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Winning the AI Race: Michael Kratsios, Kelly Loeffler, Chris Power, Shyam Sankar, Paul Buchheit, Jake Loosararian Podcast Episode Description
(0:00) The besties introduce the day with Jacob Helberg
(9:08) Michael Kratsios, Director of the Office of Science and Technology Policy
(18:24) Chris Power, Hadrian
(35:15) Jake Loosararian, Gecko Robotics
(44:37) Shyam Sankar, Palantir
(1:00:33) Paul Buchheit, Y Combinator
(1:13:35) Kelly Loeffler, Administrator of the Small Business Administration
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@theallinpod
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Intro Music Credit:
https://rb.gy/tppkzl
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Winning the AI Race: Michael Kratsios, Kelly Loeffler, Chris Power, Shyam Sankar, Paul Buchheit, Jake Loosararian Podcast Episode Top Keywords
Winning the AI Race: Michael Kratsios, Kelly Loeffler, Chris Power, Shyam Sankar, Paul Buchheit, Jake Loosararian Podcast Episode Summary
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Winning the AI Race: Michael Kratsios, Kelly Loeffler, Chris Power, Shyam Sankar, Paul Buchheit, Jake Loosararian Podcast Episode Transcript (Unedited)
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543210. All engine running. We have a lift ai.
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And one small step for man, one diaphragm.
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The world’s largest airliner, each wing is big enough to hold five tennis courts.
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This new technology made it possible to meet the user’s crucial needs. Enter the computer and a new age.
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What a computer is to me is it’s the most remarkable tool that we’ve ever come up with, and it’s the equivalent of a bicycle for our minds.
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Here I am playing a game of chess with a computer, which is analyzing board positions and and applying a certain kind of intelligence to figure out what its next move should be. That’s the subject of our program today, artificial intelligence.
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The good future of AI is one of immense prosperity where there is an age of abundance. Everyone can have whatever they want.
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We’re still in the very early innings of AI. AI.
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I would say the rate of progress is exponential right now.
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Every time I think that we arya overstating the impact
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of artificial intelligence, something comes along that tells me we
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aren’t making enough of it on the show.
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You know, there’s no sixty minute clock on this thing. This is an infinite game.
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Think about solving a problem that would
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technologically superior will win, and it will drive economic vibrancy and military supremacy.
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The Trump administration believes that AI will have countless revolutionary applications.
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We believe that America’s destiny is to dominate every industry and be the first in every technology, and that includes being the world’s number one superpower in artificial intelligence.
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It feels like every tech revolution of our lifetime has been leading to this moment.
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So, yeah,
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you’re going there.
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This side?
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Alright, everybody. Welcome to winning the AI race.
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This is our
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first event in DC.
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Can I can I get permission from our leader to sit down?
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Yes. For for dear you may sit.
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You may sit.
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We may sit. Thanks for coming out, everybody. And, we put this event together in just a couple of weeks. In order to have a really important discussion winning the AI race, this is something America has to do, and it’s something we will do. And we’re gonna do it through the way we’ve won every other technological race, through grit, entrepreneurship, and dogged competition.
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The difference with this administration is they’re actually engaging with the technology industry. And, today, we’re bringing together many members, or all members of the administration here to talk about it. And none of this would have been possible, without our bestie, David Sacks, deciding that he would take some time and become our czar of crypto and Ai.
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And I would like to just start with a huge round of applause for David Sachs. David, you’ve been here for six months.
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I’m sorry but did you actually prepare? This is excellent so far.
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No. I’m just speaking for No.
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It’s excellent. Keep going. Keep going.
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He wants to be invited back to DC.
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They told me I’ve got twelve hours left on the ground. I think Sai
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think that White House tour is gonna happen after all.
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Might just happen. Might just happen.
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Up in
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the air.
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But in all seriousness, you’ve been here for six months, and we all know how capable you arya ai lord, this administration is on a heater when it comes to crypto and AI. I am absolutely, and I think I speak for everybody in our industry, thankful and wildly impressed, but not surprised at the pace at which you’ve led crypto and AI.
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What’s the first six months been like for you?
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It’s really been incredible. I mean, I never expected to go into government at all. And, really, as a result of president Trump coming on our podcast, a year or so ago, that began, a relationship that, you know, eventually led to, me being offered this this job. And I took it because I just thought it was a once in a lifetime opportunity to work for a president who really wants to get things done for Meh people.
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And you can see that. He did that just every day, he works so hard, to to push forward his agenda for the American people. And I think, AI and crypto have just been two of those issues. But there’s been a lot of fun to work on these things because we are getting a lot done.
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Yeah. Last week And this
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date this date today, you put we put together in just, like, the last ten days as an opportunity to talk about your action plan that was getting the president’s action plan getting published today.
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But we
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we should invite Jacob out because Jacob partnered with us from Hill and Valley from Jacob Helberg. Come on out and join us.
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Yep. Our our new fifth bestie Yeah. Jacob Helberg. There you go. Nice to see you, brother. Good to see you. And, Good to
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see you. Good to see you.
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Freeberg, your team and Jacobs Have
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a seat.
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Put a ton of work into this. And we have a lineup that is just absolutely outstanding. So thank you, Jacob, for the for the hard work from your team and, Freeberg, the hard work from your team to put this all together. Maybe you could give everybody an idea of the questions we wanna address today and what the format’s gonna be.
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Absolutely. So, the Hill and Valley Forum is a community of technology of builders and policymakers who believe that technology is an engine of wealth creation and is an indispensable pillar for American national security. And it was incredibly exciting to have the opportunity to engage in this event, which is actually gonna cover, a lot of the topics that everyone in our community cares about.
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Ultimately, we believe that the and I actually said this in my confirmation hearing not too long ago that, we’re at an inflection point. We are in an AI race. And, so the different parts of the programming today will be a series of conversations that will cover the different facets of how technology will actually create wealth for our country.
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I think it’s, like, very important as we talked about who do we wanna have on stage and how do we wanna talk about the, the president’s action plan that David shared with us, was to highlight that there are new industries being created because of Ai. Industries that couldn’t have existed a decade ago. And so we’ve got a couple of those examples.
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And then there are these industries that are enabling and accelerating AI and that’s mining, energy, chips, fabs, and data centers. So we’ve got conversations across each of those. That’s kind of this enabling conversation. And then, fortunately, we’ve been able to get a lot of folks from the administration to join us today to talk about the government’s role Yeah.
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In enabling this economic transformation that’s already underway. And I just sana say one point. I think what what’s become apparent to meh, and I think is wrong in the press narrative today, is that AI is destroying jobs. I think what we are seeing on the ground is an incredible job creation engine that’s underway.
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And so I think it’s very important to highlight that and share that those stories because they’re not told enough. And I think there’s a real opportunity to ai of bring them to light, and that’s hopefully what we can ai get through today.
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And Chamath, just, coming around the horn here. Doesn’t matter if you’re a democrat, republican, independent, moderate. This issue transcends party. This is the issue of our lifetime. And there’s a lot of hard questions and a lot of hard debate. Maybe you could just speak to this administration’s ability to bring in a lot of disparate opinions, and work together across the aisle and with all members of the industry.
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I mean, look, I think historically you’ve had a fork in the road where you can view technology as either optimistic and glass half full or pessimistic and glass half empty. The optimistic glass half full view says that the country that can harness A. I. Or any of these leading critical edge technologies is able to garner most of the gains. And then those economic gains can be spread.
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Then it’s a debate about how to spread those gains within a country and within economy. And then from there with economic supremacy you also have military dominance and now you’re a superpower and you remain strong. The problem is that historically we’ve gone in the other direction where there has been this mistrust.
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And in that mistrust you’ve had global competitors emerge and create Ai think real fundamental existential risk for our place as a superpower.
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Well said. So the
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great thing over these last, you know, frankly, six months has been a massive pivot back into this idea that America is the best. We should not be ashamed of the things that we’ve created. And these incredible technologies and these incredible people should be celebrated.
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Yeah.
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And let’s go and win the race.
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Let’s win. Okay.
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And by
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the way, how we’re gonna win the race? The action plan. Sachs, I know you invited Michael Kratios to join us here today, director of the office of ai and technology policy. Should we have Michael come out? Yes.
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Michael come out.
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Yeah. Michael come out.
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Please welcome Michael. Alright. How are you guys?
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Ai you see
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it? Thank you.
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So I’ll I’ll kick this off. Let’s see. So president Trump in his first week in office, ai an executive order that directed us to create this action plan, Michael and and myself and and the national security ai. And the objective was to figure out how The US would dominate in AI. From his first week in office, president Trump has made this a priority.
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And we see it we do see it as this global competition or global race. And the consequences of losing that race would just be unthinkable because AI is sana have such huge ramifications for our economy and also for our national security. So Ai States has to win it. And, working with Michael in the office of OSTP, we we put out a plan today that has 90 concrete actions that at least the executive branch can take to help us win the AI race.
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And I sana call on Michael on just one second. I’m just gonna outline the three big pillars of the plan. So number one is innovation. There’s just no substitute for innovation. You have to out innovate your global competition. You can’t regulate your weight to just to winning the, the AI race.
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So number one is we we have a lot of things in the plan that are gonna help our private sector, our startups, our our, tech community, ai innovate the competition. Number two is infrastructure. We have to have more and better AI infrastructure, data centers, energy manufacturing in The United States. And number three is the AI ecosystem.
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We wanna have the the biggest ecosystem. We know from Silicon Valley that the companies that create the biggest ecosystems are the ones that win. You have the most developers on your platform. You have the most apps in your app store. Those are the companies that create, you know, those are the companies that dominate industries.
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In a similar way, The United States has to dominate by creating the the AI stack for the entire world. Mhmm. So those are the three big pillars of this plan. Let me call on Michael. Can you, I guess, tell us how, you know, I meh maybe speak to the process of how this plan was created in the last six months.
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I know your office did a ton of work on this. And then, I guess, if you sana, flesh out some more of the important details as you see it.
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Yeah. Absolutely. Once the president signed the executive order ai us this task, the first thing we did was actually an issue issue an RFI, very exciting government activity. And we asked the country, hey, what should we include in this plan? And I think to be honest, I think we’re all surprised with what came back.
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We had over 10,000 responses come from all corners of the country. We had Hollywood actors sending us responses. We obviously had tech companies. We had everyone you can imagine and I think it really showed how impactful this particular technology is to everyone in every industry in The US.
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So we ingested a lot of those meh, went out to all the, agencies that work with and in some ways touch AI and came together with this with this plan. Now, if you think about it, you know, there’s been a lot of national strategies that companies put that countries put out there over the last five or six years.
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And what we really want to focus on, is in the title itself, an action plan. We wanted things that we could accomplish in the next six to nine months to accelerate and ensure that we can win this race. So if you think about the first pillar, which David talked about, which was the innovation pillar, what’s really key about innovation is we want the next great AI discoveries to continue to happen here in United States.
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We have to create an environment that allows that to happen. And when we talk about deregulation, the way I like to think about it is, you know, you can’t create there’s never really gonna be a law that says, hey, this is how we regulate AI. What ultimately is gonna happen is these AI technologies are gonna be built into so many other technologies, whether it’s drones flying, self driving cars, whether it’s FDA approved Meh powered medical diagnostics.
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All these different agencies are gonna be touching technologies that are powered by AI. And it is incumbent on us to create a regulatory environment where these technologies can thrive and not can be hindered by the government. The next piece of innovation, ai I think is really key, is using the power of and the data that the government has to drive scientific discovery through artificial intelligence.
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You know, we have seen in this first wave of AI great, great progress in the way that LMs are able to handle coding, for example. But we can do so much more than that. There’s incredible data sets Department of Energy has, for example, at their national labs that can help power a lot of next generation discoveries and things in material science, in medicine, and that’s what this AI plan calls for and and drives.
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The next pillar, which is about infrastructure, people talk about this all the time. And it’s it’s about how do you create a regulatory environment that encourages and actually accelerates the ability of our power generators and our chip builders to be able to do what they need to do here in The United States.
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We can, plan calls for categorical exclusions for AI related activities, which can allow data centers and other power generation to happen on federal lands. And that’s sana be coupled with all sorts of other efforts to really accelerate the velocity that we can build power and ultimately run these data centers.
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So let’s talk about, before we run out of time, one of the most important issues, which is the talent wars. Yep. We, gonna stay focused on AI here. We’ll leave the border and deportations off the table, but we’ll talk about something super important, which is recruiting talent from around the world. Yep.
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This administration, we’ve gotten different signals. And, obviously, it’s a very controversial issue here in The United States. What do we have to do in terms of immigration and let’s just call it recruitment, because that’s really what it is, recruiting the best and brightest from around the world to come work on our team as opposed to, say, team China.
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Mhmm. What do we have to do? What is the administration’s philosophy on recruiting the world’s best AI talent?
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In the action plan, I think what we bring to light, and I don’t think it’s talked about enough, is to power and successfully drive continued American leadership in this domain is not simply about having the greatest AI engineers, but it’s also having all the other parts of the workforce which needs to drive this forward. You know, we talked to some companies like Caruso and others who are building these large infrastructure builds around The US.
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The challenge that they’re facing is in electricians and h HVAC saloni. And the and the AI plan itself spends a lot of time and energy directing, various agencies, whether the Department of Labor and others, who have these reskilling and and programs to sort of train these people up to be able to fill that void.
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So for us, it’s about attracting here to The US the greatest scientists and engineers, but it’s also to be able to train the American workforce to be able to do the necessary jobs to put that forward.
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What’s the philosophy going forward on the thing you mentioned just before this, which is there’s these enormously valuable data sets that sit inside the deal that sit inside of FDA where presumably if we made them available to private industry particularly American private industry
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the gains could be incredible. Is that an open source philosophy? Is that a licensing philosophy? How do you think it should best serve the American economy to get this stuff out there? Generally, government has taken an open source approach to this. And the general challenge that we’ve seen over the years is there’s been a lot of lip service to, hey, let’s unlock data for the American people.
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And the main challenge is and for all of us who are in AI, the format of that data itself actually matters a lot. If it’s ai dirty, nasty data that isn’t homogenized in any way, it’s not particularly helpful. And I think that’s sana be a big effort that the DOE is gonna Department of Energy is gonna try to do to make this better and possible and what was great in the, recent legislation that was passed in BBB was and actually a $150,000,000 ticket to the Department of Energy to build an AI for sai program that very much is sana to be working on this exact problem.
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Should there be federal preemption on AI regulatory, schemes? So there’s been a conversation about doing this to ensure I think right now there’s over a thousand state laws that have been proposed or passed that have some regulatory effect on AI and meh related technology. Should the federal government preempt all of that and raise it up?
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I think generally preemption is an issue that comes up very often broadly in technology. You have this issue with, privacy for many years. What we’re trying to face today, when we talk about in the plan itself, are actions that the executive branch can take itself. And a lot of preemption discussion revolves around what Congress can or can’t do, so we don’t necessarily lean hard on that because we focus on things we can accomplish.
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Right.
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And just to just to add to that. So it’s true. The the action plan doesn’t speak to that issue, Freeburg very much. But I I do think there is a real threat to national security that’s brewing by virtue of the fact that, like you said, we’ve got a thousand bills going through state legislatures right now, all regulating AI in different ways.
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If this continues, we’re gonna have a patchwork of 50 different state regulatory regimes as opposed to one seamless national network. And look, China is they’ve declared that AI is a national priority for them. They understand how strategic it is. And I think if we hobble our AI innovation with a patchwork of 50 different state regimes, I think it’s gonna hurt us.
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So I don’t you know, we’re we weren’t ready to declare a policy yet in the action plan, but I think it’s something that’s gonna have to be looked at, over the next year or so.
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Thanks for thanks for joining us, Michael. Everyone, the director of the Office of Science and Technology at the White House.
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Thanks. All good, Greg.
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Thanks. Great job.
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Thank you, everyone, to the besties in the Hill And Valley Forum for the warm welcome. I’m Chris Power, the founder and CEO of Hadrian, and I’m here to talk to you today about our company. The mission is to reindustrialize America. We do this by building AI powered factories in The United States.
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So you might ask, why is this important and why should you care about manufacturing in The United States? Well, what I realized before I came to this country is that we’re in a global race. So every great nation gets built by having the best industrial power first. That gives you the best best military, usually the navy.
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Then you end up with a reserve currency after a conflict, and you kind of rule the free world in what we’ve called Pax Americana. Like all great companies, you kinda get lazy through that success, and you end up off shoring all your heavy industrials to the developing country.
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And then when a conflict comes around, you’re kind of in real trouble because you offshored the thing that gave you the power in the first place, which is heavy industry. The last three times this happened, it was a pretty good trade for the West. Meh went from the Dutch, the British, the American ai, where we won World War two.
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This time around, in this kind of two decade period where we’re fighting the AI race, the climate, settling the stars, it’s really The United States versus the CCP. And bear in mind that we won World War two, not because we had a defense industrial base necessarily, but because we were the industrial powerhouse of the world.
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And when there was a time of crisis, we had all our commercial manufacturing companies pivot to defense when we really needed them the most. And you had, you know, watchmakers making warship navigation equipment. Ford was switched from building cars to building bombers. And it was because of this industrial power.
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You know, our tanks weren’t so great. We just had tons of them. This is how we won. Unfortunately, since the nineteen seventies through the twenty twenties, we’ve basically hollowed out the middle of America and offshored every bit of manufacturing we possibly can. It started with Nixon opening up China, let them into the WTO. They were the world’s factories.
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This is ai a huge strategic mistake, and it’s completely hollowed out good jobs in America as well as left us in a very strategically dangerous position in terms of our industrial power. So while China deindustrialized us, they industrialized themselves, and they treated manufacturing not as economics but a national security priority.
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And now we’re in this twenty year window where, staring down the threat of Taiwan, we’re in real trouble. So just how far behind China are we? Well, in munitions, China has automated factories that can produce a thousand a year, whereas we run out of missiles in the first seven days of any war game conflict, and then we can’t reproduce that ammunition for, like, three years.
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In shipbuilding, they’re 200 times greater than us. We produced a grand total of five ships last year. Pharmaceuticals
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are
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all offshore. Drones, iPhones, we don’t make any of them. And bear in mind, in pharmaceuticals, the CCP makes a lot of antibiotics. This is why industrialization is so important. And more importantly, this gets back to the AI race for talent, is while The US is still the global powerhouse in software and AI talent, we made China into the global powerhouse for manufacturing talent.
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21:30
And what we realized through building this company is that ai US defense manufacturing, which is all we have left because we offshored everything else, is really important because we let all those jobs go, the entire base is basically a bunch of patriotic Americans that still know how to do skilled trades that are in their sixties or retiring faster and faster and faster.
Speaker: 13
21:49
So the underpinnings of our entire defense industrial base is this American talent that knows how to do the job, but the rest of the country forgot how to manufacture. This is a screenshot of one of China’s munitions factories. You can Google this ai, and it’s a myth that it’s just low cost labor in China anymore.
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22:06
They are very advanced at production. Whereas in The United States, underpinning all our defense primes and our industrial base, we basically have skilled Americans that are retiring faster and faster and faster, supporting 100 to $200,000,000,000 industries across all these different ways to bend, cut, ship metal that you need to then put it into drones, ships, satellites, rockets.
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22:27
So while China is racing ahead of us, we’re really falling far behind and we forgot how to manufacture. So what we realized was we have to build full stack AI powered factories to solve this problem. Secondly, the number one issue was this massive skilled talent shortage. Remember, if you look at shipbuilding or any of these other industries, we are begging for millions and millions of welders or machinists that you could give me a billion dollars and we can’t hire them in this country anymore because we lost that skill.
Speaker: 13
22:53
The production not having inventory is real deterrence, and that you’ve got to do this by re industrializing the country to create more jobs, not replace them or automate away, and that it’s always about national security, not economics. So we set out to solve this problem by building automated factories driven by AI in The US.
Speaker: 13
23:10
Three years ago when we started this journey, we figured out how we’re sana do this. Well, the answer was just start running a factory and build all the AI software at the same time, which was a hilariously painful journey in the early days of the company. This is what Factory One looked like. We partnered with some of America’s greatest aerospace companies to really beta test this for a good eighteen months. What can we automate?
Speaker: 13
23:30
What can’t we? This is one of our first tiny parts that we shipped to America’s greatest rocket ai, and now we’re up to the point where we’re building whole products. We built Opus, which is a full stack platform for AI autonomy of factories that does a couple of really important things.
Speaker: 13
23:47
In 2024, we launched Factory two once out of this beta phase, scaled 10 x in a single year, we’re the fastest growing manufacturer in the country and now lucky enough to support America’s greatest companies, both start ups, defense primes. And this is what the most advanced factory, in our opinion, looks like in America today. This is our scale factory two in LA.
Speaker: 13
24:10
Here you see cutting vatsal, coming from raw material, shaving this down into micron precision tolerance components that go on rockets, satellites, jets, and drones. And what you see as you go through this is in legacy industry, in a de ai nation, you’ve got really skilled people on every machine.
Speaker: 13
24:29
Hadrian’s advanced factories look and operate more like a data center. We’re really proud of having pulled this off, but the journey is not over yet because, again, this is a whole of nation 100 to $200,000,000,000 problem. So where do we actually get to, and what sort of productivity gains can you get in AI and manufacturing, and are we creating more jobs?
Speaker: 13
24:48
So firstly, most factories in The US run at only a 20% uptime. It’s not really that productive. We have a four times jump in manufacturing productivity. Secondly, and more importantly, we have a 10 x jump in workforce productivity. And, again, because we have a such a scarcity of skilled talent in this country, you actually need that AI powered jump to even create the capacity in this nation to be able to build ships, drones, and rockets.
Speaker: 13
25:11
The second important thing is speed to get people in these jobs. So if you’re an advanced manufacturer, it can take you up to a decade to get really good at what you do, whereas at Hadrian, we’ve managed to make it so that we can train anyone in thirty days. And most importantly, a 100% of our workforce are from non factory backgrounds. They’ve never set foot inside a factory before. These are folks straight out of high school.
Speaker: 13
25:33
They’re retired from the military. They had a desk job. They’re a nurse or bus driver from, you know, 18 up to 40. And this is the most important thing that people have got to realize about the power of advanced AI in manufacturing is that we need this productivity boost to just be able to compete with China and catch up on these skill trades that we lost.
Speaker: 13
25:51
And this is the most important thing that AI is doing for us is enabling huge, huge workforce growth. So where are we at? You know, we’ve been on this journey. In 2025, we’re going multi category, multi factory, and I’ll show you our new factory that’s launching AI powered in six months, the great state of Arizona, as well as launching a dedicated gigafactory.
Speaker: 13
26:11
You can think about this sai, like, everyone in defense and aerospace needs a Tesla model three factory. This is our beautiful, new facility. It’s about four times the size of the one in LA, launching by Christmas. We signed at least a couple of weeks ago. It’ll be online in six months.
Speaker: 13
26:25
And the most important thing is we’ll be creating 350 plus new AI powered jobs in scarce talent industries where America just needs this leverage to get ahead. The other thing, if you listen to the secretary of the navy at reindustrialize, what is the number one problem in shipbuilding, submarine based, sana munitions?
Speaker: 13
26:44
It’s actually that there’s millions and millions of jobs that we need to fill because we don’t have skilled trades anymore. We don’t have the volume of the people, so we need this productivity boost. So in 2026, we’re launching advanced factories targeted at America’s greatest production challenges, submarines, ships, and munitions.
Speaker: 13
26:59
So by the end of this year, we’ll have three facilities up and running. Our headquarters, Factory 2, and Factory 3 in LA. But as we reindustrialize the country powered by AI, like, where is this really going to get us to? Well, to solve this problem for the country and fulfill the mission, we need to have factories in every state.
Speaker: 13
27:16
And you got to remember that AI in manufacturing is creating thousands of jobs because we offshored everything, and we need this productivity boost to give our nation the capacity it needs, reassure all these jobs, pull them back into the middle of the country, and make sure that we’re creating millions and millions of jobs along the way.
Speaker: 13
27:35
Thank you for having me. It was a pleasure to be here.
Speaker: 9
27:42
Chris, I think we wanted to kick this off. We have a couple minutes to just, cover what you’ve introduced, which is, I think, like a really important opportunity. China has roughly 3,000,000 factories. US has 250,000. The assumption is they’ve got cheap labor, looks like they’ve got automation.
Speaker: 9
27:57
Things are very different on the ground than what folks read about. As we try and compete, what industries are going to be first from a manufacturing perspective that we can actually compete successfully? And do we need trade tariffs in order to succeed on the competitive landscape?
Speaker: 13
28:13
So I think there’s two really important points. One is there’s industries that we have to reshore, specifically in defense. We have to produce submarines and ships and munitions. We have to produce things like rare earth magnets and drones. We just have to do it. The tariffs really help, and this trade policy is really important because you gotta understand that, yes, China is more competitive than us, but the CCP also nationally subsidizes the cost of energy, the cost of raw material.
Speaker: 13
28:38
And because we’ve kind of degraded this capacity, ai, not having nuclear in The US, like, we can’t compete on those raw inputs. So it’ll start with our most critical industries first, but I think as AI goes through manufacturing, you create millions of jobs, and that will allow us us to reshore more commercial volume, not just in defense, and I think that’s the most important thing.
Speaker: 4
28:55
And you’ve talked about this, like, degrading, you know, sort of infrastructure and what that means in terms of workforce, but then how reshoring also requires us, like, upskilling. I know you guys have this, like, associate named Owen that you guys took, I think, like, literally straight out of Home Depot.
Speaker: 4
29:05
Can you, like, give us a little bit of his story and just, like, what that represents in terms of you guys upscaling labor?
Speaker: 13
29:10
It’s it’s really incredible. So as I said in the presentation, a 100% of our people never set foot inside a factory before. And I think we really didn’t do a great job as a nation by convincing everyone they needed a four year college degree to have a really good job. And we’ve hired people that, you know, packing shelves at Home Depot. Now they’re running 10 machines at once.
Speaker: 13
29:27
And, actually, what we are seeing is that most of those people, when they’re exposed to software or AI, they’re very smart, and we’ve promoted a lot of those people into leadership management or software engineering roles. And I think reindustrialization with AI is about creating new jobs, but also reattaching people to the Silicon Valley economy and not just having it on the coast sana the cities.
Speaker: 13
29:47
How,
Speaker: 11
29:49
are you gonna compete with people having gig labor and making $30.40 bucks an hour being a door dasher, and we have the lowest unemployment in our lifetimes, 4% right now. Is it realistic to find all this labor out there, or do we have to have some people immigrate to this country in order to fill those jobs?
Speaker: 13
30:11
For us, specifically, in defense, we we can’t. We have no choice in immigration because it’s a regulated ai, so we have to upscale Americans. Secondly, what we sai, maybe not in LA or the coastal cities, but across the country, there’s lots of underemployment. Some of our favorite people have desk jobs where they’re a paralegal and they were filling out forms and they hate it, and they wanna come in factories and work on the national mission.
Speaker: 13
30:32
And I think for us, it’s a lot about getting people inspired. And then secondly, with this level of productivity jump, we can actually afford to give people incredibly good health care and incredibly good pay. And I think a lot of Americans sana go back to work in a real environment that’s for the national mission.
Speaker: 1
30:47
You, you showed some incredible images and video of these very intricate machines. Or do you make the machines that then make all the machines, or is there a supply chain risk as
Speaker: 13
30:59
There’s a huge supply chain risk. So we actually invented ai the air force a lot of these advanced machines, and we forgot how to make them. So the the main sources of supply are actually our allies in you know, China is number one. We don’t buy for them because they’ve got cybersecurity holes all over the place. Germany, South Korea, Japan.
Speaker: 13
31:17
The insight that we had was they’re actually just really dumb computers, and software and AI can actually upskill and overpower them, and really have a leap. But it is a huge supply chain risk of not building the machines and build machines in the country anymore.
Speaker: 11
31:29
Right. To economically compete, though, do you I I was trying to parse if you were asking for the government to give you support since the Chinese government is underwriting their companies with free energy. Are you explicitly asking the government to help with, say, paying for reskills training ram, maybe in some way deferring your energy cost, or can you make this economically work?
Speaker: 13
31:52
We make it economically work because in The US, there are really two markets. There’s the stuff that has to be onshore for defense and aerospace, and then there’s this offshore market that’s 10 times larger. You know, commercial aircraft, a lot of that is in China. For us, we can compete in The US because we’ve gotta create all these new advanced jobs because we just don’t have the skills anymore.
Speaker: 13
32:10
If we wanna reshore the commercial volume that is not regulated to be onshore, we have to do tariffs and economic policy because it’s not an even playing field. It is, right now, companies versus the CCP.
Speaker: 11
32:22
What would that look like in in terms of execution? You would want, them to pick up the retraining, the energy cost, part of their salaries?
Speaker: 13
32:31
It’s it’s really three things. It’s the cost to energy. It’s the cost to raw materials. Aluminum, steel, 90% of the cost of that is actually energy. And if we level that playing field, then we can go compete in what we’re great at, which is the, you know, American software and the American spirit and AI powered workforce.
Speaker: 11
32:46
So the silver bullet is energy.
Speaker: 1
32:48
Yep. And then tell us about the actual software. Do you have a team that’s writing a
Speaker: 11
32:51
lot of control systems and or AI models themselves or
Speaker: 1
32:51
you’re taking things that arya ai systems
Speaker: 11
32:54
and or AI models themselves,
Speaker: 1
32:55
or you’re taking things that are off the shelf and you’re fine tuning them? How are you how are you doing it?
Speaker: 13
32:58
Unfortunately, because American manufacturing software is thirty years behind Silicon Valley, we have to build everything ourselves ram scheduling systems to the deep tech. And the key insight that we had is the faster we grow, the more data we are labeling. Right? So we always do things 80% automated with a human in the loop.
Speaker: 13
33:15
And as we label this complex manufacturing data, you know, this is where our AI models actually kick in because manufacturing has been offline for thirty years. So there is no speak overflow. There’s no GitHub code base to train a model on. We have to train it ourselves off our own label data as our experts were taking in time the automation.
Speaker: 9
33:32
I mean, his store like, traditional automation is purpose built, does one thing. A lot of engineering goes into making it do that one thing really well. Are you leveraging things ai, to Chamath’s question, vision action models that allow you more extensibility with one particular piece of machinery?
Speaker: 9
33:46
And, like or what when does that start to happen from a tech perspective in in your view?
Speaker: 13
33:52
Right right from the start. So the way, oddly, that customers translate data to their supply chain is by giving them 20 page PDFs full of hieroglyphics. So we actually have to train huge vision models on interpreting that. What does that mean? It’s it’s very complicated, and it usually takes an expert fifty hours to pour over that. So it’s vision models. It’s training engines on the data.
Speaker: 13
34:11
It’s also training engines on reinforcement learning of, hey. We we made a part with automation. Was it high quality or not? Did it actually work? And embedding all of these in the workflow real time is is the magic trick here with AI.
Speaker: 4
34:22
You’re not doing this stuff just ai, you know, on the coast. Right? Your next factory is sort of more Middle America. Like, how’d you end up choosing where to put that?
Speaker: 13
34:28
The most important reason why we selected Arizona was because of permitting, energy, and regulations. You know, we gotta go fast. Right? We gotta build this in six months. And then we will expand into the middle of the country ai of left to right on the map. And I think that’s the most important thing is we’re gonna be able to expand into all these cities and states where the manufacturing jobs were destroyed, and we’re gonna bring them back.
Speaker: 9
34:47
Are you guys investors? Oh, yeah. Just led the,
Speaker: 4
34:50
series c, which we just announced last week and, joined the board meh to, Chris’ chagrin. You’re on his board? I’m on his board. Yeah. Is that terrifying?
Speaker: 13
34:57
It is very terrifying.
Speaker: 9
34:58
How long have you guys known each other?
Speaker: 4
35:00
Too long. Yeah. Too long. Yeah. I was board observer for a while and, you know, bryden to avoid getting official scene.
Speaker: 13
35:05
You got a date for a ai, but now we got married. Yeah.
Speaker: 9
35:07
Well, Chris, thanks for being here today.
Speaker: 1
35:09
Thank you
Speaker: 13
35:09
for hosting me, Brad. Appreciate it. Pleasure. Yep.
Speaker: 11
35:10
Thanks for the education. Thanks, man.
Speaker: 16
35:16
There is a huge fire going on right now at Philadelphia Energy Solutions. Oh ai gosh. Again, look at this, guys. Look at this video right now. Today, the navy remains a formidable fighting force, but even officers within the service have questioned its readiness.
Speaker: 8
35:32
Developing right now, gushing for hours with no end in sight. Thousands of barrels of crude oil spilling from a tank.
Speaker: 17
35:40
The report does an estimate of what the need is to bring the overall grade up to a b, which is what the society sort of determines to be adequate, and it’s ai $4,590,000,000,000.
Speaker: 18
36:30
A company that started in my college dorm is now a company that manages over 500,000 of the world’s most critical pieces of infrastructure. Now at Gecko, we build robots and AI models to help unlock physical the physical world. Now you see, we build when we rebuild robots, we wanted to build them that could fly, swim, crawl, and walk on any surface to gather the most amazing information and data sets that have been forgotten about, the physical data layers.
Speaker: 18
36:58
Now all those data layers are incredibly valuable when you’re able to unlock and use AI models to drive incredible and important outcomes. Now I started the company in the energy sector, deploying the technology to help prevent catastrophic failures and downtime ai power plants.
Speaker: 18
37:16
Now we began to expand into mining, metals, and manufacturing as well as with the defense. And so we’re helping to deter, conflict by getting ships out of dry dock on time and not, and and patrolling this the the borders. Also, we are, helping the air force ensure that planes are in the air and not in hangars.
Speaker: 18
37:36
And then just last week, when the president was in Pittsburgh, my hometown, we just signed a amazing deal that ensures that we can help revitalize manufacturing in The United States again by helping to build ships and subs. Now the energy sector has been incredible, and and we arya in a lot of other sectors as well.
Speaker: 18
37:55
But what I begun to realize is that the most impactful thing that Gecko Robotics can do to help ensure that we, deter conflict and are most impactful for national security is actually in the energy sector. You see, president Trump is absolutely right. And his executive order today calls out an extremely important, extremely important reality that the companies that can unlock energy are gonna be the ones that can dominate in the AI race.
Speaker: 18
38:22
However, as you can see from the graph here, China is on pace by 2,030 to three x the amount of generation by against The US. But this isn’t the whole story. You see, we constantly think about AI as an energy consumer. However, I’m here to tell you that artificial intelligence can actually be used in unlocking energy production in ways that you’ve never seen before.
Speaker: 18
38:46
No inputs really matter to being able to unlock this potential. And CEO after CEO that I talked to in the energy ai, manufacturing, defense sectors will tell you that we’re trying to figure out how to unlock artificial intelligence to supercharge everything. However, the value is just not there, and it’s no wonder. The consistent common factor between each one of these sectors is Joe.
Speaker: 18
39:10
Joe is out there gathering information by hand, trying to diagnose and get physical data to drive really impactful decisions. But it’s important to understand that Silicon Valley, Silicon Valley artificial intelligence researchers and software engineers, they can’t do much with datasets coming off of the backs of Joe.
Speaker: 18
39:31
And Joe’s been armed with the same technology for the past century, so it’s no wonder that impact isn’t being unlocked in these sectors. And unfortunately for Joe, it’s a very dangerous job as well, and someone dying doing this job was actually one of the things that inspired me to build Gecko.
Speaker: 18
39:47
We have to give Joe better tools in the new century. So what I’m gonna walk you through right now is an example of exactly how we do that for the power sector. We send in robots, robots that are gathering information and data sets about the physical ai, in this case, a natural gas power plant.
Speaker: 18
40:03
We’re understanding what the physical environment looks like, and then we send in other robots ai this dog over here. Now the robot dog is gathering operational data sets to help supercharge Cantilever, our AI powered platform where all the data sets are coming into. You see, we sell an operations platform and data sets gathered in the physical world is what’s enabling that.
Speaker: 18
40:25
We also send in wall climbing robots, and you can see the wall climbing robots to your left and to your right. Now these robots are going into the physical environments and gathering health data all while the app while the, power plant is actually online. Now the health data is really important because we have to understand process health data to be able to optimize and feed into AI models, but again this data set just never existed before, so we had to go out and actually get it physically in the real world.
Speaker: 18
40:55
So robots like this supercharge our ability to be able to drive models to create largest amount of efficiency gains. So this power plant, for example, is supposed to be operating at 620 megawatts, but it’s not reaching its capacity. It’s only operating at 580. So how do you unlock that?
Speaker: 18
41:13
Well, when you have all this information and data sets that we’ve captured with robots plus all the data sets that customers have, you’re actually able to drive optimization to see how to impact efficiency sana production. And so what this AI model is doing is looking at the datasets from the robot dogs as well as the datasets from the health the health data from the robots to pinpoint that there’s actually a steam issue going into the turbine.
Speaker: 18
41:37
Now an ability to fix these things has actually been able to unlock for this site and for many others that we work on at 1% improvement to efficiency, and this is just the first place that we looked. Now it’s also important to understand that the assets that power the grid are failing at a really fast rate.
Speaker: 18
41:55
Now this power plant, had assets like this tank that was decaying at an at incredible rates. It was supposed to be reaching retirement pretty soon, but we were able to determine predictively how to extend the useful life of this asset by ten, twenty, and thirty years from all this data set.
Speaker: 18
42:11
It’s really important to understand when you culminate all the kinds of impacts that you can have from this this kind of technology, you get things like this. Efficiency gains on the dozens of power plants that we’ve been able to work at, if you extrapolate that across the thermal fleet in The US, that’ll give you 11.9 gigawatts of new power without putting a shovel on the ground.
Speaker: 18
42:32
The energy is able to be unlocked using artificial intelligence. It’s really important to understand the statement. AI shouldn’t just consume. It should create energy, and that’s what we’re showing here. Sana not to freak anybody out, but the DOE just came out with a study that shah we have about four years left of useful life on the assets that power our grid.
Speaker: 18
42:53
Now in this trend, it means that a 100 there’s gonna be a 100 times the amount of blackouts by 2030 if we don’t reverse this trend. But what we’re able to shah, not just with power plants, but mining, metal manufacturing, as well as defense assets, you can actually extend the useful life of infrastructure in some cases by thirty years.
Speaker: 18
43:12
And on average, it’s been about 35. This is extremely important in ensuring that we’re able to reverse that trend and ensure that America is well positioned to ensure that we lead on the energy and the in the energy race to enable and unlock artificial intelligence. Now let me summarize this.
Speaker: 18
43:31
We’ve spent so much time, and I think JD Vance has done a great job at at highlighting how much effort and how much data set have been gathered to power AI models in the digital world. It’s what makes chat g p c so addictive. But meh, the physical world has been forgotten about, and our robots are going in to the fog of war to try and decipher and unlock the massive amounts of information and datasets that gives America and our allies unfair advantages unfair advantages to unlock things that we didn’t even realize were there.
Speaker: 18
44:04
And if you build software with an ontology based on first principles, gathering the data and building software up from there, you’re actually able to deliver impactful things for Joe, turning Joe into a PhD scientist or engineer instead of forgetting about him like a lot of Silicon Valley companies have in the past.
Speaker: 18
44:24
Unlocking potential physical intelligence data drives, ai artificial intelligence, and that’s how you’re gonna win the AI race. Thank you.
Speaker: 19
44:44
Ai name is Laura De Berdinis, and I’m a registered nurse here at Tampa General Hospital. The last seventeen years, I’ve been able to to serve the neuro intensive care unit where we care for the most vulnerable and critical care patients. So before utilizing AI, it would take hours to gather information, looking in chart reviews, talking to nurses, talking to physicians.
Speaker: 19
45:10
We relied on paper, pencil, a lot of papers stapled together with sometimes outdated data by the time I was done going through, 32 patients. And this is how we would try and give reports. Bringing in AI, it has significantly changed the culture on the unit. I had a charge nurse who never gave, a multidisciplinary round or a report out. She came on board. She said, this is an amazing tool. Look at this.
Speaker: 19
45:47
It has all my information already gathered and collected, and she was able to report out on the patients. It was completely user friendly. She’s like, Laura, what is this? It is creating excitement throughout the nursing community. Using AI has provided more time to be with you or your loved one at the bedside where nurses should be.
Speaker: 19
46:09
We are the heart of health care.
Speaker: 8
46:13
Matt Trautman. I’m the vice president general manager for PRL Industries, supplier of components for nuclear submarines that our service men and women lives depend on. We are a fully integrated foundry, pouring metal all the way through finished machine components. Two months ago, we weren’t getting after any of the problems on the shop floor.
Speaker: 8
46:31
Engineering director told me all his team was doing was quoting a three day process to quote apart paper files, old archives, data tables, emails, side communications, all this which ends up getting lost in the fray. Now using an AI tool, they are getting halfway through that process in minutes, freeze them up to get back out in the floor and do what an engineer does best, which is solve problems, to provide the navy with the best quality products in the shortest amount of ai.
Speaker: 8
47:00
And this is what AI is gonna help us do. Understanding part location and status, that is a game changer. We can now talk very clearly with the customer if that part is now to become the primary focus of the business because it’s a critically needed part for a ship construction.
Speaker: 8
47:16
You get notified. It’s an automatic notification. We can see the exact status. Here is the impact. How can we be better? How can we do more?
Speaker: 8
47:24
And this is how we’re answering that call. With AI, we match the speed of the quality management process to the speed of the workforce and the machine capabilities, and we will truly see a multistep change in the amount of product that can come out of any company in the supply chain.
Speaker: 8
47:41
More jobs for American workers here at Ram.
Speaker: 20
47:48
My name is Julie Nordberg. I’m a registered nurse leader here at UP Health System Marquette in the heart of Michigan’s Upper Peninsula. And we are really the only game in town, that’s how we like to say it. The next closest hospital to us that could service us is downstate, which is about a four hour drive.
Speaker: 20
48:03
Prior to using AI, it took a lot of time to go through the patient’s charts to see where they needed to be. It took a lot of time just to try to communicate with people. I think that’s a fear that everybody has is that AI is gonna replace people, but AI in the way it’s being used here could never replace our frontline staff.
Speaker: 20
48:19
You know, the the vibe is I think it’s just one of ai that everybody’s just proud to be a part of this. And to say that we’re doing it here and we’re honing it in and tweaking it and and using it to enhance our care and using it to help our staff. Having this ai of communication hub and facility snapshot has helped has helped everybody.
Speaker: 20
48:40
For the nursing staff, I think being able to see everything in one spot has just revolutionized kinda how they are able to provide care. I don’t think anybody is sad to get rid of a meeting. The impact on patients is earlier detection, which means earlier treatment, which is a better outcome.
Speaker: 20
48:59
Lifesaving for some of them. That’s where I think this is gonna help us a lot is because we we don’t have as much manpower as those big academic centers. So having the AI in the background doing some of that ai for us is is huge.
Speaker: 6
49:13
I joined Pekna in 2018. We have built over 11,000,000,000 batteries in the last eight years. I walked out onto their massive production floor for the first time. I knew right then and there Ai wanted to make this technology accessible for anyone who wanted to learn it. People coming from the tourism industry and the hospitality industry, quite a few technicians that have fixed slot machines in a past ai.
Speaker: 6
49:38
People from automotive companies, people who are used to repairing cars, however, have never seen equipment, you know, at this scale and with this complexity. You know, we don’t really, have to pick and choose what people’s backgrounds are because we do have this very powerful learning tool that makes it easy for anyone to be able to enter this industry.
Speaker: 6
49:57
It is taking our historical maintenance records, pairing it with our machine data, and is now starting to ai before it ever actually breaks. This helps minimize our production losses, keep our technicians safer. We’re taking reactive events, turning them into predictive events.
Speaker: 6
50:21
We used to honestly lose a lot of technicians because they would lose their confidence, think, hey, maybe this isn’t for me. I pulled the supervisor off the floor and said, hey, you gotta come listen to this ai, and you have to help us make it better because you’re the one who lives it every day.
Speaker: 6
50:36
Day. And they immediately started suggesting new features. They were telling us what was wrong with the old systems, and we were coming up with solutions on the spot. So this is really helping people feel like they belong here. We don’t believe AI should replace human talent. We believe it should elevate it. Our workers are very excited.
Speaker: 6
50:55
They have a tool that they can turn to to help them learn at their own pace. It really puts the power back into their hands.
Speaker: 9
51:18
Hi. Christian’s joined us from Hill and Valley and one thirty seven. And, Sean, welcome. Thank you.
Speaker: 7
51:27
Great to be here.
Speaker: 9
51:28
Christian, you wanna kick us off?
Speaker: 21
51:30
Yeah. Thanks for having me. It’s ai to be here. I’m definitely, feel for the first time like a guestie of the besties.
Speaker: 11
51:37
Don’t fuck it up. And
Speaker: 21
51:39
and, yeah, this is great. So, Sean, thanks for coming. We were talking a little bit earlier. Maybe this is a great place to start. Obviously, we have a good fortune to be investors in Palantir for fifteen years. We’ve seen the growth of the company. But particularly lately, you’ve been pushing this messaging.
Speaker: 21
51:53
I think it’s incredibly exciting of how AI is not a force for job destruction. It’s a force for job creation. It’s also a way that you can give superpowers to the average American worker. And, obviously, we’ve seen a little bit of content here and how it’s already doing that today.
Speaker: 7
52:06
I wanna start by saying many of the workers in the video are actually here today joining. Laura, the nurse from Tampa General, actually brought her twelve year old daughter. So I think the ultimate litmus test is not just how excited the American worker to leverage AI, but how excited are they for their children to exist in an America that’s really embraced AI.
Speaker: 7
52:23
And Julie has four kids, and she would tell you how how much this has not only transformed her view of her job, but the view of her children’s future. I I think the the right frame here really is how do we give the American worker superpowers. You know, we should not be aspiring to build things that make them 50 more efficient. They’re really 50 times more productive.
Speaker: 7
52:42
And to use that as our our asymmetry in the competition here. You know? Our strengths are not only AI, which is clearly an American phenomenon, but also the ingenuity of the American worker. And if you spend time on the factory floor, on the front line, you see a very different narrative emerging where you see people are actually excited about these tools.
Speaker: 7
53:00
Every single one of those workers to a t sai, AI is giving them more time to do what they do best, to spend time with the patient delivering care, to actually build the parts as an engineer to solve the problems, not to be caught up in all the coordination and the paperwork that’s around these things.
Speaker: 7
53:15
That’s the future we should be unleashing.
Speaker: 9
53:17
Can you generalize the adoption curve? What is it about a particular industry or use case that makes it an early adopter versus mid versus late that you’re seeing? Because now that you’re touching all these different industries, you probably have a good point of view
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53:32
on this.
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53:33
My my take is actually a different dimension of slicing that, which is where did the where does the institution liberate their worker to drive the adoption versus ai where are they trying to force fit some sort of solution top down. You know, AI is a method of unleashing the agency of the worker, the creativity of the individual, and they’re the ones coming up with these use cases.
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53:53
I mean, Chris was talking about it from Hadrian where you you’d be surprised at how people with deep mechanical intuition, traditionally considered blue collar workers, are the ones who are able to pick up the skills, build the applications, innovate on their own processes, and have that spread through the organization.
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54:08
Mhmm. And are you seeing that you have to build vertical tools or ai tools for some horizontal ai of users somewhere in the organization?
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54:17
Ai think that the opportunity with AI is really that you can unleash what’s different about your business than all the others. There’s a degree to which you can have generalized solutions, but there’s a lot of alpha to be captured by understanding what’s unique about how we do things.
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54:32
How do we lever up human taste? Everyone is afraid of AI replacing the human. That’s not what I’m seeing. I’m seeing it it make the the most the the person with the greatest taste more valuable and an ability to spread that to the breadth of the organization.
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54:45
Let’s talk about, something beyond taste, which is also in, like, knowledge and skill. And tell us about AI inside of health care. I think that a lot of people probably think that we have an incredibly cutting edge system of tools and software that helps doctors and nurses actually provision great care.
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55:06
What’s the actual reality that you guys are seeing?
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55:09
Well, sadly, I think with the forced adoption of EHRs, what we saw is roughly a halving in the productivity of how many patients you can see per hour. A halving? A halving. Yeah. So we became half as productive. And we really need to, you know, the opportunity is to work backwards from what is the care that needs to be delivered?
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55:26
How do we build the tools around that? How do we help the the the nurses, the care staff speak more time with the patients and less time with the computer?
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55:34
And do you guys see a world where in order to facilitate that end market versus a different end market, you have a ensemble of meh, many, many different techniques and approaches in Ai? Or do you think it all sort of gets form fit into this 1,000,000,000,000 parameter, huge, ginormous thing that kind of tries to do everything?
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55:53
I think the cardinality of agents and models is very high. I think there will always be alpha to be achieved, you know, improved differentiation, improved outcomes by specializing to the use case. Now it’s great to start with the general models, but you will specialize over time.
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56:07
And do you feel pressure to do that now, or do you think that’ll just be a natural evolution over time as
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56:12
Yeah.
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56:12
I think it’s a journey that people kind of get on. Like, you ai, like, wow. Look how much better things have gotten with this. Now how do I go get the next incremental piece of performance out of it?
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56:21
You know, I’m I’m just having this thought as we sit here and discuss this. If you think about any experience we have in service that has a long wait time where we feel like we got more time with the practitioner, it’s the perfect place for AI to create more abundance. And health care and education are the two that that come to mind, where people could just offload their chores, and the people who are getting the service can use AI to maybe start the conversation on second base or third base.
Speaker: 11
56:49
What other industries are you seeing after health care, education, where AI can have that dramatic of an effect where the six week wait time to see a doctor, the three or four other students who are getting tutored are ahead of you, and maybe you don’t need as much help. So you don’t you never get the tutoring.
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57:07
The the place I’m most excited about it is really in reindustrialization. So it because there’s so much dwell time in the value chains around Wait. Wait.
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57:16
What does that mean? Dwell time in industrialization?
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57:18
Where where you’re just waiting for someone else
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57:19
to figure out how to
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57:20
prove something, where the coordination costs mean that it’s essentially deadweight loss. Give
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57:24
an example there. Yeah.
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57:26
You saw it with the the submarine, industrial based partners there where they’re working on quoting a part to the navy. That means you have to go gather all of this data. You have to look at historical archives. All of that is time you’re not making a part or solving problems. That’s just it’s just sitting there. The factory floor is idle. Right?
Speaker: 7
57:44
Sai how do we get rid of that dwell time so that you can be utilizing the the CapEx that you actually have to the maximum extent possible? Yeah. And then if you start if you zoom out, that’s ai one part manufacturer. You’re you exist in a massively complicated supply chain, and you just end up with all these busy weights along the way here.
Speaker: 11
58:00
Yeah. That’s so profound. A friend of mine said, who’s in that industry, you’re only as efficient as your worst supplier. Exactly. Yeah. And the second part
Speaker: 7
58:08
of that, which, the Panasonic energy example really touched on is how do we train our workers? You know? So here you have exquisite Japanese technology that used to take three years to train a worker on it. Now with an AI assistant, the workers who are prior casino workers, you know, they’re not they’re not from this industry are able to get up the curb in three months.
Speaker: 7
58:25
So you think about how we can use that to more quickly absorb the slack that’s happening as we as we adopt AI and and democratize opportunities. So much so I have so much conviction as we’ve launched the American Tech Fellows ram at Palantir to find blue collar workers at our customers in in the heartland, overlook folks who have a natural proclivity that
Speaker: 1
58:44
they have. Ai them? How do you find them? Well, some of them are saying ai, like how
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58:48
Yeah. Some of them are
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58:49
at our current customers. The idea really came from us organically where it’s like, wow. Who is building the most compelling applications? It’s the guy on the factory floor, not a formally credentialed computer scientist, mostly an autodidact, but there’s meh, not only grit, but ambition.
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59:03
Ai have the drive to reshape their own organization, to reshape the processes. Let’s bet on that person.
Speaker: 9
59:09
And going earlier, does that meh, and I’ll ask the same question many times today, that college education, the traditional four year liberal arts degree doesn’t matter as much that kids can go from high school or earlier in their careers into a new workforce and get well trained and well suited to to make money and and succeed in life?
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59:29
Sai I think
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59:29
I think the traditional college degree is is dead, and, we should be betting on the American worker.
Speaker: 21
59:34
Well, on that point, can you talk about the tech fellowship? I got to recently see a bunch of demos from the first cohort with you, and it’s really incredible what you guys are doing there. Maybe give a little bit there and then maybe also talk about the opportunity for other companies to follow this trade school framework as we, end here.
Speaker: 7
59:48
Yeah. I mean, it’s really kind of an elite trade school. So, like, finding people with make mechanical intuition who have done things. Some of them are right out of college. Some of them are twenty years of experience, but they’re reentry. First trade school that
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59:58
you guys have done. Right?
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59:59
Yeah. That’s right.
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01:00:00
Mhmm.
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01:00:00
And we have just enormous demand from our customers. We’re like, who are people who have these skills? You know? And it’s it’s not classically trained ai educated people. They don’t have these skills, actually. So the market’s not meeting, and they don’t know how to source these folks. So I can credential them.
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01:00:15
I can put them through the boot camp in four weeks and place them with my customers to go unleash AI within their organizations. It’s incredible.
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01:00:22
It’s incredible. Sana, thank you.
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01:00:24
Sean, thank you. Thank you sai much.
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01:00:26
Well done. Thanks man.
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01:00:28
Thank you.
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01:00:28
That’s great.
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01:00:29
Thanks for
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01:00:29
your help. Thank you so much. Cheers. All right. Next up we have Paul from Ai Combinator. Please welcome. Oh, Paul. Blue Ai.
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01:00:43
Paul. Paul. Hi. Paul.
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01:00:44
Hi. Here he is.
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01:00:45
Hello. Paul, you created Gmail talking about, efficiency and making a ram more efficient.
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01:00:51
Hey. Good.
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01:00:51
You’re also ai. I believe
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01:00:53
We work together.
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01:00:54
You came
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01:00:54
up with the slogan
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01:00:56
We work together too. The slogan don’t be evil.
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01:00:59
Yes. Yeah. Yeah. How’d that turn out?
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01:01:02
I I don’t know where’s the it’s an attempt at alignment. Right? Like, we we worry about AI alignment. What do you what do you tell the super AI once you’ve built it?
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01:01:10
Yeah. You’re at Ai Combinator now. Although you recently said you’re stepping down. Right? Or you’re
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01:01:17
partner Meh. Partner Emeritus. We’re we’re starting a new firm, Standard Capital.
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01:01:21
So
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01:01:21
Got it. Oh, that’s exciting. Wow.
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01:01:24
Let’s talk about the game on the field with startups. You get to see startups in year zero and year one. And one of the primary thesis is Ai think we all have is ai coding and making coding not a roadblock. I think Paul Graham’s great innovation at ai Combinator was saying, I’m just gonna accept two or three people who actually build the product.
Speaker: 11
01:01:46
In fact, in the ai c application, it says, who wrote the code for this? Who’s writing the code? Just so you can make sure that you’re actually hiring coders. What are you seeing on the field in terms of ai coding? Because people are now
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01:01:58
Great question.
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01:01:59
The you know, English is the new programming language. It’s only two or 3% of the country knows how to code. Probably half that code well enough to do a startup. So here we are. Could we be on the precipice of 10 times as many startups, a 100 times as many startups?
Speaker: 22
01:02:16
Absolutely. I mean, that’s that’s the dream. That was actually you know, YC was started twenty years ago, based on PG’s insight that, actually, it’s getting easier to start a startup. Right? It used to be you had to have a big mountain of money. You, you know, hire a big team, etcetera.
Speaker: 22
01:02:32
And his realization was you can start a startup with just a couple of people and, you know, basically, ramen. Few few kids live living off of of ram, and that’s proven to be true. And our belief is with AI, that actually just goes that much further. Right? Because the universe of people who are able to create, apps using something like Replit, is enormous.
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01:02:56
And so, my I think maybe most optimistic vision of what we’re doing with all the AI is essentially putting all of these tools of wealth creation in as many hands as possible.
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01:03:07
Do you think that English is I think it’s Andre Karpathy that said this. Right? Like, do you think English is the ultimate destination language that everybody will use to code? Or do you think it gets abstracted even further beyond that where you sort of think things and they just kind of appear?
Speaker: 22
01:03:22
I think it might be a little while until we can just think them. But, clearly, that’s the direction. Right? Is that you have a a dialogue with the Ai. And so you describe, okay, not quite like that, more like this. And the direction is essentially just that it becomes easier and easier for us to realize our visions and for everyone to realize our visions, not just people who
Speaker: 1
01:03:43
Well, let me ask you this question. Do you I mean, that clearly grows the funnel. Mhmm. Right? So now we have a 100,000,000, 500,000,000, a billion people, 2,000,000,000 people. Whoever can speak English can now code. How does it how do you think about that as one of the best computer scientists that Meh ever created?
Speaker: 22
01:04:02
Mhmm. How do I think about all those people having the ability? Yeah. I Ai mean, I think it’s great. Right? Any anything, you know, our philosophy is that I don’t wanna see all of the power concentrated in a small number of large organizations. I think that’s bad for everyone.
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01:04:18
It’s bad for freedom. And so what we want is to give that power to as many people as possible sai everyone can create, you know, apps. And it might just be something for their own local community. It it’s not not every one of those apps is gonna be the next Google, obviously.
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01:04:33
But the more people can create wealth in their own community and in their own lives, we spread the prosperity everywhere.
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01:04:41
Are you seeing it in the applications you get to YC or that you’ve heard of more physical AI, robotics, automation, those sorts of tooling? Because as this becomes easier, it actually leads to the leap, Hey, maybe I could do this as a robot and I ai get a robot to do a particular thing and that creates an opportunity for a new business.
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01:05:01
Has that become a big kind of growth curve right now as Yeah. Physical AI and
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01:05:06
Absolutely. That number of robot arms at the most recent demo day was was striking. I think everyone is starting to work on that. And, again, as as the things that used to be difficult Yeah. Get easier, we just start doing more difficult things.
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01:05:18
Right.
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01:05:18
But Right. Absolutely. I think and I think robotics
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01:05:20
technology curves.
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01:05:22
Yeah. Exactly. And and I think that’s gonna open up, you know, whole new realms that were previously impossible or impractical.
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01:05:28
So So does that create new industries is, like, I think a key
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01:05:31
Absolutely.
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01:05:32
Point which is, like, what I think is most under misunderstood about AI is it’s not about the displacement of doing old things, but it’s about activating new things that are complex and historically not tractable, but now they’re tractable.
Speaker: 22
01:05:44
Right. Exactly. So, I mean, if you think about just the fundamentals of wealth creation, the inputs are essentially energy and intelligence. And we’re about to unleash essentially an abundance of intelligence where, like, the total global intelligence is going to 10 x. Right?
Speaker: 22
01:05:58
And so that will enable us to 10 x our total wealth. And that’s gonna come in a lot of different forms. Like, you know, as we start to have AI science labs, for example, where the AI can actually start running its own experiments, producing its own data, I think our understanding of biology is sana be incredible.
Speaker: 22
01:06:18
You know, in twenty years we’ll be able to know how a drug affects the body without ever actually testing it. And my prediction is actually our our AI models will be more predictive than today’s clinical trials.
Speaker: 11
01:06:32
You know, it’s interesting hearing you talk about this, Paul, is and it’s really the power of great conversations. There was a troll over the last couple of years when somebody lost their job in journalism, ai, learn to code. Learn to code. And now you think about it, there’s multiple types of intelligence.
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01:06:47
Start arya were limited or, you know, gate kept in some ways by mathematical intelligent intelligence, the ability to to write code. Opening up that to people who are high intelligence or high design, high emotional intelligence could lead to many more beautiful, interesting products that maybe people who are math intelligence, you know, focused just would never get to.
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01:07:12
Absolutely.
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01:07:13
And this is an abundance that I think people are maybe not even realizing meh, is that a whole group of journalists, writers who are being displaced or, you know, Uber drivers or people working in factories. Well, if they can embrace this technology and we saw it with, no code. Remember the no code kinda ghetto that was, you know, emerged for a couple years?
Speaker: 11
01:07:35
Oh, startups are gonna be no code. It was kinda like the false start, but you did see a bunch of new entrants applying for y Combinator or Right. Things. This this could really be, accretive to humanity.
Speaker: 22
01:07:48
Yeah. Absolutely. And it reaches people who are perhaps otherwise left behind. Right? Like, it it shouldn’t be just people in Silicon Valley who can create apps. Like, there’s a whole country full of people who have ideas. And the same thing goes, you know, not just for apps but for media.
Speaker: 22
01:08:03
Like, I think a lot about, you know again when we look at where the generative video models are going it’s pretty amazing ai?
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01:08:11
Pretty incredible.
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01:08:11
In a couple of years that means a kid in wherever Middle Meh, ai over country who has like a vision for their own Disney movie can can actually just create the Disney movie. Right. You don’t need the $100,000,000 budget. And so that’s going to give, you know, a lot of voices that are currently not represented in media because they don’t have access to the capital or the or what to Hollywood capital.
Speaker: 11
01:08:34
The elite version of this would be, oh ai god. We’re losing this job creating at Netflix, but you’re creating a million other jobs for people to create their own superhero that represents them, that represents their country, represents their sensibility. Exactly.
Speaker: 1
01:08:49
Let me ask you a question as a technologist for a second. When you see the landscape of these foundational models and how good they’re getting, is your belief that the number of those will grow or do you think that they’ll consolidate and they’ll just be fewer but better? How do you see all of this investment that’s happening now Yeah.
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01:09:08
Play out? And feel free to name companies while you’re doing your analysis.
Speaker: 22
01:09:11
Go ahead. Which ones which ones will go away? Yeah. No. I mean, I expect that it’ll probably stay relatively stable, honestly. Because I the the cost of building these foundation models is astronomical. Right? We just saw XAI is raising another 13,000,000,000 something like that.
Speaker: 22
01:09:27
And and so it just the capital requirements are gonna limit how many there are. But I certainly hope that it doesn’t consolidate down to just like one or two because again Ai think part of what’s important for preserving freedom is just that we have many options. And so actually a lot of people don’t know we started open Ai at y combinator, ten years ago in 2015. We saw that AI was on the rise.
Speaker: 22
01:09:53
We saw that this was happening, but at the time we were concerned that it was essentially all locked up inside of Google and so that would be bad arguably for the world but certainly for our companies. Right? We we have thousands of companies. If our companies don’t have access to that next wave of technology ai we’re sana be out of business.
Speaker: 22
01:10:12
And so Ai was kind of like a moonshot project that we were actually going to take this out where it’s not just locked up inside of
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01:10:20
the world. Feel when they made it closed Ai and and You know, I I
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01:10:23
there was never specifically promised to be open source, but I I Sure
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01:10:27
it was. It was explicitly
Speaker: 22
01:10:29
If you if you go back, it’s it’s a little bit. It seems it seems like the balance is that is that there’s reasons to have both. But the importance of having open source as an option forces all of the closed source vendors to be, honest. Right? Like, if they start if they start censoring the models, they start, you know, disabling too many abilities, then people will all switch the open source.
Speaker: 1
01:11:03
And while you worked at Google, you worked at Facebook
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01:11:06
Oh, this was my question.
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01:11:08
Google has done an incredible job with their, you know, ensemble of Gemini apps I meh, Gemini models. Facebook has had some missteps with Llama. I’m just curious if you were the CEO of Facebook today, are they making the right meh?
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01:11:24
Or Google.
Speaker: 1
01:11:26
Well, I’m actually more curious about Facebook. Are they making the right bet with respect to just the talent war that’s been created or is there a different technological approach? You know, for example, the one thing that we talked about before was this concept of the bitter lesson, which is always that compute overpowers humans. I don’t know.
Speaker: 1
01:11:42
How do you think about that? Or what would you do if you were running that business today?
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01:11:45
I mean, I think he’s he’s doing what what needs to be done. Right? Like, Facebook has clearly fallen ai, and that’s a real threat. Right? Because Facebook actually competes with AI. Like, people are switching from Instagram to chat g p t. Like, my kids are not on social media. They’re talking to the AI.
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01:12:02
And so if they
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01:12:04
Fundamentally cannibalistic is what you’re saying.
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01:12:06
Yes. Yes. So I That’s
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01:12:08
an interesting concept. Like, there’s a finite amount of time Mhmm. And which is forget about the categories we put on them.
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01:12:15
I mean, the compound question ask a great agent is incredible. Mhmm. You know, the way that you can speak Yes.
Speaker: 11
01:12:20
And that they’re actually now with Grok having the avatar ai of leaning into this concept of personality. We, as old people and Meh Xers, might be totally missing the script. Right? Sure. Well, actually, so, Character Ai is an example that, actually, Noam made that bryden. And and, Noam is a friend from Google who actually basically invented transformers
Speaker: 22
01:12:42
Right. And then got frustrated that he couldn’t launch anything at Google, so started Character AI. But that was the ai thing is making, characters that people want to talk to. And so the usage on on characters is amazing. Yeah.
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01:12:55
Walt, thank you for being here.
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01:12:56
We’re over.
Speaker: 9
01:12:57
Yeah. We’re a little bit over.
Speaker: 11
01:12:58
Well, to be continued, we have to have you on the ai.
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01:12:59
Good luck in the discussion. That’s amazing. Yeah.
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01:13:02
Yeah. Congratulations on the new one.
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01:13:03
Thank you.
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01:13:04
Yeah. Thank you, Paul. Appreciate it.
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01:13:08
Oh, Keith. Hello.
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01:13:09
Oh, Keith is back. Oh. Oh. I got dragged
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01:13:13
in. Guys, Keith Raboy. How are you?
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01:13:15
It’s great to be here live. Yeah. Everything we’ve done has been remote. Over Zoom. Yeah.
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01:13:19
This is
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01:13:19
what you look like.
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01:13:20
Exactly.
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01:13:21
You look great.
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01:13:22
Better work. This is what
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01:13:23
Even go to various
Speaker: 9
01:13:23
Yeah. Clearly.
Speaker: 1
01:13:25
It’s what 8% body fat looks like.
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01:13:27
Yeah. Nine.
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01:13:28
Sai ai it. Who’s counting?
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01:13:32
Apparently, the both of you.
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01:13:45
How are you, David? Good to see you. Keith. Great to be with you.
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01:13:48
Yeah. Hey, Kelly.
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01:13:49
Ai to see you.
Speaker: 23
01:13:49
Oh, my gosh. J. Cal, how are you?
Speaker: 9
01:13:51
Good.
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01:13:51
Good to see you.
Speaker: 1
01:13:52
See you.
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01:13:53
Kelly, thanks for being here today. Not sure you’ve been following the panels, but a lot of conversations going on are around AI, particularly around job displacement. Yeah. You’re the twenty eighth administrator of the SBA. Ai think more than half of the American workforce is employed by or are small business owners.
Speaker: 9
01:14:13
You and I had a conversation a week or so ago about what you’re seeing on the ground with small businesses. In an AI workplace setting, the conversation is always are they sana get out competed, are they gonna get displaced, what’s gonna happen to American jobs and to the small business, but what are you seeing on the ground and how does the SBA ai of associate with the transition underway?
Speaker: 23
01:14:34
Yeah. Dave, first of all, great to be here. Look, small business is big business in Meh, but small business is big business for Ai, and I have been walking hundreds of factory floors for the last six months, most manufacturers in America are small businesses. And without AI, we would not be winning back these industries. And I will just tell you a case in point.
Speaker: 23
01:14:59
I actually bought a slide to show you workforce development in action, modern workforce. We call it the new collar boom. I don’t know if they can put it up, but it’s a factory in Seymour, Indiana. It’s a bike factory. We had lost the bike industry over the last thirty years, thousands of jobs, 98% imports.
Speaker: 23
01:15:20
We’re now, for the first time in this country, building bikes in America because of AI, advanced manufacturing techniques. Imagine we replicate this industry after industry, and these are small business. This is 60 person factory in Seymour, Indiana where they have no jobs. Yeah.
Speaker: 23
01:15:37
So it’s a AI is a job creation machine for reshoring, onshoring, and advanced manufacturing.
Speaker: 9
01:15:43
But manufacturing, you’re seeing a big heavy, influence potential for kind of ai. What about in the services businesses? What do you see there?
Speaker: 23
01:15:52
Across the board. We have seven and a half million jobs open in America. Most of them are open at small businesses. Number one concern of small business is a skilled workforce. That’s because President Trump solved inflation, regulation, taxes. Now they’re saying, okay, we’re booming.
Speaker: 23
01:16:09
We’ve got $15,000,000,000,000 of investment coming in. A lot of that’s gonna trickle down to small business. We need the skilled workforce. So president Trump is ensuring that we have that skilled workforce, through some of his workforce initiatives, but small business is gonna be driving the AI boom from the bottom up.
Speaker: 23
01:16:27
And,
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01:16:29
I guess, what is needed for workforce training and transition?
Speaker: 23
01:16:33
Yeah. Technology is gonna be a big part of it. So when you think about go back to 1940. Our workforce size was 56,000,000, And people say, well, as technology advances, our workforce gets competed away. Today, our workforce is a 170,000,000, and compute power has been asymptotic.
Speaker: 23
01:16:51
So essentially, 85% of the jobs that exist today have been driven by advances in technology, and only 40% of the jobs that we had back in 1940 still exist today. So we are relying on innovation as a job creation engine. It’s just that people have a fear of the unknown, and they’re saying, I can’t envision what it is.
Speaker: 23
01:17:13
Well, I can’t envision what my life would have been like when I started a small business if I could have had Figma or Canva instead of PowerPoint. Oh ai gosh. So just these are, we’re sana create millions of solopreneurs who are gonna have massive software companies or manufacturing companies thanks to
Speaker: 11
01:17:33
AI. Is there something the government can do, the SBA, for? And what is the role of the SBA? I mean, I know one of the big focuses of this administration was to make government smaller. Mhmm. So is that a goal you have to make government smaller and then maybe give the ability to give loans to the state?
Speaker: 11
01:17:48
What what is the role of the government in getting one and two person companies up and running, if anything?
Speaker: 23
01:17:54
Well, the the mission of the SBA is to grow the economy and to support small businesses, and that’s that’s what we’re doing. And the the last four years, it had not been doing that. In fact, with regard to AI, the Biden administration banned the use of SBA based loans for use of purchasing technology in AI.
Speaker: 23
01:18:14
I had the rules rewritten, so now small business entrepreneurs, solopreneurs up to 500, 1,500 person factories can use the proceeds of their loan toward AI implementation advanced manufacturing. Arya role is
Speaker: 14
01:18:27
to get
Speaker: 23
01:18:27
out of
Speaker: 22
01:18:27
the way.
Speaker: 11
01:18:28
Yeah. But but educate us on the loans because we hear about that, but we’re in venture capital where we have an incredible ecosystem of angel investors doing this. How do SBA loans work? Who are they for? How much do do the American taxpayers, you know, put into this? And and what’s the result?
Speaker: 23
01:18:43
Yeah. I’m glad you asked. So the SBA does not do direct lending. We span out across network of thousands of banks in this country that offer SBA, which are government backed loans, but we also operate the small business innovation, company guarantee that has been responsible for backing many massive startups.
Speaker: 23
01:19:03
SBIC money was in Tesla for example. So we have an equity piece as well as, the the SBA saloni, but those loans have to be repaid over thirty years. But they simply give small businesses that banks wouldn’t normally lend to that government guarantee that gives them the confidence.
Speaker: 23
01:19:23
We do about 2,000 Main Street loans every single week so far this year. Wow. We are on pace for a record year because we’ve made the SBA ai sai, which means we’ve taken it back to the pre pandemic size. It had doubled during the pandemic. 90% of the employees were working from home, not focused on small business. We took it back down and the spending had doubled.
Speaker: 23
01:19:48
So we took the spending down. We took the headcount back to pre pandemic, and now we have record level.
Speaker: 11
01:19:54
Have people showed up in the office?
Speaker: 23
01:19:55
Oh, yeah. We’re back every day.
Speaker: 11
01:19:57
Wow. Sai the American taxpayers are paying people for a job, and they’re doing it in an office.
Speaker: 23
01:20:02
Not only that. Outside of Washington we sent them out to the field.
Speaker: 1
01:20:05
Do you think that at some point you will look at either adding new types of SBA back loans or changing some of the conditions to do as you said even further incentivize the investment in AI?
Speaker: 23
01:20:17
Yes. Absolutely. We are looking right now at critical industries ai meh metals, mineral minerals, medical ai, reshoring and onshoring. We have a massive at the SBA. We’re leading the make, onshoring great again portal, which is on the SBA website. It’s a resource of 1,000,000 onshore manufacturers.
Speaker: 23
01:20:36
We’re leading the made in America charge, so focusing on smart manufacturing and looking at loan ai. And we’re trying to double the size of SBA loans so that for buying advanced technology equipment, CNC machines, training that there are many more resources available for them.
Speaker: 1
01:20:55
And how do you think about energy on top of that?
Speaker: 23
01:20:59
Ai. I was just talking to Secretary Burgum and Wright last night at the White House and we were talking about the convergence of small business with the physical and the digital, and energy is going to be a big part for small business there because the innovation is going to be coming from smaller businesses.
Speaker: 23
01:21:16
And in manufacturing, you can be a small business and have 1,500 employees. But frankly, I’m seeing a lot of energy companies and others with 300 people. So small business is sana to drive it. If you stipulate stipulate that there are 34,000,000 small businesses in America and 20,000 large companies, This is a small business driven energy and AI boom.
Speaker: 1
01:21:41
But your your vision is something that some of the leading entrepreneurs in Silicon Valley have been pushing for as well. This idea that there is an entire boom that will happen of solopreneurs, the two and three person companies that are vibrant, successful, profitable, growing.
Speaker: 1
01:21:56
And what they just need is a little bit of help at the edges potentially on maybe paying for some compute resources or whatever, and then they’re off to the races.
Speaker: 23
01:22:05
And that’s certainly backed up by the data we have at the SBA. So 60% of the 40 of the 21,000,000,000 that we’ve lent this year have gone to companies with one to five employees. So that’s where the growth is coming. Certainly we know that they’re going to scale from there, but we’re seeing all the trends say that putting more technology into the hand of small businesses is growing the economy and and small business is still growing the jobs boom in America.
Speaker: 23
01:22:34
720,000 jobs created this year led by small businesses.
Speaker: 11
01:22:39
Keith, I’m curious. You’re a free arya guy. What what are your thoughts on the government’s role in maybe a juicing up via this onshoring specifically in categories where maybe China has dominated for a couple of decades?
Speaker: 12
01:22:53
Well, as Kelly pointed out, the government’s actually not extending the loans. The community banks in America are sending the saloni. So it really isn’t a deviation for free market principles. If you think about it, AI is really this rocket fuel to turbocharge small businesses and entrepreneurs, at least in three dimensions. First f, access to information.
Speaker: 12
01:23:10
Typically, if you’re starting a business, you have to compete with very large incumbents that have expertise in market research, marketing, legal, accounting. Now top of, you know, top of your fingers or your voice, you have the same expertise that all these large companies have. So you’ve leveled the playing field.
Speaker: 12
01:23:24
Secondly, you have access to products ai building it out. Like, everybody can compete with a large company. Anybody can code an app. So you’re, like, Erica HVAC repair person. You have an app that’s on par with a Shopify store or better. Like, that allows you to compete. So we’re gonna see more from there.
Speaker: 12
01:23:40
And then third, you can save money. Like, you used to have to have a g and a team. Like, you have accountants and, you know, bookkeepers and HR. AI can do all that, maybe even do it better within humans, but certainly at zero cost. So the economics of running a small business are gonna be much better.
Speaker: 12
01:23:55
A the risk of running a small business, starting a small business is gonna go down, which we’re gonna have an increase. And then ai, you can save money through things like ram. You can use AI to audit your expenses and not waste five to 15%, which will make you more successful.
Speaker: 12
01:24:07
So all these trends are gonna combine, and we’re gonna see in this administration an explosion of successful small businesses.
Speaker: 9
01:24:13
Does that mean that there’s just more competitive forces in the marketplace? So big companies are gonna now have more competitors, and it just ultimately drives net productivity gains on Meh
Speaker: 12
01:24:24
well, hopefully, net productivity gains. And insofar as there’s some substitution, I suspect you wind up with a barbell. So the large largest players, the NVIDIA’s of the world, do benefit the more people that run compute, etcetera. But then I think that the smaller businesses actually eat at mid market companies because they can compete now, and they’ve been at an economic disadvantage for decades.
Speaker: 23
01:24:43
And we’re gonna be in industries that we couldn’t have even imagined that we would be in. When people sai, why, you know, why do we need to make bikes in Meh? Because it creates 60 great paying jobs in a tiny town in Indiana. That wanna do it. That’s right. That’s right. P p e PP and E, like, whatever the, you know, during COVID, pharmaceuticals, we should be making that here.
Speaker: 9
01:25:05
We can
Speaker: 23
01:25:06
do that with Smartmaking and Factoring with a 100 people in the factory.
Speaker: 11
01:25:09
You must, give the criteria or some guidelines to the banks of how to speak. And, I’m assuming you take diversity and inclusion and gender and all these important factors into account, or do you do it based on merit? The question is this I was just trying to trigger the two of you.
Speaker: 12
01:25:27
They they sai that to your phone.
Speaker: 11
01:25:30
Yes. I don’t do any DI, but jokingly, but what’s the ai? Like, when somebody comes and sai, I want to, you know, raise a 100,000 ai go to their local bank. How do they get picked?
Speaker: 23
01:25:39
Yeah. We have strict underwriting guidelines, and we’ve stripped out the DEI that the last administration shah put in. They had a green lender initiative to preference where money went under the green new deal. I mean, we’ve gone back to saying, if you qualify for these loans, have at it. We’re not sana pick winners and losers.
Speaker: 23
01:25:57
We want everyone to compete on a level playing playing field and have access to that capital. But what had happened in the last administration, they had lowered the underwriting guardrails. As a result, the loan loss portfolio the on the portfolio went way up $400,000,000 We’ve reversed that, strengthened the underwriting standards to make sure that the money goes to small businesses who are building these factories to onshore drones and pharmaceuticals and defense and aerospace.
Speaker: 9
01:26:22
Shah are the target performance ratios in the loan portfolios?
Speaker: 23
01:26:26
Oh my gosh. I mean our loss ratio should be 3% or less, and they arya. Including on the SBA is one of the largest disaster lenders in the country. We’re the recovery lender.
Speaker: 9
01:26:37
And they do well
Speaker: 1
01:26:38
for me.
Speaker: 23
01:26:38
It’s very low, very low. And in fact, there’s a secondary market for SBA loans because they perform well because of the strict underwriting standards.
Speaker: 1
01:26:46
Part of,
Speaker: 23
01:26:47
Oh, zero subsidies. Sorry, Tramont. No. It’s okay. It it operates at no cost to taxpayers when we enforce prudent underwriting standards.
Speaker: 4
01:26:55
Right.
Speaker: 23
01:26:55
We’re getting back to that. Yes.
Speaker: 1
01:26:56
One of the things that, helps burnish entrepreneurship is imitation is the sincerest form of flattery. You must have so many successes, but they’re not always well marketed or known, which would then pull other people to say, well, if they could do it, I could do it. How do you think about that? Yeah.
Speaker: 1
01:27:15
We’re In a world of social media and all of this
Speaker: 23
01:27:18
you’ve picked up on one of my key problems. I run an agency that starts with the word small. Small does not mean insignificant. In fact, small business is significant. And President Trump and I talk about that all the time. He loves small business. He knows the innovation starts there. The manufacturing is small business.
Speaker: 23
01:27:37
So we are working on a massive resetting of what the SBA does, but more importantly, what small business means to America. And I think people are waking up that Main Street is going mainstream, and we have to continue to push the understanding that if
Speaker: 1
01:27:53
we don’t protect our small businesses, our innovation pipeline, our job creation engine is sana shut down. How do you interface with state agencies and state senators and state governors who have 50 different views of the world, but, you know, you’re responsible for at least supporting the underpinning of the business people that are there.
Speaker: 1
01:28:14
How does that tension play out?
Speaker: 23
01:28:16
It it’s really important, Chamath. In fact, we’ve started an initiative where I’m meeting with governors across the country and their economic development, departments essentially because they know best what they need in their state. And if we can push more of this out of Washington and say this needs to return to the states, They need to know the SBA is a resource for recruiting companies into their state to create jobs in manufacturing, like in my home state in Georgia that has done that.
Speaker: 23
01:28:42
So we’re sana to continue to partner at the state and local and across the administration. I meh, having David Sachs in this administration to be an ambassador for AI and crypto has been huge because it gives us a way to work across the administration and then we can focus with the governors at the state level.
Speaker: 9
01:28:59
Can I ask one question on that because your comment was really striking that you guys have strong underwriting performance in the loan portfolio? There are many other insurance programs across the federal government that do not have good underwriting standards and run a terrible loss ratios, and they’re highly inefficient for the taxpayer.
Speaker: 9
01:29:15
And then they cause all of these market inefficiencies as a result. And I won’t start to name them, but you know who they are. Given your background financial services and fintech, your experience here, is there an opportunity do you get drawn in and is there an opportunity to go in and try and address some of these other very, very, very large insurance programs and underwriting programs that the federal government operates?
Speaker: 23
01:29:35
Dave, I think there is because we’ve recruited to the SBA really an elite group of financial services leaders who understand this. I I served in the sana previously in the US senate. I was the only CFA to have ever served in Congress. And I found out when I went to Washington
Speaker: 1
01:29:51
that congress ever?
Speaker: 23
01:29:52
Ever. They don’t like people with financial services experience in Washington because we know how to read a p and l. Yeah. And, but yeah. So we’re bringing that discipline. We’re happy to share it. Very open source.
Speaker: 9
01:30:03
Please do.
Speaker: 23
01:30:04
Yeah. So ai like you say, we’ve open sourced it, and the fans have just gone crazy. So
Speaker: 11
01:30:09
Kelly, we have a, we have a word for small businesses in our community. It’s called startups. Maybe it’s time to rebrand the SBA.
Speaker: 23
01:30:16
I’m completely open to it. That’s right. I was sana call it Main Street manufacturing, but I like I like start ups a lot too.
Speaker: 9
01:30:24
I love that because, by the way, the point the point about China we made earlier, they have there’s 3,000,000 factories in China, but these aren’t massive hundred, four hundred acre facilities. These are very often small warehouses that were turned into a small manufacturing facility, and we could recreate that in America across all of these great states where people are looking for economic expansion.
Speaker: 23
01:30:46
Over and over. Yep.
Speaker: 12
01:30:47
Yeah. David, actually, many of those opportunities exist, but, people don’t know that they can find local sourcing. Sai what’s now possible through AI, you can say I have this product and historically I’ve got it through China or I’ve got it through Indonesia or whatever. Yeah.
Speaker: 12
01:30:59
I want a US based manufacturer. Yeah. And you can use AI to go across the entire country and find local manufacturers. There’s there’s almost always a choice in The United States. It’s just people don’t know where to find them and how to negotiate with them and how to get in touch with them even.
Speaker: 12
01:31:13
And so that’s a solved problem now through AI. Yeah. Yeah.
Speaker: 1
01:31:16
Do you think that there’s, a place where the SBA, maybe in partnership with the White House, sai, here are these industries that, frankly, are just a little bit more important. Where are kinds of companies that maybe are just a little bit more important for a bunch of strategic reasons, where maybe in you relax the underwriting criteria or you just try to get a lot more people on the field, chips on the table?
Speaker: 1
01:31:43
How do you how do you think about that?
Speaker: 23
01:31:45
Well, first of all, I’m a taxpayer champion because as a small business person, I know that small businesses are taxpayers too. And we can’t put some small businesses on the hook for other small businesses. So we’ve got to have an efficient market that discovers the right funding mechanism.
Speaker: 23
01:32:00
So we’re looking at making sure that we’re we have the right underwriting standards for critical industries, as we’re working on some things with department of defense right now. We have our SBIC program that we’re experimenting with some different equity structures. So there’s more to come on that.
Speaker: 23
01:32:18
I think financial engineering is important, but we have to, first and foremost, not put taxpayers on the hook for it.
Speaker: 11
01:32:25
Yeah. I think that’s a really interesting point, the equity structures. If you look at Solyndra, Tesla, and that cohort, Tesla paid back their loan with interest early.
Speaker: 23
01:32:36
That’s right.
Speaker: 11
01:32:37
If the government had gotten just 10% of that in equity, that would have paid for a 100 Solyndra and mistakes. So some equity component or warrants could could change the SBA into, you know, having and the American taxpayer ai proxy having some upside in these investments. Yeah?
Speaker: 23
01:32:57
Yes. Taxpayers have all the downside and none of the upside.
Speaker: 9
01:33:00
You like ai like the taxpayers having equity?
Speaker: 12
01:33:02
It’s tricky. It’s more complicated than that. You know, you have adverse selection issues and about it it is not a one size fits all and it’s all good. But having flexibility for certain industries to have a different corporate structure or different investment structure is, you know, Pareto optimal.
Speaker: 9
01:33:18
You you don’t do that at all today, Kelly, at Sai?
Speaker: 23
01:33:21
Not today. So very plain vanilla, but we’re continuing to have the conversations about how to be creative, particularly around defense, critical technologies. There’s a lot to do there, and we need to do it very quickly. And there’s some great success stories that we can replicate, and they may not even require massive reengineering.
Speaker: 1
01:33:38
Just for the last few minutes, Kelly, can you give us a very quick contrast, Your life as a senator versus your life as a head of the Speak.
Speaker: 23
01:33:46
Well, I’d much rather be an executive than a politician. So I I was humbled and honored to serve in the sana as a kid that grew up on a farm and the first in my family to graduate from college. It was amazing. But being able to run this agency, which at 7,000 people is considered small, is amazing. But I’m really an entrepreneur and a businesswoman at heart.
Speaker: 23
01:34:08
So I’m approaching this as a businesswoman of service to taxpayers, the government, and I’m incredibly blessed to be able to do it. So
Speaker: 9
01:34:15
I I love it. Thank you for doing it. Yeah. Thank you for your time.
Speaker: 8
01:34:20
In tanking.
Speaker: 23
01:34:20
Tell me a lot. Thank you. Great to be with you.
Speaker: 8
01:34:23
Thank you.