Shawn Ryan Discusses AI w/ PALANTIR CEO Shyam Sankar

Thanks for having me, Sean. It's great to be back. I owe you a huge thank you.

I love it. But that was... Yeah, man. So, thank you. But yeah, it's good to have you back. I'm pumped about our conversation today. And I know you got the new book coming out and everything, but what have you been up to?

Sounds like it. Are you looking for real estate in Miami now?

Right on. Right on. What prompted that?

Yeah. So, you know, I think it's important to be in a state where your reps are actually going to rep you. And I think that's part of it that matters. And then you could think about, okay, well, what are the places we could go from Denver and Miami or really Florida had the best both combination of legal and positioning perspectives for us. It's the right place. We don't want to be like the 50th company to go to Austin or something. Austin's great. We have an office there. We love Austin. We love Texas. But Miami felt like the right home for us.

I haven't seen the latest. Catch me up.

I think it's very hard to separate fact from fiction with these things, you know, because you can kind of egg the agents on to doing very specific things to tell a dystopic story like what's going on in the prompting with like the Claude bots. My lived experience using these things operationally is that nothing crazy like this is happening. You know, that actually it's much more contained. It's much more sane. It really is more like an Iron Man suit for the American worker than it is a headless godless machine that's just roving around doing... you know, this is maybe we should just start here. It's like the ways in which I think the American people are really being lied to about AI is that you have on one hand incredible doomerism like hey this thing it's going to lead to mass unemployment 50% of entry-level jobs are going to be destroyed inside of a year or two and on the other hand you have essentially this fantasism it's going to lead to a utopia like untold abundance. I think neither of these things are right. They're wrong for the same reason which is they assume there's no human agency. You know, AI doesn't do anything. Humans use AI to do something.

And the reality is that the future of AI has not been determined. It is being determined every single day based on the decisions we're making. We can choose to use it to build AI slop or new forms of addiction and gambling. We can choose it to re-industrialize the country and bring prosperity to the American worker. Those decisions are being made every single day. We should use our agency as humans to decide what we value. And it's very clear what we ought to value. Then there's another part of this which is age-old. Who are we listening to in AI? We're committing the same fallacy we have in the past which is we're listening to the people who invented the technology not the people who are using the technology. You know, it is and by the way these inventors are geniuses. We need them in America. They are my heretics and hero archetypes that I talk about. But just because they have the genius to invent the technology doesn't also imply they have the genius to think about how to apply that technology, how to govern it. What are the consequences of it? The example I like to give people is the telescope. You know, Galileo did not invent the telescope. Galileo used the telescope to discover planetary motion. Who had a greater impact or a greater opinion of the impact of the telescope on physics and knowledge? Was it the person who invented it or the person who wielded it? So the people we ought to be listening to are exactly the people who are not inclined to give op-eds who are not on, you know, mainstream media. It's the American worker. It's the guy in the submarine industrial-based parts manufacturer. It's the ICU nurse. It's the factory worker making wires or machinery or equipment.

And ask them like what how has AI impacted your job? Has it replaced you or has it empowered you? And perhaps I think the most profound question that I always like to ask folks, how optimistic are you about your children's future in an America with AI? You'll be surprised how optimistic they are.

Yeah.

So let's come to each of these in turn. So let's start with the kids and then we'll come back to this idea of replacement. I have kids too, 13-year-old, 11-year-old. And so this is a personal question. It's not an abstract question to me. And what I think I want them to know is how to use this tool that it's a tool and it can unlock profound education for them. But the people who are going to succeed are going to have two things. They're going to have specific knowledge like who's winning right now at the front lines. It's the guy who has 15 years of experience. We'll talk about operators in a second, but like people who really know what they're doing, have unique knowledge and insight because what the AI doesn't know is that. But then with that insight and a bit of direction to the point of human agency, it is this incredible Iron Man suit for them. So that's one thing specific knowledge is going to continue to be valuable.

The second part of it is do they know how to use AI, you know, so essentially like it is a bicycle. You have to learn how to ride the bicycle and that requires reps. I think that's why it's actually turning into a massive advantage for America because if you just compare it to say Europe, people are really thinking hard. How should we use it? They're just thinking, you know, and the American sensibility is to roll up your sleeves, get your hands dirty, play with the thing, experiment, try it out, do something, you know, a little bit of, and I mean this in the most positive possible way, the cowboy spirit. And that is something that the child's mind is very good at, you know. So I think one of the mistakes that our education system could make is try to restrict AI. In the early days, you're going to have people using it in stupid ways to write their essay for them. It's going to be a sloppy essay that you can tell is AI generated, but that might be what they're needing to get through that initial gate to go on to the more intelligent uses of it, which is, hey, I wrote a first draft of the essay. Critique it. What did I miss? What are other things I should think about? You know, help me elevate my own thinking. You know, it becomes a partner to do these things. I think that's really powerful.

Well, I think the most interesting use cases are going to start where you have the deepest domain knowledge. Like I think that's part of the reaction the American people have is they look at it and it seems like some of these things are kind of trivial. Like you're saving me a little bit of time here and then that's weighed against like crappy content that's being generated, misinformation, disinformation. So on balance it's like why should we believe in this future? Plus I got these data centers coming up and my electricity bill is going up. But if you look at it as hey this is the basis for re-industrializing the country. Like we're going to give the American worker superpowers. They're going to be 50 times more productive than any other worker in any other country. And that's not just a matter of pride. That economic leverage is how we bring back manufacturing to the US. We're not saying we're going to compete symmetrically. This is David's slingshot against Goliath here. Like, yeah, okay, the Chinese are the best at mass production today. What is our asymmetric approach to regaining the very thing that we once created? You know, we're going to reinvent production. So, an example from Panasonic Energy, they make every battery that goes into every Tesla at the Gigafactory in Reno in Sparks, Nevada. This is exquisite high-end Japanese technology that is operated, the employee base in that region of Reno, they're prior casino workers. So, the old apprenticeship journey to learn how to operate and maintain this equipment used to be three years. With AI, it's 3 months. That's leading to more employment, not less. And this is the way in which like it's like to my point of human agency, how do you choose to use this stuff? It really does matter. And I think on the consumer side, yeah, it's going to help me, you know, categorize my bills better. It's going to help me write responses. I think all those things are trivial. You know, the real stuff is going to start in the enterprise and work its way back.

Okay. I thought that's where you were going. I was like, "Holy shit." And it's really compelling to see how you have non-computer scientists. It really proves out the whole thesis here which is like experts, you know, the intel warrant officer the E4 the E8 who are inventing the future of how we're going to deter conflict and that poses lots of interesting challenges which I think apply just as much to the commercial sector as government which is like it breaks rank structure it breaks hierarchy like you're going to have to really embrace the internal disruption that's going to happen but I think this is a great thing for the American worker because for the last 100 years or so the managerial revolution has pulled power away from the frontline American worker towards the bureaucrat. AI is reversing that trend very quickly and that's very destabilizing to the middle managers where you're going to see a lot of resistance out of this. But what it gets at the core problem we have as a country which is the legitimacy of our institutions. You know why do doors fall off planes? Why aren't government basic government services provisioned in a way that we would all recognize as having basic competence? So you have two answers to that sort of question. You can be like, well, these people just don't care. Might be the case, but more often than not, my diagnosis of this, having done this across 50 different industries in the private sector and government, is that the people at the top, even when they do care, they have this steering wheel. They're trying to turn it very, very diligently, but what they don't know, it's actually a prop from the Jungle Cruise ride at Disneyland. Like that steering wheel is not connected to anything. And so that disconnection happens through this bureaucracy. And then you have the people on the factory floor, metaphorical or literal factory floor. They kind of look up and be like, "How can my leaders be so clueless? How do they not realize what's actually going on here?" That's really dangerous because it breeds nihilism, right? Like then you look at it and you're like, "Man, it's hopeless. We should give up. Let's burn it all to the ground. It doesn't really matter." And that's horrible because actually if you burn it to the ground, things will get worse. Like, yeah, everyone acknowledges it's not working right now. The answer is not burning it to the ground. It's fixing it. How are we going to fix it? What's our theory of change here? And the theory of change has to start both at the bottom and at the top. At the top, it starts with people who care. People who want to get things high agency leaders who care about the outcome. Then they need the tools. Everyone needs the tools to do this. And so then how do you empower the people at the bottom closest to the problems to actually go solve these tools? That I think is a quintessential American characteristic. Like we think about it as mission command. Give the intent. Let these people run. Let them cook. Don't overmanage them. Don't drain the creativity out of their souls. You think of every innovation on the battlefront. It was like the E4 rolling tanks across Europe in World War II discovered additional ways of getting through equipment, right? And the generals would let the soldiers cook. This is a powerful moment for the...

Yes. Yeah. So let's... there's this concept called Jevons's paradox. When we started inventing more efficient coal burning steam engines everyone thought that the consumption of coal would go down but the consumption of coal skyrocketed. Now that the engines were more efficient the cost to transport goods per mile was actually dropping. And so then the number of engines we wanted went way up. And the number of trains we wanted went way up. There's something like that that's going to happen here where if you look at something that is fundamentally demand constrained like actually if we made more no one would want it. Yeah, that's a problem. Like you getting more efficient is going to result in more jobs. But I don't think most things in the economy look like that. Most things in the economy, you look at healthcare, it's exploding. It's like 20% of our GDP. Healthcare costs might be our greatest national security risk. Like the solvency of our country depends on being able to deliver care to the American people at a better price and we're only going to need more care over time. So we know we're going to need more care over time for the same amount of money. How can we deliver more care? How can we get more efficient in doing that? That's Jevons's paradox. So an example of this with Tampa General, we're able to get sepsis deaths with the leading cause of deaths in the ICU down to zero from 50% of all deaths.

And there's no replacement of labor there. It's really automating the parts of the job that took the nurse away from the patient's bedside and then help them spend time with the right patients who had the greatest amount.

It is. That's exactly right. That's how we added a third shift to a submarine industrial-based parts manufacturer because the drag was the time they spent like dead weight loss in planning. Like I got to plan what to produce then I produce it. If the planning takes too long like tools down you can't if you don't have a plan yet you can't start making things. If I can shrink the planning process from a couple of weeks to a couple of hours, I have more time to make things. And then organically, the company's like, well, I have more work than I have workers. I need to go hire people. And that's the bounty, the American prosperity that we can see out of this. Now, I don't want to be too Pollyannish. I think there are things we need to make sure of. The most important thing I care about is reestablishing the connection between GDP growth and wage growth. Somewhere in the 70s something broke fundamentally where our GDP kept growing and wages stagnated. You know this has got to be this is the fundamental promise to the American people that the prosperity will be shared and the way in which that happens I call this the productivity dividend. The American worker at the front line who is using these tools to make their companies better. They need to participate in the economic upside of doing that. That's critical to not only the social stability of the country but the prosperity of the nation seizing this initiative.

I'm sorry. AGI, excuse me. I've always felt and I think the present moment kind of shows it that it's like this continuous journey you're on that maybe it's a frog boil, not in a negative sense where every version of the model is more capable than it was before. The models still have what they call jagged intelligence. They're savants at some things. They're not good at other things, but they're getting, you know, even the things they're getting they were not good at, they're getting better at. So, some people would say we're already there. Like for coding, they're so good. We're already there. I still think there's a fair amount of human agency that's involved in getting these things to work. As a consequence, it's valuing taste more than anything. You know like what to build, how to build it, how to think about the problem, what's the elegance of the solution and then it gives you a big lever to go after it. I think one of the challenges you could almost imagine entering a new dark age like the dark ages were caused because we kind of lost fundamental knowledge in the wake of the collapse of the Roman Empire. Even though we get to live, you know, not everyone has to know everything but at the end of the day someone has to know every... someone in society has to know about every part of it, right? I don't have to spend my time thinking about how to design chips I live somewhere else in the stack I get to write code I get to rely on the fact that someone else is a semiconductor expert and knows how to do lithography and make the chips that I depend on but at some point you can kind of see how it actually doesn't work for humans to not be involved with any of this stuff ever. That's the fantasist part of this stuff that if you don't know how it's made, you can't innovate on how it's made. You can't govern it. You can't understand or debug it. And so I think a much more reasonable path is what I call the inductive path. It's like we're on a journey. It's very dangerous to kind of skip steps and fantasize about the future ahead.

I mean, you want to be optimistic about it. You want to be able to see it, but you don't want to be reactionary to it. Things like UBI, I think, are reactionary to this totally unproven idea that there's going to be so much bounty that we're going to be reduced to being as useful as house cats.

Universal basic income. Basically, this idea that everyone should just have an income provided by the government that we fund through taxes because there will be no jobs.

Lots of people on the inventor side of AI talk about that. It's a little bit to my point of should we be listening to the people who are using it and wielding it?

They got the bomb because we had geniuses working on the Manhattan project. And a small number of them thought, some of them very famous, like Niels Bohr, one of our greatest physicists, thought, you know, we should tell the Soviets that we're building this thing. If we tell them, they won't be scared. And then another guy, Theodore Hall, one of the youngest members of the Manhattan Project, he was 18 years old working on this.