OpenAI's Financials Revealed, Tesla Robotaxi Debut, Shein's Weird CEO

0:00Let's take a look at OpenAI's newly revealed financials and discuss its massive projected losses. Tesla is also out with its robo-taxi, robo-van, and optimist robot. And we have some questions about Sheehan's IPO. That's coming up right after this.

0:19You're used to hearing my voice on the world bringing you interviews from around the globe. And you hear me reporting environment and climate news. I'm Carolyn Buehler. And I'm Marco Werman. We're now with you hosting The World Together. More global journalism with a fresh new sound. Listen to the world on your local public radio station and wherever you find your podcasts.

0:46Welcome to Big Technology Podcast Friday edition, where we break down the news in our traditional cool-headed and nuanced format. We have a great show for you today because we're going to go deep into OpenAI's financials. Now that the information has opened the books, they've gotten some exclusive details about the company's revenue projections, its costs and its losses, and where it expects to go over the next few years. We'll also talk about the Tesla robo-taxi event coming up in the second half. And then also Ranjan has some questions about the Sheehan's IPO and its CEO. But we are lucky to be joined here for the first half by Corey Weinberg, the information reporter that broke the OpenAI news.

1:26Corey, great to see you. Welcome to the show. Great to be here, Alex. And also, Ranjan Roy is here, as always, on Friday. Ranjan, good to see you. We got some numbers, Alex. I am excited for today. Finally. Nothing really excites the big technology Friday crowd like a bunch of financial projections. Line item expenses and compute amortization and expense allocation and stock compensation. We got it all today. It sounds like, yeah, that'd be a good wrap. That's right. Yes, let's get it into Suno. And next show, we'll make sure to turn it into our second theme song. But, you know, we might joke about it.

2:04And it does sound quite nerdy. But it actually is this amazing Snapchat into not only OpenAI, but like what we can expect from the broader generative AI moment here. Because this story that you broke, Corey, actually has some internal information from OpenAI. And it goes to show some like pretty jaw-dropping projections that the company is making. I mean, specifically around the losses, which we've been talking about at length here on the show recently, but then also in terms of where it expects its revenue to go. So for me, the top line was that they're expecting their losses to get as high as$14 billion in 2026.

2:39Remember, the company just raised$6.6 billion in a round. So its losses could be that high. But we also took a look at the places where it expects the revenue to come from. One of the things that astonished me was that chat GPT is what OpenAI expects to lead its revenue, which it expects to increase 100 fold by 2029. And the bulk of that revenue is going to be coming from chat GPT, according to OpenAI's projections, which flies completely in the face of everything we've been discussing on this podcast and everything we've expected, which is that the API and the other companies using this GPT technology was going to be the driver of OpenAI's revenue.

3:20But it does look like the company's expecting Chatshippity to be the bulk of that revenue. I mean, it already is, but throughout the upcoming history. What do you make of that, Corey? It surprised me too on the top line. I mean, I think, first of all, you need to view these projections and these numbers like you view a lot of startup projections, which is this is in many ways the best case scenario, especially on the top line. I'm assuming this is what they sold investors on, which means that that big round sort of predicated on investors believing this story. Yeah, 100%. And I think, look, when you have growth so far that puts them, you know, sort of in Google and Facebook territory in terms of revenue growth, you know, early in their history, you know, they're going to lean into it and be aggressive and say, yeah, by the end of the decade, we're going to generate as much revenue as NVIDIA or Tesla.

4:12Like they definitely went big with it. And then, yeah, when you dig into that, it's like, OK, maybe you can view those revenue figures skeptically. And I think we all should. But I also think, you know, let's let's actually take some other forecast at face value. And I do think the actual breakdown of that revenue was pretty revealing and interesting. I mean, you have a company that says their main product right now in ChatGPT, which is both the consumer subscription subscription product. Also, there's, you know, an enterprise product for ChatGPT. I don't quite know how that breaks down between the two of them in that revenue bucket.

4:50But yeah, they're saying this is going to be the moneymaker for, or at least the revenue driver for years to come. And it seems like the API revenue is, you know, maybe they're kind of giving it away more than, or actually like charging the full value of it. And it's also more easily commoditized. So yeah, I did think that was pretty interesting. Roger, what did you think when you took a look at this projection and saw that basically the company is expecting to be really it's a chatbot company? I mean, that's what it is. If the majority of its revenue is coming from ChatGPT, it's going to be a chatbot company and not just a chatbot company, but a paid chatbot company.

5:24I mean, yeah, no, no, that that one jumped out at me. And Corey just kind of hit at the most important point that the API revenue could be commoditized because actually, I mean, I have been arguing for a long time that that's actually where the money is going to be. It's in the enterprise. It's in the API access side of things. And maybe they laid out the case. They're arguing it's going to be on the actual consumer facing side, which was interesting to me because even though I'm not going to be on the actual consumer. I've so strongly believed the other way. Maybe it is in the user interface, the UI, the UX side, that they launch great products that everyday people will use, and that's where they're going to win.

6:06Do I think it's correct or right? I don't know, but it's an interesting way to raise$6.6 billion. Is there a limit to the way that this generative AI phenomenon can continue to grow if the leader, which is OpenAI, ends up not really making a lot of money on the API? Like at some point it's like, why are you developing these foundational models if it's, I guess maybe it's just to make the chat pop better? What do we think about this? Corey? Well, I think if you just think about it, as a user of these products, as someone who is also trying to cover, you know, these companies that are growing quite big as a reporter, it's hard for me to keep up with sort of how each of these foundation model companies are actually moving ahead of each other in different aspects of how they actually can can do math do science do you know sort of legal stuff like like it seems like between mistral versus open ai versus Anthropic.

7:16Like, you know, it's getting somewhat, these foundation models are, you know, in very tight competition with each other. And the value, I think OpenAI is saying, is in the consumer and enterprise brand. Not sort of what you're developing for other application developers, but they're kind of casting themselves, I think, as like an essential service that they can provide a lot of value to consumers on and can drive up subscription prices. And that's like an easier story to tell in a fundraising. So maybe that's why they're leaning into it. And no one's going to necessarily hold them to account to it if it turns out any differently.

8:00But yeah, I think it's an acknowledgement that they think the API business is more of a commodity. Right, which is amazing because that is effectively a tacit acknowledgement by OpenAI. admitting that it's not going to be able to stay ahead of its competition and building the state-of-the-art models. Yeah, I think that it's possible. There's other products they say they're going to develop that are quite big. We don't know what that'll look like, but obviously we know there's a lot that's not out in the world that they've teased, like Sora and kind of a perplexity type of competitor to. Yes, the old future quite big potential product we know always comes through.

8:39Yeah, it is interesting, though. I was just thinking about a company like Google, create the killer consumer-facing product and then build off of that, build an advertising business off of that, build Google Cloud and Google Workspace and all these other more enterprise-focused efforts. experts, maybe that is the way they're pitching this. Because I think like versus some boring enterprise API type of company that just, you know, is people are trying to build on and where the cost of those actions go less and less and less build it being the true consumer facing brand that introduces the whole world to generative AI.

9:17I know I've been incredibly bearish on open AI. And suddenly I sound like I'm pitching them for a fundraising. But deck really works for you, man you're like take my money i'm sold yeah looks at one slide all of a sudden he's knocking at the door yeah show me a masayoshi sun deck and i'm first in line but that's okay so that's just looking at the revenue and then things get really interesting because cory and you published this this is again coming from open ai's internal projections and financials it's a there i think this is my favorite chart i've ever looked at from a tech company. This is their revenue versus their costs.

9:55And it is one of those things where like, oh, you look at total revenue and I'm like, oh, that's pretty nice,$4 billion. And then it starts getting into the costs. So immediately, and this goes right to our question about we've talked about in the past couple of weeks, so prime AI crisis and can AI, these AI companies sustain themselves. And you look at these costs and you go, hmm. So Microsoft's revenue share right off the top of that$4 billion is$700 million. So it looks like what they're making something like 20 % of all open AI revenue. The compute to train the models then takes another $3 billion off.

10:31So thinking about profitability with those two alone, you're just barely profitable. So then you get into compute to run the models and that's another$2 billion. Now you're in the red. And then it just adds. Research compute amortization, which is Ron John's favorite line item down a billion, employee salaries down 700 million, general and administrative 600 million, data 500 million, hosting 400 million, sales and marketing 300 million. And you go from this very nice looking 4 billion in revenue after you add in all these costs to a$5 billion loss. And that excludes stock-based compensation, by the way, which is going to be another major cost.

11:13I mean, Corey, when you first came across this chart, what was your reaction? At first, a bit of confusion and mostly trying to understand. I mean, look, I think this is like a new type of business. And so how they run their numbers, how they do their accounting is going to be an interesting thing to watch. Right. Like I remember I like I interviewed some startup one time, like maybe four or five years ago about like why they hadn't hit their revenue projections or why their numbers were slightly off or whatever. And he was like, well, look, we're not running Alcoa here where, you know, some like giant, you know, old company where like we know how the business runs.

11:59It's run the same way for a long time. blah, blah, blah. So I think just first, like understanding how OpenAI is sort of thinking about its business and where the costs are coming from, that, you know, in itself is really interesting. It also is not surprising. I think like Sam Altman has said himself, like OpenAI is going to be one of the most capital intensive companies in history. I think he said the most capital intensive startup in history. So like if we take him at his word, which as we know, maybe you shouldn't always do that. I do think in this case, like he's probably telling the truth.

12:29He He is not saying that this company is not going to cost a ton of money to build. And that is by far the biggest cost is compute. It's the data centers. It's actually being able to mostly train these models. The smaller cost of the compute bucket is to actually run them, which is called inference. And that is, they're saying they're lowering those costs. But training is sort of, it's a huge, huge expense. Yeah, not much lower. $2 billion to run versus$3 billion to train. So, but yeah. Yeah, but that's going to expand over time, essentially, the training costs. Yeah, and I think the idea of these are completely new businesses, there are two numbers that jumped out, which I think were that I had not seen anywhere else before.

13:21And I thought were really interesting. First, sales and marketing at$300 million out of$4 billion in revenue. that's around 7%. A traditional SaaS company is spending 40 to 50 % on sales and marketing. And we have talked about this a lot that, and people, if you've ever used them, they don't really have enterprise customer success. They don't have the old school SaaS sales guy out there. Maybe they'll create that all with agentic AI, but at least in the near term, if they're really trying to move in that direction, the spend is so low on the marketing side. It's amazing to me that they think, unless they're going to really understand how to scale that.

14:00Then the other was gross margin, which you'd reported 41%, where typically software is, I mean, 70 % is the baseline. So the actual profit for revenue or margin relative to your revenue is so much lower because of all the actual foundation model building costs and how that actually scales. I mean, how they even I'm curious what these discussions are like with investors like do they actually present genuine plans around what these graphs look like over the next three years or it's just kind of we'll figure it out no I mean I think they they do I mean if you uh you know at the risk of insulting you know very um well just do it Corey where are you going Corey come on go Like, look, I mean, I wrote about this, like, so, but like the, if you look at the big checks that made up this round, you know, it's a lot of people that had reasons beyond just like a clear financial rationale for investing in open AI.

15:08You had Thrive Capital and SoftBank writing really big checks. Thrive is already very much, they are in the Sam Altman business. They are in the OpenAI business. They are deep in it. They very much have hinged their reputation, I think, on a relationship with Sam and with OpenAI. And OpenAI is going to open an office in one of Kushner's New York buildings. Yeah, in the Puck building, yeah. It's just like, count the ways Josh Kushner has made money off of open AI. Is any part of this industry not round tripping? You have Microsoft investing in open AI and open AI using Microsoft Azure credits. You have Kushner investing in open AI and open AI opening an office in his building.

15:51It's wild. No, totally. But more to the point, Ranjan, I'm curious when you saw the numbers, we've been talking again about like, is this business sustainable? Now we've looked at the numbers. What do you think? Do you have answers to the question? So this is a tough one because, again, as I seem to be like the ultimate open AI fanboy five minutes ago, I actually got less of a clear picture of where this company is going, bearish or bullish, after reading this. And the reason is, the thing it made me most excited is to one day read the S1 filing of this company for the IPO, because it's so weird and complex.

16:35I guess that's the only consistency from the last few months is everything gets weirder. Even Microsoft reported, I think, the cut of revenue was 20%, which was higher than previously thought. You had some information in there around. they've been able to expense last year$500 million of cloud compute, I think it was. First half of this year, yeah. Oh, so first half of this year already. So Microsoft's relationship with OpenAI is bananas. Like I cannot think of another company, certainly at this scale, but even smaller, where I've seen something that contorted. And then even just the way from the accounting side, and it's fair, this is a completely new type of technology.

17:19And I actually, what you're saying, Corey, I do kind of agree with that, that the idea that no one knows, there's no standard accounting practice for how to amortize the value of a large language model because it's so different. In the past, you build software, you have like essentially zero marginal cost. It can go forever. This is a much more cost intensive, like marginal cost intensive way of doing technology. So basically, it became more clear to me, no one has any idea how to actually do the accounting for this, to do the financial projections for this. And we're all in the same ultimate business, basically.

17:59And I think you're right to put your finger on the Microsoft OpenAI relationship being really key to all of this, not just in assessing it. It does muddy the waters on its financial statements. I'll tell you, you look at sort of the actual cash leaving OpenAI, and it's a lot lower than you would think compared to their income statement losses because so much of the expense is tied up in Microsoft compute credits, which is not technically a cash item. So that muddies the waters a little bit. I don't know how long they'll be able to sustain that sort of pace. Um, and then we have no idea how, was it ever finalized?

18:49What of the initial$10 billion was cloud compute? I don't know if it's ever been fully reported. I think it's, it's most, it is the majority of it is my understanding it, whether that means it's seven or 8 billion or I think it's in that range. It's my understanding. But my colleagues, uh, uh, had a great story also earlier in the week, basically saying that Sarah Fryer, OpenAI's CFO, has told employees that, look, we're going to spend some of the$6.5 billion, you know, racing also to develop data centers with other potential sort of companies. And essentially, like, they're in a race to kind of get compute and to get data center space.

19:31And Microsoft, as one company, isn't necessarily able to get a lock on all of it. So So that relationship is, I wouldn't necessarily, it is slowly, they are very much joined at the hip, but both are trying to figure out how do we not become too dependent on each other. I think we should put this all together because we're now we're getting some projections in terms of what they're expecting to spend, right? They're expecting to spend$9.5 billion potentially on training alone, training alone, right? Up from three this year in 2026. That's just in two years. and Corey, you report that their loss, excluding stock comp, could be$14 billion in 2026.

20:13That's a time where they're expecting, again, ChatGPT to be the lead in terms of their revenue. So let's just take our head out of the spreadsheet for a second and think about this logically i mean is there a chance they could potentially recoup all that money from chat gpt subscriptions like how much better would chat gpt have to get because i don't think it's an awareness thing at this point like ranjan mentioned it's they are getting as much word of mouth as they could potentially get and they still are where they are in terms of chat gpt adoption so how much better does chat gpt need to get to start to start to justify those costs i would say like it would basically have to be AGI.

20:58I agree that it's interesting that I was just thinking about like, is it the consumer or the enterprise side that gets commoditized? And you can make a case for or against both. And on the consumer side, that idea of like, how much better does it have to be? I would say, I mean, even out of people I know, most people aren't paying 20 bucks. I think I'm sure we all are to one of the services, but like for the everyday average user, is this something you even need to pay for or want to pay for given the current state of how these things work? I don't think so. So I think like it would have to completely transform or revolutionize, I don't know, like entire new products and entire new problems being solved for everyday people versus it can just write you some stuff or it'll help you with code from that only hit a certain segment or I'm trying to even picture what that product would be that every single person would be ready to pay 20 bucks a month or more.

22:01Yeah, Corey, is this feasible? Yeah, I think it's gonna have to be also just way deeper in the enterprise. I think like just having a consumer product is, you know, it's going to have to be, you know, pretty, pretty insane. It's going to have to be very agentic, you know, where it's doing things for you to use their jargon. But I think if it's able to revolutionize like, you know, actual, you know, there's money, there's, there's a lot of money in the enterprise, I would say, like if they can actually like improve, you know, sort of companies' efficiencies and bottom lines there. But look, I think right now the bare case is a lot of this revenue is from early adopters who are sort of playing around with this stuff.

22:50That's how I would characterize my spending on ChatGT. It's like I haven't really figured, yeah, I've listened to plenty of people say, oh, here's how you really get into it. Here's how you do it really well. And it just hasn't quite stuck. And I'm humble enough maybe to say maybe I just don't get it. And like maybe I just haven't integrated it into my practices very well. But yeah, there's definitely like some early adopter sort of effect going on that will need to expand beyond that. Yeah. And on the enterprise side in particular, we've been talking about it. Like if enterprises all went in because they had to and if they're not seeing a return, they could just as easily pull out pretty fast.

23:27So we're going to see what's going to happen on that point. Yeah. Okay. Last point for me, you mentioned in your story, we talked about this a little bit. we don't know what's going to happen we don't know when their microsoft credit is going to run out and do they factor the fact that that credit could be completely gone maybe that's what's blowing up their costs and you know do they then because you mentioned they're basically either giving away or giving at cost what's coming through their api so does do they then need to start charging a lot more to developers building on top of this stuff in order to sort of stem the losses they're already expecting to see?

24:01Right. Well, I don't think, well, there's nothing in the documents that really answers either of those questions necessarily. They, I do think they, when you see the compute amortization, it is a line that is going up in the, they're going to be expending more on research compute in the coming years. And I would imagine It is with my guess is that it's with the assumption that they won't be able to get as many like research credits from Microsoft for it or they'll have to go to another vendor and have to pay more or something like that. So one quick follow up on that on that front. When are they going to need to raise again?

24:47Yeah. Yeah. I think that is like the question. I think, look, they had a billion dollars on their balance sheet when they went out to raise this$6.6 billion. And they also have like a few billions of like a credit revolver that they raised on top of it. So my very back of the end, and they still have, I think, billions in research compute left from Microsoft. My back of the envelope would say 2026 at the latest. But, you know, this is their competitive advantage is over like Anthropic is clearly Sam Altman being one of the best fundraisers in the world. I think they're going to try to keep leveraging that and keep losing money to stay ahead.

25:28Like if no one's pushing them to like get profitable, you know, they're going to keep spending money on that compute. And on that, I'm glad we got to compute amortization. One thing I had to I had to bring up. Listeners, you should see the smile on Ron John's face when he says the words compute amortization, by the way. It's as happy as I've seen him in months. I know because, I mean, from like a pure student to business, it's interesting. It's like something completely, the way they're approaching it and how large language models like should be thought of in a company's financial statements is a completely new thing.

26:06But my favorite part of your piece was, is that OpenAI is emphasizing to investors a metric of profitability that excludes some major expenses, such as the billions it's spending annually on training its large language models. And I have to give credit, there's a Bjorn Jeffrey who tweeted back, it's time for LLM adjusted EBITDA. And for those listeners who remember the famous WeWork community adjusted EBITDA, I actually don't think it's crazy that they're going to say we are profitable and create a completely new type. And maybe it's going to be the future or maybe it'll be like the thing we all remember.

26:47But LLM adjusted EBITDA is I don't think it's I don't think it's impossible that we see that phrase in a in a filing one day. I think you're 100 percent right. My brain went there. I covered WeWork like like it's an it is very much a place where you're like, oh, I've seen this movie before. I don't think we know all the answers yet in terms of what are the real drivers of the business. That's like an area I'd like to like still be reporting on and actually try to answer. Is it legit to kind of strip a lot of your training compute costs out of your cost of goods sold? Like these are the accounting questions and the business nerd questions that I think are going to be relevant to like how do we actually think about whether this is a good business or not.

27:39Like, that's kind of like the overarching question around AI. It's like, is this okay? The technology seems cool so far. You know, it's really expensive. Is this going to be a good business? Can I weigh in here on the, um, should you include training costs in your profitability statement? Yeah. GPT-3 becomes obsolete the second GPT-4 comes out, right? So the idea that training costs are eventually going to like, you know, taper off or level out or you don't need them and they're not part of your overall mix to me is is just so crazy and you know i know that we're the cool-headed and nuanced show but i just need to say you cannot take training costs out of your profitability statement there's no basis in reality to do that it's crazy i love it i have to get that off my chest i think that's it could be cool-headed and nuanced and factual.