Chapter 1: What are the current challenges facing AI data center build-outs?
Today's number? 400. That's how many meters long the world's largest ever tiramisu was, a record set last week by a consortium of 100 Italian chefs. Italy still faces severe economic challenges such as crippling debt and a stagnant economy, but points for sticking with the whole food thing. Welcome to Fraughty Markets. I'm Ed Elson. Apologies to our Italian listeners. It is April 29th.
Let's check in on yesterday's market vitals. The S&P and NASDAQ both fell due to a Wall Street Journal report that OpenAI missed its revenue and user growth targets. That news sparked a tech selloff with Nvidia falling more than 1% and Oracle and CoreWeave dropping 4%. Notably, Microsoft actually rose 1% ahead of its earnings, which are due tonight.
Meanwhile, oil prices rose as negotiations with Iran continued to stall and the Strait of Hormuz remained shut. And finally, the United Arab Emirates announced it is leaving OPEC, putting more pressure on the oil cartel's already strained supply. Okay, what else is happening?
Chapter 2: How is energy becoming a bottleneck for AI development?
Alphabet, Amazon, Meta, and Microsoft are expected to spend more than $650 billion this year on data centers. And by 2030, data centers are expected to use twice as much electricity as they do today, enough to power France and Germany combined. The problem, though, is that the grid might not be able to handle it.
Nearly 2,300 gigawatts of generation and storage capacity are currently stuck in the pipeline, more than the country's entire installed power capacity. Meanwhile, Americans are already seeing their power bills climb. In fact, residential prices could rise 15 to 40 percent over the next five years. As a result, 14 states are considering moratoriums on data centers.
So this leaves us with a multi-trillion dollar question. And that is, can the AI build-out actually happen the way Wall Street hoped that it would? To discuss this, we're joined by a panel of experts, Jigar Shah, former director of the Loan Programs Office at the US Department of Energy, and also John Perrella, CEO at Terraflow Energy. Jigar and John, thank you so much for joining me.
Jigar, I'll start with you. When you look at the AI build-out right now and sort of the obstacles that are in its way between compute, between people's feelings and political sentiment towards the technology, and then also energy, what do you consider to be the most important obstacle, the thing that's most in its way?
Yeah, you know, it's such a crazy thing, right?
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Chapter 3: What solutions are proposed to manage power infrastructure for data centers?
You know, when you think about the five different bottlenecks you have to data centers, right? So there's the grid, right? Then there's transformers, then there's GPUs, then there's memory, and then there's CPUs now. It looks like they're short, right?
Right.
They can't build more than 50 gigawatts of data centers between now and 2030 because of limitations on GPUs, memory, and CPUs. But if you go to communities, they're creating havoc at the level of 500 gigawatts across the country. So they are making empty promises to people across the country to disrupt their communities when they don't have the GPUs to fill it.
And so that's, I think, what's pissing everybody off. I think people are just saying, if you're going to be a trillion dollars in size and you're going to be booing the entire U.S. economy, how come not a single analyst actually seems to know anything about what's possible? And everyone else is basically like feeding the hype cycle all day. I'll give you an example. In the state of Texas...
They are suggesting on official ERCOT letterhead, which is the transmission operator in Texas, that the load queue could be 300 gigawatts, right?
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Chapter 4: How do data centers impact local communities and energy costs?
Now, mind you, Texas is 70 gigawatts. That's a BS number, right? And of course, people in Texas are scared out of their minds around a BS number. But what's likely to happen in Texas? 30 gigawatts.
Right. Yeah, John, I mean, this is coinciding, this conversation, with some pretty significant news about OpenAI, which is that OpenAI missed its revenue targets last year, reportedly. Same with its user targets. And it reminds me of a lot of the promises that they have also been making. My understanding is that they were going to build 30 gigawatts worth of compute by the year 2030.
I think they've built, I want to say two gigawatts so far. I mean, the point being, it seems like that company specifically is probably guilty in particular, of this over-promise, under-delivered dynamic that Jigar is talking about? I wonder if you have any thoughts on that.
Chapter 5: What role does government regulation play in data center operations?
So, I don't know that I quite agree with Jigar on 30 gigawatts. I think it's going to be a little bit more than that. We're working on quite a few of those projects in Texas. And I don't know that I would put all the blame necessarily on OpenAI. I used to work for Lancium. That was the base land and power for the Stargate One project.
I did a lot of work on that project before we knew it was going to be Stargate One. And in going back and looking at it, they've had a lot of issues because a lot of these companies, when they applied for their grid interconnect, they applied as if they were like Bitcoin mine or traditional data centers that were very flat, stable loads. Right.
If you actually start to look at the load profile of an AI data center, it's one of the most volatile loads you've ever seen. 12, 14 times a minute load swings that are 30, 80 percent the size of the data center. And that's wreaked havoc on these data centers moving quickly because it's tearing up gen sets. They're literally breaking the crankshaft of the gen sets.
They're burning through batteries. And it's devastating.
Chapter 6: How does the volatility of AI data centers affect grid stability?
A lot of these data centers that are all about time to power and moving quickly, and they got ahead of the tips of their skis because they didn't architect the infrastructure correctly for it to succeed.
And so I know that even the Stargate project has had a lot of problems where the utility turned them back off, and they've had to scramble to try and find equipment to be able to try and solve for these problems and get them stable loads. I don't know that I would necessarily blame everything.
It was definitely ambitious on their part to be able to say that they were going to scale that big that fast. I think in a lot of ways they had to do that in order to get capital to be able to start scaling. But I think that they've also been hit by a lot of roadblocks where interconnection takes a lot longer than anticipated because these loads are big and complex. And I think that
When they actually started turning these things on, what they expected and what actually happened were different and that they started breaking equipment and finding replacements for the broken equipment is not easy right now. So it just it's a whole cluster, if you will, of problems.
So while I do believe that they were a little overambitious, I do not believe that I would blame them 100 percent.
It seems like a four-letter word that's after the word cluster.
Yeah, well, I didn't want to quite go there, but you're welcome. Someone can do it. Someone can break the ice.
Well, John, I guess— Just trying to be a little bit more family-friendly.
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Chapter 7: What future trends are emerging in the data center industry?
Clusterfuck, I said it. Okay. Yeah, there you go. All right. So, I guess, John, I mean, it sounds like what— you and Jigar both agree that this is a lot more difficult than AI companies and investors had anticipated. It sounds like maybe where you may disagree is the extent to which they underestimated things or the extent to which they misjudged it.
I guess my follow-up question to you, John, is, I mean, how bad is it really When we look at what's happening from Wall Street's perspective, for example, I don't think Wall Street is as clued into what is happening on the ground when it comes to energy and compute capacity constraints as you are. So, I mean, how big of a problem is it really if it's not quite as big as Jigga might be suggesting?
So, I mean, I definitely think that power is the number one issue. There's no question about it. The thing that everybody's talking about is how long it takes to interconnect. Nobody's talking about what happens when you actually turn them on. And I think that obviously, as you see, buying generators, there's a long lead time on getting gen sets.
Chapter 8: What is the overarching conclusion about the future of energy and data centers?
And you're seeing some deals come and some deals go. What you're seeing, it was no different before data centers were here. It was the battery craze, right? Like interconnection queue for people that went and had land and they could get power on land to interconnect and put a battery in.
You know, it was like half the projects would never see the light of day, but everybody was connecting because if they could get the power to it, they could then flip it to a developer that would build it. I think you're seeing a very similar trend.
At least we've seen this where lots of people that have, you know, rural lands and there's also the big power line that comes through their land go, I can build a data center here. And, you know, they might have been able to get $5,000 or $10,000 an acre. But if they can get a large load interconnect, they can get $100,000, $200,000, $300,000 an acre for the same land.
So you see a lot of people that came in and said, OK, if I can find the sweet spot of land where I can get gas and water and power and all these things, all of a sudden the value of that land goes through the roof and the data centers are willing to pay for it. What's funny, though, is when you start looking at
What they submitted as their load profile for those interconnects versus what the data centers are actually doing. And so the problem is now the utilities are trying to do these feasibility studies off of a legacy flat, very stable data center. And then these things show up and it's far from that. And that's, I mean, to be a little bit selfish, that's what our battery technology solves for.
Yeah. But it is a major problem. And the reality is, you know, even if I stand up gigawatts of manufacturing capacity of batteries, I can't make enough. Yeah. And that's the problem across the board with all of the infrastructure companies.
Back when the Bitcoin mine days were here and it was all the craze of building these monster Bitcoin mining data centers, you saw companies investing in, you know, PDU manufacturers and all the components because they wanted to prioritize their company over everybody else to be able to get the components. Same thing's happening with the data centers.
The infrastructure funds, if you look at the Blackstones, are investing in... TDSPs or utilities. They're investing in the land developers. They're investing in the infrastructure components. They're investing in all the different components to be able to try and prop up and accelerate the growth of all this to meet that demand.
So, Jigar, I mean, when I kind of synthesize what's happening here, what we're basically saying is these data centers are a lot more volatile than we had originally expected. They're also consuming huge amounts of energy to a degree that people a few years ago would never have anticipated. And at the same time, I also know that the Strait of Hormuz is closed and blockaded as we speak.
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