Readers: I’ve done a very generous “free” portion of this newsletter, but I do recommend paying for premium to get the in-depth analysis underpinning the intro. That being said, I want as many people as possible to get the general feel for this piece. Things are insane, and it’s time to be realistic about what the future actually looks like.
We’re in a bubble. Everybody says we’re in a bubble. You can’t say we’re not in a bubble anymore without sounding insane, because everybody is now talking about how OpenAI has promised everybody $1 trillion — something you could have read about two weeks ago on my premium newsletter.
Yet we live in a chaotic, insane world, where we can watch the news and hear hand-wringing over the fact that we’re in a bubble, read article after CEO after article after CEO after analyst after investor saying we’re in a bubble, yet the market continues to rip ever-upward on increasingly more-insane ideas, in part thanks to analysts that continue to ignore the very signs that they’re relied upon to read.
AMD and OpenAI signed a very strange deal where AMD will give OpenAI the chance to buy 160 million shares at a cent a piece, in tranches of indeterminate size, for every gigawatt of data centers OpenAI builds using AMD’s chips, adding that OpenAI has agreed to buy “six gigawatts of GPUs.”
This is a peculiar way to measure GPUs, which are traditionally measured in the price of each GPU, but nevertheless, these chips are going to be a mixture of AMD’s mi450 instinct GPUs — which we don’t know the specs of! — and its current generation mi350 GPUs, making the actual scale of these purchases a little difficult to grasp, though the Wall Street Journal says it would “result in tens of billions of dollars in new revenue” for AMD.
This AMD deal is weird, but one that’s rigged in favour of Lisa Su and AMD. OpenAI doesn’t get a dollar at any point - it has work out how to buy those GPUs and figure out how to build six further gigawatts of data centers on top of the 10GW of data centers it promised to build for NVIDIA and the seven-to-ten gigawatts that are allegedly being built for Stargate, bringing it to a total of somewhere between 23 and 26 gigawatts of data center capacity.
Hell, while we’re on the subject, has anyone thought about how difficult and expensive it is to build a data center?
Everybody is very casual with how they talk about Sam Altman’s theoretical promises of trillions of dollars of data center infrastructure, and I'm not sure anybody realizes how difficult even the very basics of this plan will be.
Nevertheless, everybody is happily publishing stories about how Stargate Abilene Texas — OpenAI’s massive data center with Oracle — is “open,” by which they mean two buildings, and I’m not even confident both of them are providing compute to OpenAI yet. There are six more of them that need to get built for this thing to start rocking at 1.2GW — even though it’s only 1.1GW according to my sources in Abilene.
But, hey, sorry — one minute — while we’re on that subject, did anybody visiting Abilene in the last week or so ever ask whether they’ll have enough power there?
Don’t worry, you don’t need to look. I’m sure you were just about to, but I did the hard work for you and read up on it, and it turns out that Stargate Abilene only has 200MW of power — a 200MW substation that, according to my sources, has only been built within the last couple of months, with 350MWs of gas turbine generators that connect to a natural gas power plant that might get built by the end of the year.
Said turbine is extremely expensive, featuring volatile pricing (for context, natural gas price volatility fell in Q2 2025…to 69% annualized) and even more volatile environmental consequences, and is, while permitted for it (this will download the PDF of the permit), impractical and expensive to use long-term.
Analyst James van Geelen, founder of Citrini Research recently said on Bloomberg’s Odd Lots podcast that these are “not the really good natural gas turbines” because the really good ones would take seven years to deliver due to a natural gas turbine shortage.
But they’re going to have to do. According to sources in Abilene, developer Lancium has only recently broken ground on the 1GW substation and five transformers OpenAI’s going to need to build out there, and based on my conversations with numerous analysts and researchers, it does not appear that Stargate Abilene will have sufficient power before the year 2027.
Then there’s the question of whether 1GW of power actually gets you 1GW of compute. This is something you never see addressed in the coverage of OpenAI’s various construction commitments, but it’s an important point to make. Analyst Daniel Bizo, Research Director at the Uptime Institute, explained that 1 gigawatt of power is only sufficient to power (roughly) 700 megawatts of data center capacity. We’ll get into the finer details of that later in this newsletter, but if we assume that ratio is accurate, we’re left with a troubling problem.
That figure represents a 1.43 PUE — Power Usage Effectiveness — and if we apply that to Stargate Abilene, we see that it needs at least 1.7GW of power, and currently only has 200MW.
As an aside, I need to clear something up, because everybody — including myself! — has been getting this wrong.
When you read “1.2GW data center,” they are almost certainly referring to the data center’s IT load — which is the power consumed by all of the computing equipment inside, but not the cooling systems or power lost in the infrastructure bringing the electricity to the gear itself. The amount of non-IT load power required, furthermore, can fluctuate.
Data centers need far more power than their IT load, and any time you read a “gigawatt” data center, know that they need about 30% more power than the amount of capacity the data center has.
Stargate Abilene does not have sufficient power to run at even half of its supposed IT load of 1.2GW, and at its present capacity — assuming that the gas turbines function at full power — can only hope to run 370MW to 460MW of IT load.
I’ve seen article after article about the gas turbines and their use of fracked gas — a disgusting and wasteful act typical of OpenAI — but nobody appears to have asked “how much power does a 1.2GW data center require?” and then chased it with “how much power does Stargate Abilene have?”
The answer is not enough, and the significance of said “not enough” is remarkable.
Today, I’m going to tell you, at length, how impossible the future of generative AI is.
What Makes a Gigawatt
Gigawatt data centers are a ridiculous pipe dream, one that runs face-first into the walls of reality.
The world’s governments and media have been far too cavalier with the term “gigawatt,” casually breezing by the fact that Altman’s plans require 17 or more nuclear reactors’ worth of power, as if building power is quick and easy and cheap and just happens.
I believe that many of you think that this is an issue of permitting — of simply throwing enough money at the problem — when we are in the midst of a shortage in the electrical grade steel and transformers required to expand America’s (and the world’s) power grid.
I realize it’s easy to get blinded by the constant drumbeat of “gargoyle-like tycoon cabal builds 1GW data center” and feel that they will simply overwhelm the problem with money, but no, I’m afraid that isn’t the case at all, and all of this is so silly, so ridiculous, so cartoonishly bad that it threatens even the seemingly-infinite wealth of Elon Musk, with xAI burning over a billion dollars a month and planning to spend tens of billions of dollars building the Colossus 2 data center, dragging two billion dollars from SpaceX in his desperate quest to burn as much money as possible for no reason.
This is the age of hubris — a time in which we are going to watch stupid, powerful and rich men fuck up their legacies by finding a technology so vulgar in its costs and mythical outcomes that it drives the avaricious insane and makes fools of them.
Or perhaps this is what happens when somebody believes they’ve found the ultimate con — the ability to become both the customer and the business, which is exactly what NVIDIA is doing to fund the chips behind Colossus 2.
According to Bloomberg, NVIDIA is creating a company — a “special purpose vehicle” — that it will invest $2 billion in, along with several other backers. Once that’s done, the special purpose vehicle will then use that equity to raise debt from banks, buy GPUs from NVIDIA, and then rent those GPUs to Elon Musk for five years.
Hell, why make it so complex? NVIDIA invested money in a company specifically built to buy chips from it, which then promptly handed the money back to NVIDIA along with a bunch of other money, and then whatever happened next is somebody else’s problem.
Right?
Actually, wait — how long do GPUs last, exactly? Four years for training? Three years? The A100 GPU started shipping in May 2020, and the H100 (and the Hopper GPU generation) entered full production in September 2022, meaning that we’re hurtling at speed toward the time in which we’re going to start seeing a remarkable amount of chips start wearing down, which should be a concern for companies like Microsoft, which bought 150,000 Hopper GPUs in 2023 and 485,000 of them in 2024.
Alright, let me just be blunt: the entire economy of debt around GPUs is insane.
Assuming these things don’t die within five years (their warranties generally end in three), their value absolutely will, as NVIDIA has committed to releasing a new AI chip every single year, likely with significant increases to power and power efficiency. At the end of the five year period, the Special Purpose Vehicle will be the proud owner of five-year-old chips that nobody is going to want to rent at the price that Elon Musk has been paying for the last five years. Don’t believe me? Take a look at the rental prices for H100 GPUs that went from $8-an-hour in 2023 to $2-an-hour in 2024, or the Silicon Data Indexes (aggregated realtime indexes of hourly prices) that show H100 rentals at around $2.14-an-hour and A100 rentals at a dollar-an-hour, with Vast.AI offering them at as little as $0.67 an hour.
This is, by the way, a problem that faces literally every data center being built in the world, and I feel insane talking about it. It feels like nobody is talking about how impossible and ridiculous all of this is. It’s one thing that OpenAI has promised one trillion dollars to people — it’s another that large swaths of that will be spent on hardware that will, by the end of these agreements, be half-obsolete and generating less revenue than ever.
Think about it. Let’s assume we live in a fantasy land where OpenAI is somehow able to pay Oracle $300 billion over 5 years — which, although the costs will almost certainly grow over time, and some of the payments are front-loaded, averages out to $5bn each month, which is a truly insane number that’s in excess of what Netflix makes in revenue.
Said money is paying for access to Blackwell GPUs, which will, by then, be at least two generations behind, with NVIDIA’s Vera Rubin GPUs due next year. What happens to that GPU infrastructure? Why would OpenAI continue to pay the same rental rate for five-year-old Blackwell GPUs?
All of these ludicrous investments are going into building data centers full of what will, at that point, be old tech.
Let me put it in simple terms: imagine you, for some reason, rented an M1 Mac when it was released in 2020, and your rental was done in 2025, when we’re onto the M4 series. Would you expect somebody to rent it at the same price? Or would they say “hey, wait a minute, for that price I could rent one of the newer generation ones.” And you’d be bloody right!
Now, I realize that $70,000 data center GPUs are a little different to laptops, but that only makes their decline in value more profound, especially considering the billions of dollars of infrastructure built around them.
And that’s the problem. Private equity firms are sinking $50 billion or more a quarter into theoretical data center projects full of what will be years-old GPU technology, despite the fact that there’s no real demand for generative AI compute, and that’s before you get to the grimmest fact of all: that even if you can build these data centers, it will take years and billions of dollars to deliver the power, if it’s even possible to do so.
Harvard economist Jason Furman estimates that data centers and software accounted for 92% of GDP growth in the first half of this year, in line with my conversation with economist Paul Kedrosky from a few months ago.
All of this money is being sunk into infrastructure for an “AI revolution” that doesn’t exist, as every single AI company is unprofitable, with pathetic revenues ($61 billion or so if you include CoreWeave and Lambda, both of which are being handed money by NVIDIA), impossible-to-control costs that have only ever increased, and no ability to replace labor at scale (and especially not software engineers).
OpenAI needs more than a trillion dollars to pay its massive cloud compute bills and build 27 gigawatts of data centers, and to get there, it needs to start making incredible amounts of money, a job that’s been mostly handed to Fidji Simo, OpenAI’s new CEO of Applications, who is solely responsible for turning a company that loses billions of dollars into one that makes $200 billion in 2030 with $38 billion in profit. She’s been set up to fail, and I’m going to explain why.
In fact, today I’m going to explain to you how impossible all of this is — not just expensive, not just silly, but actively impossible within any of the timelines set.
Stargate will not have the power it needs before the middle of 2026 — the beginning of Oracle’s fiscal year 2027, when OpenAI has to pay it $30 billion for compute — or, according to The Information, choose to walk away if the capacity isn’t complete. And based on my research, analysis and discussions with power and data center analysts, gigawatt data centers are, by and large, a pipedream, with their associated power infrastructure taking two to four years, and that’s if everything goes smoothly.
OpenAI cannot build a gigawatt of data centers for AMD by the “second half of 2026.” It haven’t even announced the financing, let alone where the data center might be, and until it does that it’s impossible to plan the power, which in and of itself takes months before you even start building.
Every promise you’re reading in the news is impossible. Nobody has even built a gigawatt data center, and more than likely nobody ever will. Stargate Abilene isn’t going to be ready in 2026, won’t have sufficient power until at best 2027, and based on the conversations I’ve had it’s very unlikely it will build that gigawatt substation before the year 2028.
In fact, let me put it a little simpler: all of those data center deals you’ve seen announced are basically bullshit. Even if they get the permits and the money, there are massive physical challenges that cannot be resolved by simply throwing money at them.
Today I’m going to tell you a story of chaos, hubris and fantastical thinking. I want you to come away from this with a full picture of how ridiculous the promises are, and that’s before you get to the cold hard reality that AI fucking sucks.