Latent Space: The AI Engineer Podcast
01:17:18 · Shawn Wang, Jamin Ball
[01:17:18] S1: was the other one. [01:17:18] S0: The balance sheet. Oh, wow. Have they raised more debt? And then it was the income statement. Are they actually losing money? [01:17:23] S1: As an investor, why do you get involved in these kinds of [01:17:27] S0: Oh, this is more of like... I mean, I'm You're just having fun. Yeah. I think, look, Altimeter is a firm. We do venture investing, growth investing, and public investing. And I spend a lot of my time on the venture investing in early stage. However, I consider myself like a student of finance, and Anthropic is such an iconic company. You shouldn't have [01:17:45] S1: to educate people on the three statements of accounting.
01:17:45 · Shawn Wang, Jamin Ball
[01:17:45] S1: to educate people on the three statements of accounting. [01:17:48] S0: Yeah. But hey, think a lot of people look at the income statement, the P and L, but the reality is there's a lot to learn from the balance sheet and the cash flow statement too. And so this was more of a, hey. As as just someone who's intellectually curious, I mean, Anthropic is is a really important company to understand. I think if the Anthropic s one came out and the financial profile that was pictured was doomy, and it didn't look like a good business, I think we have a lot to be worried about. Yeah. Because if they're not delivering profits and high ROI, what does that mean for everyone downstream of them? Like, that's... It's... I think it's really important to understand the Anthropic P and L. But what I understood from the Anthropic P and L... Let me just rip through these really quickly. Here's what you're seeing about their gross margins. Lots of leverage in the gross margins. They're improving rapidly. [01:18:38] S1: Which one one nuance on this is this is the half that is not through CloudPartners. [01:18:43] S0: Exactly. This this... No. This is just the GAAP gross margin. Right. Okay. That... [01:18:48] S1: Okay. I I don't know. I I read something about like how... Obviously, Cloud Partner margin would not go into gross margin at all. Yeah. That's 50% of How [01:18:57] S0: many account, I believe, is a lot of the cost that they pay out the rev share is in sales and marketing Yeah. Yeah. Which is below the line, which I which I think what you're By
01:18:57 · Jamin Ball, Shawn Wang
[01:18:57] S0: many account, I believe, is a lot of the cost that they pay out the rev share is in sales and marketing Yeah. Yeah. Which is below the line, which I which I think what you're By [01:19:05] S1: the way, $3,000,000,000 of sales and marketing. [01:19:06] S0: I think it's like 40 something percent of the revenue comes from cloud partners. [01:19:10] S1: It's it's
01:19:11 · Jamin Ball
[01:19:11] S0: not a trivial amount. 48. 48? Okay. Yeah. I was close. Insane. So you see gross margin profile improving. And and sure, maybe it'd be lower if you kind of factored in the third party, you know, the the cloud providers, but like the trend is going up. You see operating margin going up, positive GAAP operating margin. You see free cash flow margin going up. And so to me, what I see is a highly profitable business that is probably going to flip to reinvest in compute and build out. I think the way compute gets built is gonna look different in the future. It's gonna be expensive. There's gonna be more upfront payments, right? I do think you should expect to see the profitability profile of these labs go the other way in the short term as they shift to investing in growth and investing in compute. But the biggest takeaway for me was it's a highly profitable business that's still operating in growth mode, that's seeing some reacceleration probably in the third party data from the new models, which gave me a lot more confidence for the rest of the industry. So long as the revenues show up, the compute obligations will be hit, the supply chains will continue to be saturated and constrained, and companies will continue to perform. And OpenAI and Anthropic, the reality is is they're a huge percentage of the overall AI revenues. And so everyone looks to them as a proxy for the rest of the industry. So if they keep growing, which again, I think a lot of the bears would say they're going to stop growing because open weight models are gonna eat their lunch, like, this, this, and that. But I think those are the important kind of questions.
01:20:40 · Shawn Wang, Jamin Ball
[01:20:40] S1: Yeah. Very important. Very good questions. I I think, like... Yeah. Anyway, do you do you dabble in, like, forward projections or numbers? Like, what what, like, we we... What what should we expect from FY '27? What is [01:20:52] S0: the Oh, I think it's too hard. Okay. Yeah. And if if... Yeah. I I think that's that's too hard. [01:20:56] S1: Because the the the delta is very high. Yeah. Right? And given the year they just had [01:21:00] S0: It's It's a business that is so hard to project because the future is so unknown and unknowable. They'll go public. The sell side research analysts at all the banks will build their models, will kind of have a forward number. I don't know where that's going to shake out. But I do think you'll see a lot of optimism about what the future of this business could look like. But again, would it surprise me if it was much higher than expected or some... You know, anything could happen. It's anyone trying to predict the future, especially in the short term, it's it's as it's as hard as ever. I think businesses at the frontier are the most predictable because they're the least likely to be disrupted. But I don't know. We live we live in a highly uncertain time.
01:21:49 · Shawn Wang, Jamin Ball
[01:21:49] S1: Yeah. The the kind of a plus financial analyst as a PM in my hedge fund I would have wanted is to do physical limits Mhmm. Calculations Mhmm. On, like, okay. You have all these inference optimizations. Where... Like, how much juice is there left Yeah. On the current thing? Yeah. Let's let's say the next gen has has this level of inference. How much can we charge on that? And given the competitive profile and exhibited pricing history of of these things. Yeah. And then finally, how much GPU supply Yeah. Has been locked in and and secured so that translates to this number of tokens, and that's what we can sell for. Because that's, like, the physical limits of what... Where these things can go. Because I think a lot of the financial analysts... And I used to do this. You you would just kind of had this spreadsheet of, like, here's the past performance, you couldn't click the right corner and just drag [01:22:37] S0: it Yeah. Yeah. Yeah. Exactly. [01:22:38] S1: That's not how works. [01:22:39] S0: Can't do that. [01:22:39] S1: Mean, look There's not good an... There's not good analysis. Right? [01:22:41] S0: Totally. I mean, it's... I think there's limitations everywhere. Everyone knows like, hey, NVIDIA can only produce so many chips. You know? Yes. Challengers, Cerebras, TPUs can only produce so many chips. But I think there's other constraints. There's only so much land power shell that's approved and permitted. Correct. [01:22:57] S1: So you do that buildup, right? It's same name. Okay, who has what share?