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The Opinions
The A.I. Bubble Is Coming for Your Retirement Account
00:32:40
David Wallace-Wells speaks with the economist and law professor Natasha Sarin about what the coming A.I. I.P.O.s could mean for your retirement account.
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This podcast is supported by BetterHelp. Summer can feel like a sprint. Kids home, trips to plan, routines flipped upside down. It's easy to slip into survival mode just trying to get through it. Then suddenly it's over and you're wishing you enjoyed the days just a little bit. More. Therapy can help you slow down and actually be present for the moments that matter. With BetterHelp, you can connect with a licensed therapist from anywhere on your schedule. Don't just survive this summer, thrive. Visit betterhelp.com newyorktimes this is the Opinions, a show that brings you a mix of voices from New York Times Opinion. You've heard the news. Here's what to make of it.
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I'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. SpaceX 2, 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 Sarin, an opinion contributor and an economist and law professor at Yale. She also runs the Yale Budget Lab. Welcome, Natasha.
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A
Thanks so much for having me.
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So let's start with a really naive question. Why are these companies doing IPOs right now?
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A
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 in 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 going to 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, and 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.
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So just drilling down on that for a second, I mean, you're saying that the motivations here are kind of classic IPO motivations. Raise money for the companies, liquidate cash for the investors, make some amount of social compact with the public by getting them 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?
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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. And 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 multitrillion dollar valuations that they're essentially going to be forcing on the market at levels that if you take space X which is coming this week, and you take the valuation that they're assigning to themselves, which is this record 1.7 trillion that they're going to go out with, that's significantly higher than a Lot of what analysts are assigning to it. Right.
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And 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.
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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. And 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 iPodOS, 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% of stock market growth last year was about just a few technology companies. That 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.
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B
So 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. We 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. How big a part of this story do you think that is?
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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 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.
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But it is striking that young people do seem to be skeptical of the AI future, which is not what you would anticipate totally.
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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. If you take what Darya Amadeh or Sam Altman has said, Dario in particular has been of the view over the course of the last few years that we're gonna 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 harness for economic growth, as opposed to some of the real risks that we know that the same technology in fact poses. And 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 telling that is really about like, you know, when SpaceX goes public, Elon's on his way to being a trillionaire.
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Well, I think at the moment a lot of Americans are 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. But 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?
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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. You 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, we. 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. Everyone 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 into, 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.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. And 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.
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B
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. Three 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, 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. And 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. You 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, 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 Anthropic's first rate model and pay only 5% of the price, that'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, 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 like these companies are at some real risk of expecting much, much higher returns than they are likely to get in the medium term?
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100%? 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. But historically, I mean ChatGPT was, as you were pointing out, launched in the fall of 2022, ancient 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.
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It's like a whole different era and
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the same it was. 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 that sort of transformational potential that existed. And the, 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. Or you have a bunch of these companies by the like GitHub moving copilot 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 revolutional so quickly that we're going to get all this productivity growth. In fact, we're going to displace a lot of labor and 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. 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. And now you have people again not to sort of 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. But that's not something that's going to happen instantaneous, spontaneously.
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But even the way that you're talking about these questions is illuminating to me because you're, you're talking about, on the one hand, the big AI companies and then the firms that are using them, and you're, 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. And 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
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companies, these exact companies. It feels like both an unanswered question and it, and an inherently, frankly, unanswerable question. But also it should make you even more nervous about this bubble conversation that we were having because, and Ray Dal said a version of this last week, it 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. So 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. And I think that is something that is just so striking about this moment.
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B
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 negative, so skeptical? We should have known that all of this was happening. What would be required for that to unfold?
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I 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. You know, I happened to be traveling last week and used Gemini to try and figure out a walking route to allow me to see all of the sights 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, like so phenomenally important.
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But 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, 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?
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For that capacity? Yeah. And how much are you extra are you willing to going to be willing to pay for the best version of
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that or what number of people are willing to pay that totally.
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And so again, this is, 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, productivity writ large. There was sort of a famous saying by the economist Robert Solow 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. And 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.
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Yeah, I mean my own view is, I often think about that Robert Solow quoted, 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, it's transformed the American economy, but it's also what in total given us like, like a boost of maybe half a percentage point of GDP growth a year. And you know, it's a lot, 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 path towards like superabundance 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. Or we tell ourselves that it's all, you know, nonsense, these people are selling us fish oil and it's all, it's all completely worthless, a scam, self dealing, etc. 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 or selling the stuff into the market, the people who are proposing buying that, all of the analysts, they seem to be sort of 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. And 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 or not 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
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large ownership stake and our retirement accounts. Right, which are automatically going to take
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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.
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Totally. Sam Altman 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. You 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.
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B
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. Right. I mean, there's a lot of companies that are able to sustain market interest over long periods of time without actually justifying it on the fundamentals. And so we may be in a future in which which these propositions don't come to pass. The 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.
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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
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B
say how deranged the American investor is? Natasha Surin, thank you so much for the conversation.
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A
Thanks so much for having me. If you like this show, follow it on YouTube, Spotify or Apple. The opinions is produced by Derek Arthur, Vishaka Darba, Victoria Chamberlain and Gillian Weinberger. It's edited by Gillian Weinberger and Kari Pitkin. Mixing by Carol Sabaro. Original music by Isaac Jones, sonia Herrero, Pat McCusker, Carol Sabaro, Efim Shapiro and Amin Sahota. The fact that 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.