00:00:00 · S0, Max Read, Jasmine Sun
[00:00:00] S0: Your organization has more data, more tools, and more AI than ever. But having more information doesn't mean everyone has the context they need. Who made the decision? Why did they make it? What happens next? Atlassian connects knowledge across your organization so your teams and AI agents can spend less time piecing things together and more time moving forward. Learn more at atlassian.com. That's atlassian.com. [00:00:28] S1: In a few weeks, we're finally going to get some answers on whether we're in an AI bubble. That's because the Frontier Lab Anthropic is going public. [00:00:35] S0: Anthropic gets ready to make its Wall Street debut as the AI giant [00:00:40] S2: AI giant Anthropic. That's the company [00:00:42] S0: based AI giant Anthropic filed papers today.
00:00:42 · S0, Max Read, Erin Griffith
[00:00:42] S0: based AI giant Anthropic filed papers today. [00:00:45] S1: It might raise a $100,000,000,000 at a $2,000,000,000,000 valuation and rescue a whole slew of companies floundering in the debt market, or it might raise a lot less and send the entire stock market into a tailspin, which is to say a lot is riding on this IPO. The near future of the American economy, the medium future of the tech industry, and given that the risk factors in Anthropic s one catastrophic and existential risk to humanity, maybe even the long term future of the human race. At a minimum, the Anthropic IPO will mark the end of an era. The venture investment driven, hype accumulating startup phase of the AI century is nearing completion. But what comes next? In today's episode, we're going to try to wrap our minds around the most important company in the economy, at least for now, and look at what's at stake in its big moment. Are we in a boom or a bubble? Will tech's big bet on data centers workout or fizzle? And can Silicon Valley's most militant AI believers be a normal public company? Or are we entering a new era of AI hype and mysticism? I'm Max Reed. This is Hard Fork. We are live in studio with [00:02:01] S3: Aaron. Okay. [00:02:04] S1: That's a really good start. We are here in studio with Erin Griffith. It's so good to see you in person. [00:02:10] S3: Yeah. Likewise. [00:02:11] S1: There are two big developments in the Hard Fork universe this week. First is that you finally followed me on Instagram. [00:02:18] S3: Oh, yeah.
00:02:18 · Erin Griffith, Max Read
[00:02:18] S3: Oh, yeah. [00:02:19] S1: We can get to that later. Maybe in the segment b. [00:02:21] S3: Yeah. I was on the fence. [00:02:22] S1: Yeah. Well, there's a lot of referendums that we're gonna talk about today. I think that was an important one. The second thing I wanna talk about is that Anthropic announced its intent to go public, which means the rubber is finally hitting the road after however many years it's been of hype and doomsaying and argument. You have been reporting on Anthropic and the AI world for a long time, and I wanted to of pick your brain about this company today Okay. Because this feels like a huge inflection point Yeah. For for AI, for tech, for the stock market, the economy, humanity. [00:02:53] S3: Yeah. Just the stakes are stakes are only that high. [00:02:55] S1: Yeah. Exactly. So what is riding on this?
00:02:55 · Max Read, Erin Griffith
[00:02:55] S1: Yeah. Exactly. So what is riding on this? [00:02:58] S3: I mean, everything. Everything. I mean, think that was our headline, was nearly everything. Practically speaking, this is the first pure play, like, LLM, large language model company to go public, to open its books so we can actually look at the underlying business of this AI boom that has been going on for four years and attracted trillions of dollars in investment and sort of reoriented our entire economy around itself. And, you know, Anthropic, alongside OpenAI and, you know, arguably Gemini from Google, are kind of the companies that are that are driving this. They're like the pillars that are... You could call... I've heard many metaphors. Okay? You could call them the the bottom piece of the Jenga Tower. I've heard them described as, like, know, the tip of a pyramid with, like, a bun... An entire ecosystem of of companies supporting it. But either way, like, they are sort of the quintessential AI companies. And now for the first time, we have kind of a look at underlying business model that so much money has gone into. [00:03:54] S1: So are the investors you're talking to, are they nervous about the IPO? Are they worried about what might come out of it?
00:03:54 · Max Read, Erin Griffith
[00:03:54] S1: So are the investors you're talking to, are they nervous about the IPO? Are they worried about what might come out of it? [00:03:59] S3: Well, I mean, last week, they were definitely nervous. Yeah. Now we've, you know, had a a day or two to kind of look at these numbers and and see. And and some of them have leaked already along the way. So we had kind of a sense that this is the first time we see, like, in a 300 plus page document, the full picture of what Anthropic's business looks like. [00:04:18] S1: So let's let's go there. What what are the the sort of big important things that we can take away from the s one?
00:04:23 · Erin Griffith
[00:04:23] S3: Okay. Well, first of all, I guess it's okay to say that business looks kinda healthy. I mean, it's arguable. There are people that have, you know, made the case that it's not. But I think, like, generally speaking, people have been kinda pleasantly surprised to see that this company is capable of making money. And I mean, when we've seen how much money these companies have raised over the years, we've seen how much they've been spending to build their AI products, I think the general consensus has been like these companies can never make money. And just to be clear, Anthropic posted an $80,000,000,000 net loss. So maybe let me unpack that a little bit. An $80,000,000,000 net loss seems insane, but it's actually kind of a weird accounting quirk where they have to count some convertible debt that they issued to some of their shareholders as a net loss, and that will essentially be cleared in the next quarter or then... Or by the time they go public. And so that's not a reflection of the health of their actual business. What we've actually seen is that they, in the first half of this year, had an operating loss of around 6 to $700,000,000, and that's shrinking from the same period last year where it was, like, over $2,000,000,000. So they're they're shrinking their losses of the actual business that they're operating. On the flip side, they are still shelling out enormous sums of money, and they're on the hook for enormous sums of money to build out their AI infrastructure. So this is the data centers, the chips, the compute power, the very, very expensive stuff that they need to keep training new models and to support the old models. So, like, it's it's this kind of... And Dario has talked about how the company is sometimes on a knife's edge when it's making these decisions and signing these deals. And so they have signed so many contracts in anticipation of the demand. And it's like a very high risk game. If the demand's not there, then they're gonna be sitting on all these contracts, and some... Many of them are non cancellable. If the demand is there and they don't have enough, then they're gonna be losing business. And so that's kind of what's like underlying all of this is like how much AI are businesses and people going to be using, And has the company, you know, basically laid the groundwork for that?