In short
The episode argues that massive AI-related IPOs (including SpaceX) are pulling the public into a potentially bubble-like stock cycle, raising questions about whether valuations match fundamentals and whether AI’s benefits will translate into profits for the IPO-bound firms.
Guests
Natasha Serin, an economist and law professor at Yale who runs the Yale Budget Lab; she contributes opinions and analyzes public finance and markets.
Key claims
The IPO timing is driven by access to capital and by letting early investors realize record valuations; public-market index rule changes could quickly expose retirement portfolios. Private credit is already funding AI growth, so going public isn’t purely a funding need. AI skepticism is growing inside the boom (e.g., firms capping usage due to cost; usage-based billing). Even if AI is transformative, the “utility/monopoly” profitability story may be overstated, leaving the public holding risk if a correction comes.
Notable examples
ChatGPT launch (late 2022); SpaceX valuation cited around $1.7T; index inclusion after ~15 days; Uber reportedly winding down employee AI use; GitHub moving Copilot to usage-based billing; Gemini used for a walking route in Madrid; comparisons to internet/railroad bubble cycles.
Written by AI. May contain mistakes. Listen to the episode to check what was said.
Chapters
Tap a time to open that second in VOThe Rise of AI IPOs
0:54 to 1:22
Discussing the emergence of AI companies and their upcoming IPOs.
“It really wasn't very long ago that chatbots, LLMs, and big AI first really got the attention of the public.”
Understanding the Market Dynamics
1:22 to 1:56
Exploring what these IPOs indicate about the economic landscape.
“SpaceX, too, which is both an AI company and a satellite company, is about to go public for a total value of$1.77 trillion.”
Motivations for Going Public
1:56 to 3:21
Analyzing the reasons behind these companies' decision to IPO.
“So let's start with a really naive question.”
Impact on Household Portfolios
3:21 to 6:14
How upcoming IPOs will affect individual investments and portfolios.
“So just drilling down on that for a second, I mean, you're saying that, you know, the motivations here are kind of classic IPO motivations.”
Political Economy of AI
6:14 to 8:13
Examining public backlash and government proposals regarding AI firms.
“That trend is going to accelerate in a world with these mammoth IPOs coming in the second half of this year.”
Youth Perspective on AI Futures
8:13 to 10:27
Discussing generational concerns about AI's impact on the future.
“to make their proposition about their own role, their own large role in the future of the economy seem more palatable to more Americans.”
Risks of a Bubble Burst
10:27 to 12:34
Analyzing the potential for an economic bubble in AI investments.
“these types of models, and ultimately these types of firms?”
Historical Context of Technological Change
12:34 to 14:00
Reflecting on past technological bubbles and their economic impacts.
“It's not like once you go public, you're on this, like, you know, glide path to huge future profitability.”
The Nature of Technological Change
14:00 to 15:00
Discussion on how new technologies generate excitement and investment, often leading to economic bubbles.
“Everyone sees the emergence of this new technology and gets really excited about it and its potential for massive change.”
Valuation and AI Company Dynamics
15:00 to 17:43
Exploration of the current valuations of AI companies and the implications of competition from open-source models.
“having an economy that isn't growing quickly, having the need for the government to step in as a potential backstop.”
Show all 14 chapters
Skepticism Towards AI Implementation
17:43 to 20:46
Examination of how companies are struggling to realize the productivity potential of AI, despite its technological promise.
“model and how many more people are likely to think, you know, I can use this open-source product from China that's 80 % as good as Anthropics' first-rate model and pay only 5 % of the price.”
Future of AI Valuations and Market Share
20:46 to 22:41
Discussion on the uncertain future of AI companies and the challenges they face in justifying their high valuations.
“And flip side, for a while we were all talking about and we were hearing a lot about the idea of singularity or AGI as sort of this like gold star that was coming right on the horizon.”
Transformative Potential vs. Reality
22:41 to 28:00
Debate on the transformative potential of AI and whether it will live up to the growth narratives presented by companies.
“Because, and Ray Dalio said a version of this last week, basically, if you're thinking about it from the perspective of these firms, you have to spend a ton of money and justify these valuations.”
The Transformation Debate: AI's Impact on the Future
28:00 to 31:54
Exploration of the transformative potential of AI and its implications for the economy.
“Or we tell ourselves that it's all, you know, nonsense.”
Transcript
Automatic transcript. May contain errors.0:00This podcast is supported by WTTW. As Chicago's source for local independent reporting, WTTW News brings you essential coverage. Subscribe to the Daily Chicagoan e-newsletter for the news of the day directly to your inbox Monday through Saturday. And on Fridays, explore the natural wonders around us in Urban Nature, WTTW's newest e-newsletter. And watch WTTW's trusted nightly news program, Chicago Tonight at 5.30 and 10 p.m. and stream at WTTW.com slash news. WTTW News. Cutting through the noise so you can see Chicago clearly. This is The Opinions, a show that brings you a mix of voices from New York Times opinion.
0:41You've heard the news. Here's what to make of it.
0:48I'm David Wallace-Wells, a writer for Times Opinion and a columnist for The Times Magazine. It really wasn't very long ago that chatbots, LLMs, and big AI first really got the attention of the public. ChatGPT launched in late 2022. An awful lot has happened since then. But even so, every few months we have another burst of commentary about whether this is all a big bubble. Whether the leading AI labs are raising too much money and spending too much money, given how much they're earning. And leading the whole sector and maybe the whole economy with it towards a crash. But we're about to enter a new phase because two of these companies are preparing for absolutely mammoth IPOs.
1:28SpaceX, too, which is both an AI company and a satellite company, is about to go public for a total value of$1.77 trillion. So what are these IPOs telling us about the risks of a bubble, about the state of an American economy so highly leveraged on AI, and about where we might be heading in the future? With me is Natasha Serin, an opinion contributor and an economist and law professor at Yale. She also runs the Yale Budget Lab. Welcome, Natasha. Thanks so much for having me. So let's start with a really naive question. Why are these companies doing IPOs right now? So if you think about these companies and, you know, SpaceX, OpenAI and Anthropic are all essentially trying to go public within just a few months of each other.
2:15in the second half of this year. And they're at the scale, as you're describing, David, that is kind of unheard of. It's hard to understand like what to make of these like multi-trillion dollar valuations. But one way I've been thinking about them is if you kind of take the three of them together, the sort of expected market cap of these three IPOs is gonna be something like over$3 trillion. And if you look at essentially all of the technology IPOs in the internet boom, so from 1995 to about 2000, and you combine their value entirely, all of them, this is inflation adjusted. SpaceX alone is almost as large as that.
2:54And the three of them together are significantly larger than that. So these are huge IPOs. And part of what is going to happen as a result of that and part of what the motivation is, if you're thinking about why are these companies deciding to go public now, it is about access to capital. It is about being able to sell stakes in this company to a broader pool of investors and being able to have the valuations attached with that and the public market valuations attached with that. And I think that's really a significant moment, not just for these particular companies, but for all that portends with respect to artificial intelligence more generally.
3:28So just drilling down on that for a second, I mean, you're saying that, you know, the motivations here are kind of classic IPO motivations. You know, raise money for the companies, liquidate cash for the investors. make some amount of social compact with the public by getting them, you know, some slice of the pie. But is it the case that Anthropic is unable to raise money now in the private markets? Like, why turn to Wall Street? Yeah, it's such a good question. And in part, we know the answer to that is no, right? And so if you look at something I've written extensively about over the course of the last year or so, has been really the growth in private markets and particularly in private credit markets, which involves a lot of traditionally private equity firms that made equity investments, things like Apollo, things like Blackstone, actually making loans to a lot of these same companies that are powering their growth or powering the data center infrastructure build out.
4:22And so private markets are like keen and eager and stand ready to invest very substantially in these firms. But to your point, that's not the only motivation for why these companies are deciding to go public at this moment. There are lots of motivations for why they're deciding to go public. One of them has to do with the ability of their own investors in the company to be able to realize the benefits of these multi-trillion dollar valuations that they're essentially going to be forcing on the market at levels that if you take SpaceX, which is coming this week, and you take the valuation that they're assigning to themselves, which is this record 1.7 trillion and that they're going to go out with, that's significantly higher than a lot of what analysts are assigning to it, right?
5:05And they're actually trying to relax some of the conditions to buy, right, to allow smaller investors in, which tells you something about the kind of buyer that they're hoping to sell to. Yeah, and there's so many pieces of this that I think are so important for how the market functions and for actually like regular people and their portfolios that I think are really important for your listeners to grapple with. One is that part of what is happening just because of the scale of these IPOs that we started by talking about is they're going to instantaneously be a really significant part of household portfolios through things like the retirement accounts.
5:47And the reason for that is because as these giant IPOs are happening, the stock market indices are actually relaxing their own rules with respect to how long it takes in order for companies to get onto the index. And so the idea that 15 days after SpaceX IPOs, it's essentially going to be part of all of our retirement portfolios and all of our index investing is actually really consequential for households. And in general, these IPOs and the concentration that they're going to represent, you know, as much of even before you had these IPOs, by the way, something like 60 percent of stock market growth last year was about just a few technology companies.
6:27That trend is going to accelerate in a world with these mammoth IPOs coming in the second half of this year. And so that, too, has really consequential effects for household portfolios, because in some sense, It means that we're all massively exposed to the idea that there might eventually be, and what history tells us is true is in fact true, that when you have these types of technological changes, even ones that are hugely beneficial and bring a lot of welfare and a lot of economic growth, things like the internet, things like the railroad, they come with a bubble that eventually pops and households are going to be massively exposed to that and more exposed now that these companies are going public than they were, you know, a few weeks ago when all of them were private.
7:08So one thing you're talking about is that we're sort of all collectively going to be pulled into this investment cycle. And I wanted to pull back a little bit from the question of the IPO and talk about the sort of political economy of AI at the moment generally. Because at the same time that we're having the prospect of all of us getting enlisted in this profit machine, we're also seeing huge amounts of public backlash, particularly around data centers. There's broad unease about the future of an AI-powered economy. We see Bernie Sanders proposing, you know, the American government taking a 50 % ownership stake in these labs.
7:48We see Donald Trump making similar noises and the AI labs themselves saying, we're open to this kind of like, let's talk about it. And on one level, this is, for me, quite strange to be happening at the time that these companies are going public. We are simultaneously ramping up for, you know, this huge distribution of ownership to the public at the same time as we're contemplating the federal government coming in. These companies, which in certain ways are flush with cash, are nevertheless trying to bring more of the public on board to their project, presumably to protect themselves, to stabilize or, you know, buffer themselves against public backlash and to make their proposition about their own role, their own large role in the future of the economy seem more palatable to more Americans.
8:38How big a part of this story do you think that is? Yeah. You can kind of totally understand why there is a fair deal of nervousness about these companies and more generally about what artificial intelligence is going to mean for all of our futures. We were just talking about Michelle Goldberg has a piece on how if you look at commencement addresses over the course of the last few weeks now, you're hearing a lot of backlash from students, you know, who are graduating out into an economy where youth unemployment is starting to tilt up. Again, that's not really about artificial intelligence. That's kind of what happens at the end of a long credit cycle where there's been a lot of money flowing into the economy and a long sustained period of growth.
9:27But it is striking that young people do seem to be skeptical of the AI future, which is not what you would anticipate. Totally. If you look at where artificial intelligence is having like a very clear impact already, the life of a college student on any campus in this country is like a great place to look for where you are actually seeing day to day the educational experience of students being impacted in a way that, frankly, as someone who teaches at a university, I feel I'm watching it in real time. Like, how do you deal with the fact that that obviously is going to bear on the educational experience of those students and ultimately sometime down the road, the labor market outcomes of those students as this type of technology?
10:05If you take what Dari Amadei or Sam Altman has said, Dari in particular has been of the view over the course of the last few years that we're going to displace a very significant share of white collar workers as a result of this technology. And so, again, it doesn't really feel clear what path the future particularly holds. And as a result of that uncertainty, if you think about it from a policy perspective, it's also very difficult to think about how should we actually envision regulating ex ante these types of technologies, these types of models, and ultimately these types of firms? And how do we ensure that the revolutionary potential that they have is like harnessed for good and harnessed for progress and harnessed for economic growth as opposed to some of the real risks that we know that the same technology in fact poses?
10:58And so going back to like, is this part of why these companies are going public or is this part of the rationale for why sort of the discipline of public markets, the both access from an investment perspective, but also the relative to private alternatives, the transparency that comes with some set of reporting that comes with public valuations that comes with tradable shares. Maybe that is, in fact, part of the story from the perspective of these firms. And in that sense, it's sort of a more benevolent story than one that you're telling that is really about, like, you know, when SpaceX goes public, Elon's on his way to being a trillionaire.
11:35Well, I think at the moment, a lot of Americans look at the AI companies and do see a kind of especially vivid illustration of kind of the plutocratic structure of our society, right? They see these five companies. They're run by these five visible people. They're all worth an unbelievable amount of money. And to the extent that we are imagining futures being dictated by the companies themselves, that can be quite scary. And to some degree, going public and, you know, government stakes in the companies both address that problem to a certain extent. It would mean that the country as a whole is invested in the success of these labs and may benefit to some degree, although at what scale is an open question, from the success of the company.
12:18But there are other ways in which some of these approaches, you know, public offerings and or government investment don't change the dynamic, which is to say, maybe most notably, like if this is a bubble, then it's the public that is left holding the bag. It's not like once you go public, you're on this, like, you know, glide path to huge future profitability. It may actually be more likely that from the point of initial public offering, the companies lose money at least for a period of time. So how do you think about that prospect, the prospect of a genuine correction, a bubble popping? You know, part of what makes me somewhat nervous and should make everyone nervous is that it's not like you and I are alone in our sort of view that, oh, we might be on the verge of a bubble, a bubble might be on the horizon.
13:12You know, last summer, Sam Altman was asked some version of, is this an AI bubble? And said, are we in a period where investors as a whole feel overexcited about AI? My opinion is yes. And another thing that should make us somewhat nervous is if we look at history, if we look at every large technological innovation that has changed the way that humans work and the way that we all live, most recently the Internet. But if we go back to railroads, whatever you want, whatever moment you want to look to, there is a very predictable, in some sense, cycle that you see in terms of what happens to the economy at those moments of technological change.
14:02Everyone sees the emergence of this new technology and gets really excited about it and its potential for massive change. investors see that too. And money rushes in to this new technological prospect. And it rushes in in productive ways, but it also rushes in in ways that ultimately don't end up being that productive. So this is if you think of examples during the internet bubble, like the growth of everything, every company that had dot-com attached to it. And ultimately, like, that is nothing to take away from the fact that the internet actually did change all of our lives. But ultimately, what happens is that the bubble bursts and a bunch of debris is left behind.
14:44And that isn't just about a couple of companies that ultimately fail. It is about what that means from the perspective of the broader economy that we all inhabit, in that often those corrections come with deep economic downturns and have the consequence of, you know, having large-scale unemployment, having an economy that isn't growing quickly, having the need for the government to step in as a potential backstop. And so I think from my perspective, the question isn't like, are we in a bubble or will the bubble burst? The question is a bit when. Yeah, I mean, one thing that I think about in this moment when thinking about the IPOs and what justifies these massive, massive valuations is, you know, These are five companies.
15:34Three of them are going public. In the public imagination, they do dominate the AI landscape. But of course, they are only providing one set of products, which is to say access to their LLMs. And they're providing it in different ways, at different price points, at different tiers. But it seems to me like the sort of massive boom story that they're trying to tell is one that's a little bit of a holdover from an earlier era of AI thinking in which the companies and the people who are designing the products often talked about artificial general intelligence, artificial superintelligence. intelligence.
16:12And they said, you know, these products are improving so much that at some point they're going to be able to improve themselves recursively without human interference. And at that point, there's going to be a kind of a takeoff in which the products themselves, the companies that made them, and to some extent the economy as a whole would be rendered almost unrecognizable to people living on the other side of it. Some people call this the singularity. But I wonder exactly how much that feels still true today. And what I mean by that is I was just looking at some data today that just over the course of this calendar year, 2026, you know, the amount of use of Chinese open source AI models has tripled over the course of the year while the use of the American AI products has basically flatlined.
16:57You know, we see a lot of companies, Uber was maybe the most high profile one, saying we're actually winding down our employees' use of AI because it was too expensive given what we were getting out of it. And so if we think about a future in which there's going to be a super intelligent Borg running the whole economy, then yes, racing to be the biggest, best monopolistic AI company is hugely important. And it does justify these absolutely gargantuan valuations if you believe that, for instance, Anthropic will be the one to win. But if you're thinking about a world in which, yes, AI is everywhere, yes, everyone is using it, but, you know, it's not totally clear how many people think it's super important to pay a huge premium to buy the absolute best-in-class model and how many more people are likely to think, you know, I can use this open-source product from China that's 80 % as good as Anthropics' first-rate model and pay only 5 % of the price.
17:56that's a very different world. The AI companies used to talk about building a moat, what they could do to secure their advantage. And they thought that getting to something like AGI or ASI faster was the main way to do that. In a world in which that's at least not imminently on the horizon, and we have all of this low-price competition from below, isn't it the case that these companies are at some real risk of expecting much, much higher returns than they're likely to get in the medium term? A hundred percent, yes. And I will say something that has given me a fair bit of nervousness around AI and the ultimate possible profitability of these companies is that historically, I mean, ChatGPT was, as you were pointing out, launched in the fall of 2022.
18:48Ancient history. Which feels like yesterday, but was less than four years ago, you know? But I guess it's all relative. It's both at once. It's like a whole different era and the same. And if you think about that moment over the course, it feels like we've gone through many chapters. And one set of chapters was the case against AI was coming from like outsiders to the technology. You know, doomers or short sellers who were betting against it or Luddites who just like couldn't possibly think about the sort of transformational potential that existed. And the new skeptics are coming from inside the boom in some sense, because as you're describing, it's like Uber capping AI usage in three months or four months over the course of this year.
19:38Or you have a bunch of these companies, by the way, like GitHub, moving co-pilot to usage-based billing because of how costly it is in order to deploy the technology in ways that they kind of, as they were starting out, didn't fully appreciate. And if you look at a bunch of these, like a bunch of these consulting firms have started to do surveys of companies asking them about their own AI usage, because the sort of optimistic case of the world hinges on the idea that this technology is going to be so revolutionary so quickly that we're going to get all this productivity growth. In fact, we're going to displace a lot of labor.
20:15And they're essentially finding that the technology is working and we all experience it. It's working in newly and better ways over time. But that sort of value proposition hasn't yet arisen for the firms themselves that are trying to deploy the technology. Again, that's not to say that that productivity growth isn't ultimately going to come on the horizon, but it is to say that over the short and medium term, I think companies and the economy writ large are still kind of in figuring out mode with respect to what exactly it means to deploy AI in its most optimistic, most growth potential, most productivity potential way.
20:59And flip side, for a while we were all talking about and we were hearing a lot about the idea of singularity or AGI as sort of this like gold star that was coming right on the horizon. And now you have people, again, not to sort of, I'm using Sam Altman because he's spoken publicly about this recently in ways that have been, that have gotten a fair bit of attention. But he's not the only one saying this, where they're talking about AI and describing it even internally themselves is not really all that useful of a term. and kind of describing not as some sort of, you know, magical switch that's going to flip on at some moment in the short horizon, but instead as the idea that these models are over time going to continue to get better and more useful and more transformational.
21:43But that's not something that's going to happen instantaneously. But even the way that you're talking about these questions is illuminating to me because you're talking about, on the one hand, the big AI companies and then the firms that are using them. And when you're talking about productivity, you're focusing on the firms that are using them. But these are two separate questions, right? If like OpenAI and Anthropic are going to justify trillion dollar valuations or even larger valuations, they're going to have to make a lot of money too. Even if tons of people are making money on AI, it has to be in these companies to justify the value.
22:13And when I hear Sam Altman talking about the possibility that, you know, in the future, AI will be like a utility in the same way that we, you know, pay for our electricity, I think to myself, the electric utilities are not worth a trillion dollars. You know, this is a technology which absolutely has huge transformative potential. But to me, the question is, how much of that is captured by these companies? These exact companies. It feels like both an unanswered question and an inherently, frankly, unanswerable question. But also, it should make you even more nervous about this bubble conversation that we were having.
22:46Because, and Ray Dalio said a version of this last week, basically, if you're thinking about it from the perspective of these firms, you have to spend a ton of money and justify these valuations. not just because you're worried about like, is this a good way to deploy resources? But frankly, because you're worried about losing market share. If you're of a view that the way this all shakes is there's going to be one, two, maybe three large players that are able to capture the market, you have to try to be one of them. And that results in, frankly, the incentive structure to spend a lot and to look like you are doing a lot in ways that might ultimately not be tied to fundamentals with respect to investment opportunities and what is, you know, profit maximizing from the perspective of the firm.
23:35So you should be worried about that. But there's another piece of this, which is that the companies themselves are asking public investors to pay prices at valuations that assume that AI is going to reshape the economy and to pay those prices at the same time as these companies themselves haven't figured out how to stop losing money. And at the same time as these companies themselves haven't figured out how they are going to be the ones left standing at the moment when AI ultimately is a developed technology with a developed set of market players that we all kind of have grown with and understand.
24:14And I think that is something that is just so striking about this moment. So this has been a relatively skeptical conversation about the IPO cycle, at least. And I wanted to close because of that by asking you to tell us, like, what is a version of the story that we could be telling two years from now, four years from now, in which that skepticism looked naive, in which actually there was no bubble. these companies did earn these valuations and more, and we were looking back and thinking, why were Natasha and David so skeptical? We should have known that all of this was happening. What would be required for that to unfold?
24:52I should specify my skepticism in that, and I think this is your view too, but I'm curious if it is. I am actually not skeptical of AI's transformative capacity, in part because I, like you, have been living with it over the course of the last few years and have seen how much it has changed my own life and my own work. I happened to be traveling last week and use Gemini to try and figure out a walking route to allow me to see all of the sites of Madrid, despite the fact that the Pope was visiting in an afternoon. And boy, was Gemini incredibly good at doing that. And so I think it's great. I think it is really like so phenomenally impactful.
25:44But in the context of this conversation, you don't need the world-class AI to do that for you, right? You need like a pretty good AI to do that, especially because you're asking a kind of generic set of recommendations. It doesn't require that much customization or personalization. You know, it's basically, you know, aggregating and presenting to you in natural language the same kind of result you might have gotten a few years ago from a search engine, right? And that's really useful. But the question is how much are you going to pay a month for that value? For that capacity. Yeah. And how much extra are you going to be willing to pay for the best version of that?
26:16Or what number of people are willing to pay that? Totally. And so, again, this is not skepticism then about the technology. And it's not even skepticism about the technology's ultimate impact on productivity, where I think partly we're being a little unfair to AI in that we're in early innings. If you look at the Internet and its impact on productivity writ large, there was sort of a famous saying by the economist Robert Solo who said, you can see the Internet everywhere except for in the productivity statistics. And so I think that's probably a version of what you're likely to see here, which is it's going to take some time in order to be able to ultimately have the productivity growth from AI unleashed.
26:56And a bit the sort of story of the optimistic versus the pessimistic case is going to depend on what the horizon is for that type of productivity growth. And it is going to depend on what type of market share is ultimately controlled by these few, very large, currently leading AI labs. Yeah, I mean, my own view is I often think about that Robert Solow quote. There's a related one that Paul Krugman gave where I think in like 97 or something he said, you know, the impact of the internet is by 2005 is going to be only as big as the fax machine. And I think about, you know, obviously the internet has transformed American life.
27:35It's transformed the American economy. But it's also what in total given us like a boost of maybe half a percentage point of GDP growth a year. and you know it's a lot it makes a huge difference in human well-being especially over long long horizons but compared to the stories that we as a public and in particular the leaders of the these ai companies have been telling us for years it seems really paltry and i i just i think there's something quite weird about the way that we've conceptualized this transformation in our lives which is we've basically told ourselves that we're either heading on a path towards like super abundance in which labor is over and that may be disruptive, but it's going to be completely a different world in a relatively short order of time.
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28:21Or we tell ourselves that it's all, you know, nonsense. These people are selling us fish oil and it's all completely worthless, a scam, self-dealing, et cetera. The likeliest outcome is in the middle in which the world is transformed. But is the world going to be transformed in a way that justifies the growth stories that we've been told, I'm not sure. And this episode in particular, the IPO episode, is striking to me because we used to think, as you were suggesting earlier, the market has this disciplining function. But these days, the people who are selling the stuff into the market, the people who are proposing buying that, all of the analysts, they seem to be sort of buying the incredibly dramatic story of growth much more simplistically than I would have liked and not applying the same level of skepticism that I would have expected from market analysts.
29:17And to the extent that we expect that those valuations will be roughly met by the market, it means that the public is accepting those stories. And whether or not we end up five years from now or 10 years from now living in a world transformed by AI, there's still this big question of whether the growth in the economy and the growth in the profit rates of these particular companies will justify the story that we've been told at anything like a level that, you know, earns back to the investor. And if that doesn't happen, if we've gone into a phase in which the public on the market level takes a large ownership stake.
29:53And our retirement accounts, right, which are automatically going to take a large ownership stake. If we end up as leveraged on these companies as these market valuations suggest, that's a lot hanging on the success of these five companies. Totally. Sam Allman said, you know, when bubbles happen, people get, smart people get overexcited about like a kernel of truth. And so here's the kernel of truth. This stuff is transformational. It is changing the way we work, the way we live. But he also said when bubbles happen, someone is going to lose a phenomenal amount of money. And part of what gives me a little bit of pause about the IPOs and the valuations is some of what we've been describing.
30:35You know, I think I have a bit of nervousness that comes from the unknown and relatively novel and relatively sort of vibes-based approach that it feels like these valuations are falling prey to. And I think that we should all have a bit of pause because it does feel like if you just take a set of fundamentals, we're not really priced relative to what the outcomes that feel like they're reflected. Yeah, I mean, one thing that I think about there is take the example of Tesla. It's not like fundamentals are driving that share price in general. I mean, there's a lot of companies that are able to sustain market interest over long periods of time.
31:23without actually justifying it on the fundamentals. And so we may be in a future in which these propositions don't come to pass, that companies don't gain monopolistic positions, are not earning huge profits, and yet in the market they're treated as the new kings of the economy. And we just have to sort of— And that could sustain for quite some time, right? So we're not telling people to go short SpaceX this week because, in fact, who is to say when, how, if the market will correct itself? Who's to say how deranged the American investor is? So, Natasha Serin, thank you so much for the conversation.
31:57Thanks so much for having me.
32:14If you like this show, follow it on YouTube, Spotify, or Apple. The Opinions is produced by Derek Arthur, Vishaka Darba, Victoria Chamberlain, and Jillian Weinberger. It's edited by Jillian Weinberger and Kari Pitkin. Mixing by Carol Saburo. Original music by Isaac Jones, Sonia Herrero, Pat McCusker, Carol Saburo, Efim Shapiro, and Amin Sahota. The fact check team is Kate Sinclair, Mary Marge Locker, and Michelle Harris. The head of operations is Shannon Busta. Audience support by Christina Samulewski. The director of opinion shows is Annie Rose Strasser.
33:13Thank you.
From the publisher
SpaceX, Elon Musk’s rocket, satellite and A.I. company, is about to go public at a record-breaking $1.77 trillion. This summer, Anthropic and Open A.I. will follow suit, also with sky-high valuations. Are they worth it? The Opinion writer David Wallace-Wells and the contributing writer Natasha Sarin, an economist and law professor, tackle that question and discuss what these I.P.O.s mean for the American economy in the near future and beyond.
(The New York Times has sued OpenAI and Microsoft claiming copyright infringement. The companies have denied those claims.)
Thoughts? Email us at theopinions@nytimes.com.
This episode of “The Opinions” was produced by Jillian Weinberger. It was edited by Kaari Pitkin. Mixing by Carole Sabouraud. Original music by Sonia Herrero, Pat McCusker, and Carole Sabouraud. Fact-checking by Mary Marge Locker and Kate Sinclair. Audience strategy by Shannon Busta and Kristina Samulewski. The deputy director of Opinion Shows is Alison Bruzek. The director of Opinion Shows is Annie-Rose Strasser.
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