What's The Big Deal?
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What's The Big Deal?
OpenAI vs. Anthropic Explained: Business Models, Valuations & IPO Breakdown
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ChatGPT vs. Claude.
Consumer vs. enterprise.
Own your infrastructure vs. lease it.
On the surface, OpenAI and Anthropic look like the same business.
Look closer and the differences are significant and they matter enormously for investors.
In this episode of WTBD, Debs and Graham go under the hood of the two most talked-about AI companies in the world, breaking down what their business models actually look like, how their revenues compare, what recent fundraising rounds tell us about their valuations, and whether there's really room for both to win.
Topics covered:
→ Business model differences: consumer vs. enterprise, API vs. subscriptions
→ Infrastructure strategy: why owning vs. leasing compute matters long-term
→ Strategic partnerships: Microsoft, Google, Amazon and what they signal
→ Revenue and cost efficiency: who's doing more with less
→ Recent fundraising: $850B vs. $380B, why the valuation gap?
→ IPO outlook: target valuations, retail investor appetite, and the $1 trillion question
→ Winner-takes-all or fragmented market? The $5 trillion AI market breakdown
Whether you're an investor weighing up the AI space, a finance professional tracking the IPO pipeline, or just trying to cut through the hype, this is the episode for you.
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OpenAI revenue and the GPT vs. Claude question
SPEAKER_00So we're talking about both open AI and anthropic.
SPEAKER_01Do you think the nature of those partnerships could be a differentiator in terms of the future success of one of these companies?
SPEAKER_00So we started with GPUs, now we've got TPUs. Just think an even more specialized AI compute engine.
SPEAKER_01Microsoft, Amazon, and Google dominate cloud services, but not any one of them winning.
SPEAKER_00The latest I'm seeing on OpenAI in terms of their run rate revenue is $25 billion as of the end of February.
SPEAKER_01Welcome to all our listeners and welcome to this week's episode of What's the Big Deal, where we take a look under the hood of major deals in the public and private markets. And we also explore finance industry developments. Now I'm Deborah Taylor, and I'm going to use my experience from my career in investment banking to bring insights from a public markets perspective.
SPEAKER_00And I'm Graeme Smith, and I'm going to use my experience in private credit to bring the private market perspective here.
SPEAKER_01Thanks, Graham. And please, can you introduce us to what the big deal is for this week?
SPEAKER_00So this week we're talking about actually a couple deals that are going to come to market and something that I suspect we're going to revisit quite a few times this year. We're talking about both Open AI and Anthropic, the two behemoths in the AI space that are both getting ready to launch IPOs. We'll see which one's going to come first. But today we want to spend a bit of time and talk about some of the similarities and some of the important differences between both of these companies.
SPEAKER_01Absolutely.
Overview: what we're covering this week
SPEAKER_01We're returning to the topic of AI, which is quickly becoming our favorite theme. And in terms of what we'll cover in this episode, we will indeed start with discussing their business models. They do sound like similar businesses, but in reality they're quite different. And we'll see try to see which one has the competitive edge. We're also going to look at recent fundraising and their current financials just to get some steer on what the businesses might be worth. And finally, with both these companies likely to IPO soon, we'll discuss whether this is actually a winner-takes all battle for market share of the AI market. As we
On the surface: how similar are OpenAI and Anthropic?
SPEAKER_01said, Graham, right at the start there, on the surface, these sound like quite similar businesses. We've got OpenAI and also Anthropic. They both have AI businesses with large language models. Now, OpenAI, they have Chat GPT now on its fifth version, which I think we're all pretty familiar with. And then Anthropic with their model Claude, which is maybe less known in the consumer market. And they're now on their fourth version. So both have these models that they're running at the moment. But in terms of their businesses, they are quite different. And Graham, you've got a bit of experience looking at software companies. So can you just talk us through, walk us through how the businesses are actually different?
SPEAKER_00Yeah, let's let's talk about first of all how these businesses, you might think of as software companies, but in a lot of ways are and they aren't. There's some pretty important differences, mainly related to the infrastructure for both of these businesses. So in a traditional software model, you have some CapEx and RD spends. You're developing a software platform, but in general, thereafter, your CapEx spend tends to be fairly light. We all like to think of software as fairly, fairly high cash conversion businesses because you develop the product, and then once you have it developed, you sign these long-term customer contracts, get cash in the door, and generally don't have to spend a ton to maintain your platform. The difference between traditional software and AI is because of the compute capacity required for these LLMs, actually, the compute capacity of the infrastructure becomes a really, a really important factor and kind of a limiting factor to growth for businesses like this. So I'm sure we've we've all heard the terms GPU, TPU thrown around. So, Debs, do we know what these terms are?
SPEAKER_01Uh Graham, actually I have
Business model deep dive: how they're actually different
SPEAKER_01to admit I don't. And I love a TLA myself. That's a three-letter acronym. So please, can you enlighten us? What do you mean by GPU?
SPEAKER_00Okay, so I think everyone, everyone who's followed this space has probably seen companies like NVIDIA do incredibly well because GPUs are really the compute engine for AI. So the way the way a typical, say, computer processor works is this is really, really high level, kind of processes information on a sequential basis. The type of math that is required for LLMs really, really likes a compute engine that processes information sequentially. So traditionally, the the type of math that GPUs run has been used for computer graphics. This is just kind of what they've been designed for historically. And it just turns out that the processors in GPUs are just much more efficient and much more, much more suited to the type of math required by LLMs. So we've also seen terms called TPUs as well, tensor processing unit. Tensor is really just the core mathematical item, I suppose, for lack of a better word, that LLMs are computing through. So we started with GPUs, now we've got TPUs, just think an even more specialized AI compute engine. And the thing about both of these, both of these products is they require a huge amount of power. And these LLMs just require a huge amount of this compute capacity in order to operate efficiently. So unlike traditional software, AI, we see both OpenAI and Anthropic making investments in different ways in compute capacity. OpenAI is spending a ton building its own and owning its own compute capacity. Anthropic's also spending a ton of money, but more in the in the leasing or the rental of compute capacity. We can talk about the differences between the two, but in both cases, we're having to spend a ton of cash just to build out the compute platform to run these models. And that makes this investment, I think, quite different from a traditional software
Infrastructure: owning vs. leasing compute (the retailer analogy)
SPEAKER_00business.
SPEAKER_01Okay. So you say that the infrastructure is really important, but the way that they're kind of setting themselves up around that infrastructure is actually quite different for these businesses. Now you mentioned Anthropic effectively like leasing their infrastructure. I believe that's something to do with how they are using that, how they're partnering with the cloud providers. Can you elaborate on that?
SPEAKER_00So Anthropic has been partnering with some cloud providers to provide their compute capacity, namely Amazon and Google. And instead of owning the capacity like OpenAI is doing, they are effectively spending money to lease compute capacity. So think about this in terms of, say, the old retail comparison where we're comparing businesses that rent their stores versus businesses that own their stores. So we got metrics like EBITDAR, so eBITDA, but before rent, that help us compare businesses with the same fundamental business model, but a different financing and ownership structure. And I actually really wonder if we're going to come up with some similar metrics to evaluate businesses like this, where you've got Anthropic that's spending a bunch of money to lease capacity with partners like Google and Amazon. And then you've got OpenAI that's touting huge infrastructure investments in terms of owning its compute capacity. They're also, of course, partnering with some of the big cloud providers. Of course, Microsoft and VIDIA have both made big investments into OpenAI as well. But what OpenAI has been telling investors is that actually us spending, I want to say it's $500 billion or committing to spend half a trillion dollars on compute capacity is a really, is a really big barrier to entry just because they want to own the capacity and the infrastructure. Which one turns out to be the winning strategy? I think it's probably too early to tell yet. But I can certainly see benefits and drawbacks on both sides of that story.
SPEAKER_01For sure. Because, you know, if as you mentioned, the analogy with um retailers that own or lease their buildings, you know, if you own your own infrastructure, although it's costly up front, that gives you a huge amount of control, you know, particularly if there are constraints around capacity. Well, that's, you know, you that's yours to manage. Whereas if you're renting, which is Anthropic's uh sort of angle on this, then sure, they don't have to pay for everything up front. But you know, and also maybe it gives them agility. You know, they can tap into other sources whilst they're growing. But then the downside is that, you know, if there are constraints around capacity, they're just in the queue. They are kind of downstream, if you like, of those providing the capacity. So in the short term, it sounds like it gives anthropic an advantage around agility and the cash flow side. But longer term, maybe it skews the benefits to open AI on the upside.
SPEAKER_00Quite possibly. And again, I'm I'm certainly no expert in this space, but everything that I understand about the AI space, about large language models, really suggests that compute capacity is the barrier to not just entry, but barrier to progress, and that the more compute capacity we have coming online, the smarter these models are gonna get, the better they're gonna perform. So right now, one may have an advantage over the other in terms of the current product offering, but there is an argument to say that, say, OpenAI spending this huge amount of money on compute capacity, even though maybe their product offering for certain customers isn't as interesting as Anthropics today in the long run, might actually turn out to be a really important part of the strategy. Again, I think it's wait and see a little bit. I know there's a bunch of compute capacity that has been committed, that's been being that's being built right now and is going to start to come online soon. And I think we're gonna see some really interesting step changes in the capability of some of these models in the not too distant future. And I think at that point we might start to get an idea of just how how important owning that infrastructure is versus leasing it. It's uh it feels a little bit too early to make that distinction just now.
SPEAKER_01Absolutely. And I mean, to be honest, I think it's worthy of a whole separate episode talking about the infrastructure side of things, you know, the amount of money flowing into these hyperscalers. So maybe let's just park that for now. Um but let's talk about another area where they're quite different in terms of their route to market, because actually OpenAI and Anthropic, they've kind of tried to sort of gain market share in quite different ways, haven't they? Can you talk about that, Graham?
Route to market: consumer vs. enterprise focus
SPEAKER_00Yeah, I mean, I think everyone, well, everyone listening to this, I think, will have heard of, if not used, both. I mean, I don't know about you. I actually use both on a regular basis. I find them suited, better suited for different tasks. OpenAI has got a fantastic brand and consumer awareness just in terms of their reach. They have spent a lot more focus on the retail consumer, right? And the the benefit to that is the is the visibility, it's the brand. The drawback is think about how how little most consumers want to spend on technology like this. I can't remember the stat off the top of my head, but I think in in terms of the percentage of customers, the vast percentage or the vast majority of customers in terms of percentages for open AI are not paying. They're on the they're on the free tier. Right. So if you compare that to Anthropic, who's really gone after enterprise customers with Cloud, I mean, Cloud Code is so is so popular because it's such an interesting tool. But also, if you think about the way they have marketed themselves and built their brand, building or sorry, selling, selling to enterprises, they've got more revenue visibility, longer-term customer contracts. They're selling to people who actually have money to spend on this kind of technology. I mean, I personally I wind up paying for both every month, but I'm a drop in the ocean compared to the big corporates that spend millions and millions of dollars per month, per year, whatever you're looking at, on tools like, on tools like Claude. Uh so I do think right now, Anthropic has the slight advantage in terms of business model. Just great customer base, better revenue visibility. These companies both burn a ton of cash right now. But if we think about how do you value businesses, what what kind of revenue is more interesting? It's the predictable recurring revenue that investors find a lot more interesting. So I think despite the fact we've got different types of infrastructure right now, it feels to me like as we as we sit here today, which company is doing better right now, it feels like Anthropic. Do they continue to keep doing better in the next, say, three, five years? Who knows? We'll see, we'll see what OpenAI's compute capacity does for them. But right now, I think Anthropic is in a really, a really interesting and exciting place.
SPEAKER_01Absolutely.
Revenue breakdown: subscriptions vs. API and what it means for quality
SPEAKER_01And I think I think um one thing that we could just sort of touch on is the fact that we have very limited data about their numbers. Um, but what we do know is the splits of their revenues in terms of sources or their revenue streams. Um so the latest figures that I've got for OpenAI, about three quarters of their revenues are subscriptions, you know, particularly from members of the general public, and the rest APIs, that's basically paying for sort of automated access to the lat the models. Um whereas for Anthropic, about 85% of their revenue comes from APIs versus the rest from subscriptions. Now, my understanding of APIs, I don't do coding myself, but I do work with people that do, is they spend a lot of time setting up code that then automatically pulls the data in from these APIs. So that presumably gives quite a lot of stickiness to those API revenues versus subscription revenues, which you know, they are generally viewed as quite good quality revenues, but you can just turn them off on a whim and switch provider, which maybe in a way is not so easy with APIs.
SPEAKER_00Yeah, I think that's absolutely right. So API just simply stands for application program interface, I believe. Okay. All it means is this is I should check and make sure that's right. But all this, all this really means is if you're a, if you're a software company, if you're a developer, and you want to integrate Anthropic's product into your platform, either Anthropic or or or GPT, that doesn't matter, you're gonna use some kind of interface to interface with that product directly vis-a-vis an API. That differs massively from the consumer where you're sitting in front of a chatbot effectively. And to your point, if you want to change that to another one, you can do that really easily. So if you're building a if you're building a program of any kind that really relies on a specific type of AI and an API call into either anthropic or uh or open AI, you're a lot more likely to be, to be sticky. And it's not to say, by the way, that you can't rip those out and change it with something else, because I can also see a world in which these models get so good that you can quite easily take that same, take that same program, plug it into the competitor API, and the model is just so good it understands exactly what you need to do and takes everything from where you started and just keeps running with it. Are we at that point yet? Probably, probably not. So I can really see a at least a near-term benefit for Anthropics Cloud in terms of their stickiness just through developers building cloud specifically into their product.
SPEAKER_01So we've talked a bit about the infrastructure differences for these companies. We've also talked about the differences in their route to market and their focus on different and on different types of customer. What about their strategic partnerships? I know that OpenEye is, well, that's well known for having a very close partnership and actually quite a lot of funding from Microsoft. Um, on the flip side, um Anthropic, a bit closer to Google and Amazon Web Services, obviously because it leverages their cloud services. I think also they've been involved in some funding as well for Anthropic. Do you think the nature of those partnerships could be a differentiator in terms of the future success of one of these companies?
SPEAKER_00Maybe. I think it's too early to tell right now. And the reason the reason I say that it is that it does feel like there's actually quite a bit of overlap between between the two. We've seen, you know, Microsoft, NVIDIA, Amazon make big investments to to both of these, to both of these platforms. So you can also see this as a way for some of the big guys to be hedging their bets a little bit. I mean, obviously, Anthropic's got a huge commitment from Microsoft. That's the that's the main partnership. But we've seen we've seen these big players make investments into both platforms. So I I don't I don't know yet. I don't know. I mean, what do you what do you think? Do you think it's a real differentiator just yet?
SPEAKER_01Um, it's interesting, and we might come back to this. But my view is that it increases the chance that this will continue to be a fragmented market sort of as it evolves. Because we've seen Microsoft, Amazon, and Google really sort of dominate cloud services, but not any one of them winning. And I just wonder to what extent the fact that they are all partnering or with both OpenAI and anthropic, that continues to result in fragmentation of the market rather than just consolidation around just open AI or anthropic. But I think that's a really interesting discussion point. And I'd love to come back to that. Um, but yeah, that's my view. I don't think it's necessarily that you if you align with one of them, you're gonna win.
SPEAKER_00Yeah, I agree with that. I mean, the thing, the thing that I think about with with this kind of thing is this technology is so quickly becoming so good. If one of them gets to the point where maybe I we we used to talk a lot about developing real artificial general intelligence or AGI. I feel like we've pulled back from that a little bit in in recent months. But if one of these models just gets so good that the other one is almost rendered useless, then at that not not useless, but so good you just you just don't need the other one. Do you wind up in this winner take all situation? And is this some of these cloud computing platforms hedging their bets a little bit? Yeah. I don't know. I I wanna I want to keep up to date on this and and continue the chat for sure.
SPEAKER_01Absolutely. Um well, let's talk
Financials: revenues, costs, and training efficiency
SPEAKER_01about one other area where there is a difference. Uh we have some information about the revenues and maybe even a little bit of information about the cost of these businesses based on recent news articles. Could you just kind of provide us a little bit of insight into the numbers for these two companies, how they compare, and maybe what that tells us about which one is winning at the moment?
SPEAKER_00Okay, so right now we've got both Anthropic and OpenAI kind of in a similar, similar ballpark. So I just want to look at my look at my stats here to make sure I've got this right. So the latest, the latest I'm seeing on OpenAI in terms of their run rate revenue. I want to come back to the run rate discussion in a second, is $25 billion as of the end of February. It's crazy to think that in today's world, the end of February for a business like this is actually quite dated. And then Anthropic, we're talking about $30 billion run rate as of early April. So a little bit more recent. So both, both very much in the same ballpark in terms of revenue. Now, run rate revenue, you can you can really make an argument for why that's important for a business like this. For anyone who doesn't know, when we think about run rate revenue, we're trying to form a view of effectively what is the revenue of the business today kind of going forward. Because if you look at a high growth business like this, I want to say, I think I read a stat saying anthropic doubled their revenue monthly, like from one month to the next, like not that long ago. So usually when we're putting our conservative investor hats on, we're looking, say, last 12 months to get a view of underlying real performance. But for companies that are growing so quickly, you you generally tend to look at revenue on some kind of run rate basis. So I don't know how run rate here is being calculated. And I think it'll be really interesting once we start to get more detail through both these companies' S1s to find out how they're thinking about some of these run rate calculations. Because you can take a pretty simplistic approach and take the last quarter and multiply it by four. You can take the last month and multiply it by 12. You can kind of form a view that that's a semi-reasonable way to look at a business like this. But there are ways that these run rate calculations can get really, can get really muddy. Like let's say one of these, one if not both of these companies are including some some kind of some kind of unsigned but maybe expected contract. Let's say they are assuming more revenue comes online from compute capacity that's about to come online but hasn't been turned on, or we haven't received contracts that that underpin it yet. I don't know what's in these numbers yet, and I don't know how much confidence we can place in them. Um and that's something I'm really interested to to get under the hood of once we start to get a little bit more detail through through the S1s.
SPEAKER_01Ooh, so it does sound a little bit murky, but nonetheless, quite surprising that Anthropic, having been very much the late starter, um, has at least matched OpenAI's position in terms of its revenues and possibly is overtake. That's quite significant, isn't it, Graham?
SPEAKER_00Yeah, agreed. And also I'm I'm trying to find the last stats that I've seen on the purported valuation. I want to say OpenAI was around a trillion. And I'm just kind of surprised that the target valuation for for each of those is so different right now. Right. Because if we've got anthropic that's really caught up to OpenAI in terms of revenue, I would argue today probably has a higher quality of that revenue in terms of visibility through enterprise customers. I'm just kind of surprised that we're not talking very similar valuation targets for both of these businesses, unless there's there's just a huge amount. Of value ascribed to OpenAI's compute platform in their evaluation. But these are we no one
Anthropic's training cost advantage: 4x more efficient than OpenAI?
SPEAKER_00really knows yet, right? Because all we've seen are some headlines that have been talked about in the market. We don't have any real detail to evaluate yet. And I'm really, I'm really interested to start getting some of this and forming a real view.
SPEAKER_01Absolutely. And I think even compounding what you were just saying, something that I was reading recently was about efficiency of training the models. So OpenAI, I think they're reported to have training costs which are about four times anthropics recently, which, given the comparable performance, you say that you use both these models, I do too as well. There's no real discernible difference in terms of the quality. It suggests that Anthropic has been much more efficient about its approach to training its model. And maybe, and this is just my interpretation, the fact that they're focusing on enterprise customers, maybe they're being much more focused about how they train their model for a specific use case. Whereas OpenAI, they're having to train Chat GPT for all applications. And maybe that is making them less efficient about how they deploy their training costs. So we're in a situation.
SPEAKER_00I don't know. I'm interested, I'm interested in learning more. It's a it's a really I it's a really fascinating topic to dive into. Um, but just the amount, just think about the amount of cash that needs to get spent to bring to bring these models to life. It's the infrastructure the investment in the actual infrastructure. It's the the ongoing energy cost. Like a huge amount of that cost is spent on model training. And then you finally get to spend all the money on the CapEx and spend all the money training the model. Now I finally get to the point where I can start selling the model and actually earning money on the actual, the actual, I think inference is the term that that tends to be used for that.
SPEAKER_01Absolutely. And actually, that's a great point. And it brings us very nicely onto their fundraising because both of these companies have been raising extraordinary amounts of cash. They've had to. They are burning through cash at a huge rate, not expected to be cash flow positive for you know a number of years yet. Um, so let's talk about their fundraising because it does give us some insights into what these businesses are worth. So
Fundraising rounds and what they imply for valuations
SPEAKER_01um, Graham, what do we know about the recent fundraising rounds in particular and what it implies for their valuations?
SPEAKER_00Let's see. So they're they're both in similar kinds of states in terms of their development as companies. So I've just got my my notes here in front of me. Anthropic raised their Series G in February of this year. They raised $30 billion through through that fundraise at a $380 billion valuation. Uh OpenAI has been has been raising has been raising more money, admittedly, recently. Their last fundraising was their Series F, $122 billion at an $852 billion valuation. And to be fair, they they raised also, I guess we've got two two Series F dates, one in February, one in March. In February, they raised $110 billion, in March, $122 billion. So, you know, $230 billion raised just earlier this year. And again, we know we know where that money is going. This is going to building out that compute capacity. Um, so that that might explain part of the difference in terms of in terms of the expected IPO evaluation is just that that asset, that asset heavy infrastructure that OpenAI is building for itself.
SPEAKER_01Okay, that's really interesting. So, because I think we have struggled so far to say why, you know, if they're both comparable in terms of their revenues, if they're both, you know, doing really well at gaining market share. Um, why would they have such a difference in terms of their latest valuation? As you said, the latest fundraising gives uh OpenAI a valuation of about $850 billion versus anthropics at closer to what, $380 billion? That's still quite a big difference. But you suggest maybe that's because of the infrastructure differences.
SPEAKER_00Potentially, I don't know. I'm literally this is I'm literally making this up on the fly. And you kind of you look at the difference between between those two numbers and you say, okay, OpenAI is investing a half a trillion dollars in infrastructure. That's about the difference in terms of valuation between the two, and you say, okay, maybe, maybe that's it. You can also see OpenAI pitching to this, uh pitching investors with I can see people being worried about overspending and overcapacity, but if you think about there just being an unlimited demand for compute capacity for all these models, you could also see OpenAI saying, hey, if things, if things don't work out with some of our models and we don't need it all, what's stopping them from leasing that to Claude or whoever else? Right? Could be it could be an interesting secondary revenue stream for them.
SPEAKER_01Oh, that's a really good point, Graham. Completely see that. That basically you've got that ability to pivot with that infrastructure in a way that Anthropic doesn't. So that control point really about leasing versus owning your assets really comes to the fore there. Um, I think what's interesting, just looking at the numbers from the or and the information about the recent fundraising, that we do have slightly different types of investors participating. In particular, Anthropic
Investor base differences and IPO implications
SPEAKER_01has much more um involvement from institution investors. We've got Fidelity, DShore, well-known institutional investors, quite heavily involved in more recent fundraising compared with OpenAI. I do wonder whether that will give Anthropic a little bit of an edge when it comes to the actual IPO, because these are the sorts of investors you're really looking to to be big participants in that actual IPO event. So I think that could sort of flatter slightly their valuation when it actually comes to the IPO. Um, but the numbers I'm hearing um sort of rumoured, and it is very much sort of rumors at the moment, that Anthropic is aiming for a valuation of about $600 billion versus OpenAI looking for a trillion dollars in terms of their IPO valuation. Um what do you think about that compared to the recent fundraising?
SPEAKER_00It seems it seems relatively in line with what we might expect. I guess if we're saying $600 billion for anthropic, you say, okay, last funding round done at just about $400 billion on the basis their run rate revenue, however that's being calculated, has doubled in the last couple months. Do do you see a world in which their valuation at IPO is quite a bit higher than the last fundraising round? Yeah, you probably do. So that doesn't sound too crazy. And again, on the open ASI, the last, the last private investment they had and valued them at $850 billion. By the way, compared to the compared to the SpaceX discussion we had the other week, where they're going from, I don't know, $800 billion to $5 trillion, going from $850 to a trillion doesn't sound too crazy. So I I don't know what I don't know yet because we don't have all the information. But based on the trajectory that we're seeing here, those don't sound like insane numbers to me.
SPEAKER_01Yeah, absolutely. And actually the other thing that we're hearing a lot of, um, both in relation to SpaceX and Anthropic and OpenAI, is that there's expected to be really large retail allocations. Typically in an IPO, you get five to 10% uh allocation to retail investors. And I think SpaceX, we're expecting it maybe a 30% allocation and possibly similar for these companies. Um and that just reflects the fact there is so much appetite uh from the public to invest in these companies. You know, it's really caught the imagination, I think, of the public, hasn't it?
SPEAKER_00Yeah, I mean, just think about the conversations you have day to day. I mean, we both were both in financial training. So obviously this comes up all the time in terms of what AI tools can we use? Are are there any of these tools that we think are going to replace our jobs or someone else's jobs? Just think about the number of conversations you have about this kind of platform on a day-to-day basis with with whomever. So, on that basis, with everyone kind of invested and excited, can you see there being a lot of retail demands? Yeah, probably.
SPEAKER_01Absolutely. I think
Valuation sanity check: is $1 trillion realistic for OpenAI?
SPEAKER_01we should probably challenge slightly what we're hearing. Um, I don't want to kind of get too swept up in the excitement of AI. Um so I did a little bit of analysis on the valuation side. And I think if OpenAI are targeting a $1 trillion valuation, um, we know that there is a lot of investment for them at the moment that really drags down their free cash for in the short term. There's good expectations longer term about the fact that they have control over their infrastructure. But the the valuation of $1 trillion does require really aggressive growth. I mean, we're talking probably revenue growth, um, KGO of about 30% over the next decade. And it would give them an implied revenue multiple. Remember, revenue multiples are really important for um IPOs, um, a multiple of about 40 times, which is not dissimilar to what we had with Cloudflare when they did their IPO, but they were very much positioned as the market leader in network security. That's the market that they operate in. Whereas OpenAI obviously wouldn't be necessarily the market leader, they kind of share that position at the moment with Anthropic. And in terms of Anthropic's rumoured IK valuation, about $600 billion, um, they do have much lower CapEx needs at the moment. Longer term, as we've mentioned numerous times so far today, sort of longer term concerns about ability to um kind of control their infrastructure and maybe capacity constraints, um, but much less stretching valuation. We're probably talking um a revenue Kager over the next decade of around 25%. And that valuation would put them on a multiple of only 20 times. So slightly less ambitious, I think, when we're talking about anthropics IPA valuation. Now, I think the big question, the question du jour, shall we say, is really whether the valuations that we're hearing rumoured, are they supportable for both companies, or is this a winner-takes all
The big question: winner-takes-all or fragmented $5 trillion market?
SPEAKER_01situation where really it's only feasible for one of them to dominate in let's say 10 years' time. Now, I'm hearing numbers for the global AI market in 10 years' time of about $5 trillion, which so we're seeing a huge sell-off in the public markets for companies disrupted by AI. So there is going to be some presumably some transfer to the businesses that benefit from AI. But in addition to that, there's going to be hopefully productivity improvements. So all of that should result in a really vast market. Um, so five trillion dollars is what's being talked about. Now, if we use the numbers that I've just talked about in terms of the revenue pagers for open AI and anthropic, that would put them on revenues of about 300 billion or slightly more than that in 10 years' time. That's only about six or seven percent of a five trillion dollar AI market. And that actually sounds quite achievable, doesn't it? It doesn't sound too, you know, too ambitious. And in my mind, that points to a much more fragmented AI market, not just this duopoly or even monopoly by one AI company. It suggests that there's going to be spoils for lots of different participants in the market. Probably Amazon, Google, Microsoft with their cloud services, possibly some of the end users in terms of um companies like healthcare companies, robotics companies, financial services, who then need to apply the AI in their business. They'll want a piece of the pie as well. Um so I think in my mind, the numbers suggest that we're not talking about a winner-takes all situation. But Graham, what do you think?
SPEAKER_00I think it really depends on how these models improve in recent or in in coming months and coming years. In terms of the in terms of the overall landscape, in terms of the potential size of the market, I very much agree with you. And I also hope that's the case, by the way, because I think the worst thing that we could that we could do really as a society, if you think about, if you think about the potential for this technology to put people out of work, like really, really take over huge pieces of the economy, I think the worst thing we could do is really give that to one player. The thing I think about sometimes is if you think about the the compute capacity that's coming online, think about say OpenAI building all this compute capacity. Like, do we reach a point where one of these models reaches maybe not AGI, but a level that's close enough to that where it's just so good that it kind of renders the other ones not useless, but certainly not as useful as they used to be. And in that, in that scenario, do we end up in more of a winner-takes all market? Like maybe, but I would hope I would hope, but I'm not I'm not holding my breath that we have some kind of regulation that prevents that from being the case. I think that's kind of a big ass just given one, the political environment in the US right now, and two, just how much faster this technology is progressing than anyone in government probably even can keep up with. Um, but we'll we'll see. I don't I don't know if we have an answer to that question right now, but I certainly hope you're right. Um because it's it's a really it's a really weird time in history right now. You think about just the the history of computing where we ha everything used to be governed by this thing called Moore's Law, which basically said every what one to two years, the number of transistors on a computer processor would double. And that was kind of the thing that limited progress. Now it's how much money can you spend on infrastructure, how many GPUs can you buy, how much power do you have access to? And it do we wind up in a situation where the winner is just the one who builds the most compute capacity and therefore trains the best model? Maybe. I don't know.
SPEAKER_01Yeah, it does, it starts to feel a bit sci-fi, isn't it? I mean, I still remember Star Trek.
SPEAKER_00Right.
SPEAKER_01Having those flip phones for um being able to teleport around the universe. Um maybe we're nearly there.
Final takes: who are you backing?
SPEAKER_01Um but uh no, it does feel very um, it feels very sort of sci-fi, but also I think very exciting from an investor perspective. And I mean it's important we don't get swept up in uh just all the rhetoric um around the IPO companies that you challenge the valuations. But there's definitely opportunities, and the skill here is identifying where the opportunity is. Is it with these newcomers with their like large language models? Is it gonna be with some of the incumbents in terms of the cloud services providers who could end up taking some of this um AI market, or even, as you say, disruption from someone else completely? And really interesting to see how this plays out, I think.
SPEAKER_00Yeah, I think this is gonna be the first discussion of many. And we'll get we'll get a lot more insight and a lot more detail as we get closer to listing. And I guess the big question is gonna be who's first? I do feel like there's gonna be a big first mover advantage in terms of investor appetite valuation. And I'm sure they're both, as in anthropic and open AI, are both rushing to be first to the to the starting line here.
SPEAKER_01Which one's your money on, Graham?
SPEAKER_00I'm gonna go, I'm gonna go Cloud Anthropic for being for being first. And I guess I say that just because of the the enterprise tie-in. Like, do they do they have more potential and I don't know what their customer this looks like, but do they have more entrenched relationships with, say, you know, some of the banks, some of the stakeholders that actually bring the IPO together? Uh I don't know. I don't know. That's just a shot in the dark. What do you think?
SPEAKER_01I'm gonna actually go the other way. I'm gonna go with OpenAI. Um, I think the pressure's on with them. Um if they don't move first, there's very much a risk that the IPO just doesn't sort of take off in the way they would want. I think also just some of the messaging, some of the public statements that they've been making maybe suggests that they're really pushing to open uh to IPO soon. Um but hey, let's see. Um we'll see how it plays out. We'll we'll watch this space definitely and hopefully many more episodes to come on both AI and also definitely the infrastructure side of things. So I hope that all of our listeners have enjoyed listening to this week's episode uh into our deep dive into open AI and anthropic. If you have enjoyed listening, please do like and subscribe to our podcast. And if you're listening on YouTube or watching on YouTube, please do um subscribe and also uh leave us a comment. We do love to hear your comments and we will respond to them, won't we, Graham?
SPEAKER_00Definitely. No, 100% we will. Yeah, please please engage, let us know what you think. If there are any topics you want to hear about next as well, let us know down in the comments and then we'll we'll get them we'll get them in our next uh our next few episodes.
SPEAKER_01Yeah, absolutely. So until next week, same time, a new deal, and some fresh insights for myself and Graham.