Dylan Patel – Anthropic & OpenAI will have most of the world’s compute by 2028

**Dwarkesh Patel** (0:00)
Okay, I'm back with Dylan Patel, founder of Semi-Analysis. Our version of a family Thanksgiving dinner is a regular yearly podcast, but you're not actually related. Don't tell the people this, it will destroy the myth.
Basically, where the world economy is headed is more and more becoming a function of where like lab economics are headed, where like the compute market is headed, etc. So, I want to understand where the crazy future ends up within a few years. But let's start with just where we are today. So, walk me through lab compute and lab revenue right now, and maybe projecting out a year or two.

**Dylan Patel** (0:36)
Yeah. So, when we go back to last year, even at the end of the year, most of GDP growth in America was just AI infrastructure. As we look towards this year, about a third of the compute coming online is for the labs, for Open AI and Anthropic. Now, it may be built by others and then rented to them, but at the end customer, it's them. As we go forward into the future, the numbers for computer ballooning, we're at a little bit over a trillion dollars of CapEx this year. As we go out into 28, it's going to be more than two trillion dollars.
The labs are also taking an increasing percentage of this. So ultimately, you've got a very interesting situation where the labs are going from companies that spend tens of billions of dollars a year, to hundreds of billions of dollars a year, to forecasting to spend trillions of dollars a year even towards the end of the decade. This is at least some of the contracts they've begun signing with their partners. So this requires a big reshaping of what happens with their economics. So up until now, they have been companies that mostly lost money. Anthropic started turning a profit in Q2.
It's believed at some point in Q3, OpenAI could potentially start turning a profit even, with the big rise of Codex and 5.6 and all this. But if we go back a year ago, everything that they all the money they had was venture-funded losses, right? If we go back to even the beginning of this year, it was venture-funded losses. They've now turned the corner and are actually starting to profit. Now, that doesn't mean they're not taking a new capital. The new capital is still coming in to accelerate the growth further. But ultimately, there's more and more of their business is being funded off of their own revenue rather than capital injections into them. Over the last year and a half, their margins have really skyrocketed. The base cost of compute tends to be around 10 or 13 or 15 million dollars per megawatt. The most interesting aspect about what's happening now is, before, again, they were generating if they served a model, GPT-4 being served on NVIDIA Hopper GPUs was generating negative gross margin for OpenAI. But now, when OpenAI serves GPT-56 or Anthropic serves Opus 5 or Mythos, Fable 5, their revenue generation has passed well beyond the incremental 10, 15 million dollars per megawatt. In the case of Anthropic, the revenue has gone as high as 50 million dollars per megawatt.
And what that now enables them to do is, if I spend 10 bucks on inference capacity, actually generate 50 bucks of revenue, and then I can turn around and incrementally spend all of that profit on training.

**Dwarkesh Patel** (3:24)
One thing I'm very interested in understanding is how you see the centralization of compute happening in the labs, or the relative ratio of compute that goes to the world versus goes to the labs.
Where if you say right now, a third of marginal compute is going to the labs. By when is it over half of the incremental compute in the world is going to the labs? And by what point do the labs have basically a vast majority of the world's compute?

**Dylan Patel** (3:50)
Yeah, so earlier this year, you know, the beginning of this year, Anthropic OpenAI started at 2 for OpenAI and less than 2 for Anthropic. End of this year, they're both above 5 So they have 3, 4X compute as a whole.
When you look at the incremental compute added, that's about 30% of the compute added this year. And as we step forward to next year, given what's already been signed and penned and inked, you've got something even more dramatic, right? You've got Anthropic OpenAI are taking as much as 40-50% of compute next year. And this centralization doesn't look like it's slowing down or stopping. In fact, it looks like it's only accelerating. Now, who's building that compute for them will change.