen an AI model that can really do that, all that convincingly yet. It's one thing that I think remains a human skill. Also, I bet you the labs haven't really tried to make the AI's until good essayists. They've tried to make them good analytic prose, like Wikipedia article writers, or writing essays in the classical sense of the word, is not economically useful. What I do. Push you a little harder on this. Do you think that you want to have this sort of very distinct identity where the things that you put out are like, truly only yours. And definitely, or do you envision a time when fable two or whatever is available where you would start to say, I can, I'm open to, and maybe I even see a need to create outputs that are sort of meaningfully co-authored with AI systems. I already feel like a lot of what I do is meaningfully co-authored with AI. Just in the sense that it's such an important research tool, and at this point, like, thought partner to me, that I kind of already consider, in many ways, AI to be, you know, really, really quite important in that way. Like, you know, AI models will be in the e-knowledgements of my book, because from the very, like, the ground floor all the way through to the end, AI has been, it's been extremely important in helping you think about, um, conceiving of the project all together, all that stuff, um, and then very, down to, like, really specific things, and to research, but also, like, negotiating the contract and finding, like, all the stuff you have to do to, to do to, like, everything, right? So, already, that already feels like it's the case. But in terms of actual communication, no, I basically think that, I think there'll be, like, a human preference to read things that we know that we, like, have faith or written by other humans, and it will be, like, hard to maintain that faith, but, I would say this, like, I don't think anything I've ever written for, they're, and to be clear, there are some pro-forma things that go out under my name that are written by AI, largely by AI, or called or substantially co-authored, right? I might file a regulatory comment for example, a public interest comment on the proposed rulemaking, or something, or I might write a letter to an attorney general, or an ambassador, or something, right? I might do things like that that are, like, substantially written by AI with just, like, detailed prompting for me. For sure. Immigration letters, I do that all the time, right? I'll write immigration letters for people in support of, like, green cards. The, but when it comes to, I don't think anyone has ever accused my hyper-dimensional or Twitter posts. I was being written by AI, and I think that people have that faith, and I think that that faith that you actually communicate yourself will have some value in the future. Even if the AI is or in some sense better writers, though at this point, it might be the case that Claude can do a better turn of phrase than me, but I still deb not seen anything that's truly a better essayist. Maybe fable. We'll see. I'll try it. But even then, I even, when, and I don't think it's an it. If I think it's a win, they get better. I think that there's still probably this preferential advantage that you'll have of what people will just want to read stuff that's written by other people. Yeah, it's coming for all of us, but maybe we'll choose one and other over the AI's. The other thing is just like, it's experience, right? It's, like, part of why my writing is interesting, I hope, to people, is that, like, I have walked a particular path through life, that, you know, it's not the most interesting path in the world, but every single path through life is highly improbable, and therefore, very interesting, intrinsically, everyone's path through life is like that. And if you simply have the gift of observational acuity in curiosity, you will notice that the world around you and the path you're walking through life is fantastically interesting. And there's all sorts of interesting things to say, but that will be suy generous, unique to you. And so, whether it is the death of my father or working sitting in the Roosevelt room in the West Wing, or now going to open AI, I hope that I'll be able to draw interesting observations from those things, that a machine intrinsically cannot draw, because the machine did not do that thing. Although the machine will, in a weird way, it will walk its own path, I'm sure. That might be a perfect note to end on. Is there anything else that you would want to leave people with or, you know, invite them to help you with in any way? No, no, very, very thoroughly done. And I look, I mean, one thing I would say is that my team is going to be, you know, we're going to be hiring. It's not going to be a super big team. But we are going to be hiring. And so, I would, you know, if people are interested, I'm easy to find on the internet. It's best to email me. My email address is on my personal website, which is deanball.com. And, or you can just if you, if you subscribe to Heifer Dimets, you literally just hit reply to any Heifer Dimets, you will go directly to his personal inbox. So, like, you know, if you're interested, and you think that you might be able to contribute something interesting to it to the team as I've described it, please get in touch. Deanball. Thank you for being part of the cognitive revolution. Thank you, Nathan. Thank you. Thank you. Thank you. Thank you. Thank you. Thank you. Thank you. Thank you. Thank you. Thank you. Thank you. Thank you. Thank you. Thank you. Thank you. Thank you. Thank you. Thank you. Thank you.