HN Reader

It’s cute they describe this as a solution to _the_ power problem. It’s a solution to _their_ power problem. We have a grid problem. This massive amount of investment would be an incredible time to do something about it. Instead we’ve got an administration hostile to modern energy solutions and an industry hostile to everyone. Really depressing to see all this money go up in smoke in such a massive short sighted rush.

>>xAI entirely bypassed the grid and generated power onsite, using truck-mounted gas turbines and engines.

These generators polluted the nearby historically black neighborhoods in Memphis Tennessee with nitrogen oxides. Residents are afraid to open their windows, with the elderly, children and those suffering from conditions like COPD particularly affected. Lawsuits alleging environmental racism are pending.

xAI says cleaner generators will be installed but I think this episode shows that we cannot allow public interests to be compromised by private sector so easily just because they scream: Jobs! Investment!

https://time.com/7308925/elon-musk-memphis-ai-data-center/

Really cool in depth report, thanks for sharing. It's very interesting to see what these big datacenter deployments are actually doing. Go look at the oil price charts for the last 25 years and you'll see why it makes a ton of sense economically.

I also love how you can see the physical evidence of them pitting jurisdictions against each other from the satellite photos with the data center on one side of a state border and the power generation on the other.

I often like SemiAnalysis' work, but there's parts of this article that are shockingly under-researched and completely missing critical parts of the narrative.

> Eighteen months ago, Elon Musk shocked the datacenter industry by building a 100,000-GPU cluster in four months. Multiple innovations enabled this incredible achievement, but the energy strategy was the most impressive.

> Again, clever firms like xAI have found remedies. Elon's AI Lab even pioneered a new site selection process - building at the border of two states to maximize the odds of getting a permit early!

The energy strategy was to completely and almost certainly illegally bypass permitting and ignore the Clean Air Act, at a tangible cost to the surrounding community by measurably increasing respiratory irritants like NOx in the air around these communities. Characterizing this harm as "clever" is wildly irresponsible, and it's wild that the word "illegal" doesn't appear in the article once, while at the same time handwaving the fact that permitting for local combustion-based generation (for these reasons!) is one of the main factors to pushing out timelines and increasing cost.

[1] https://time.com/7308925/elon-musk-memphis-ai-data-center/

[2] https://www.selc.org/news/resistance-against-elon-musks-xai-...

[3] https://naacp.org/articles/elon-musks-xai-threatened-lawsuit...

There's not a single mention of pollution or clean energy or the environment in the entire article. Presumably the regulatory requirements for these generators are less stringent than for proper power plants, so the costs are pushed onto the rest of society (having to deal with the environmental impact) while Microsoft et al. keep the profits?

Does anyone know a really good source for basic information estimating what % of global carbon emissions come from AI training and AI inference, both 1) now and 2) in the future if we believe AI companies' capacity projections? I would really like to read a detailed analysis of this avoids both AI hype and anti-AI hysteria. It's an important question but it excites strong reactions that tend to cloud the facts.

Yes, all sources are biased, but some are useful. And I know that it's hard to get solid data on this from AI companies, but we must have at least a rough estimate?

Please don't tell me to ask ChatGPT about it :)

Kinda proving that these are a bad deal for communities - very few jobs and tax revenues, but enjoy the increased asthma and cancer we all get to pay for.

I previously worked directly for some of the power generation manufacturers listed in the article and later on the grid/power transmission side.

My takeaway is they get it correct enough but no deep insight on the power generation industry.

I was surprised by and learned a few things from the article though. Definitely gives me some ideas of reaching out to old contacts to see if there’s any opportunities with building models and analytics for the new demands.

Focusing on Bloom is fun because they’re new and startup vibes but Innio and cat are really having a resurgence of demand with their generators and building diesel/natg engines is much simpler than gas turbines. I’m sure the heads at GE wish they hadn’t sold that off now.

On steam/gas turbine blade manufacturing there most certainly are more big players than 4 and many US based. You have to remember this is an old industry with existing supply chains and maintenance companies.

As long as the demand for new data centers doesn’t lose steam these onsite options will continue to flourish. Fed grid access builds are currently a 10+ year wait and they are reworking the system to be “fast”, only 5-6 years for build outs now. They’re also changing how the bidding process works which was touched on here. You need skin in the game if you want to be taken seriously now. There’s so many requests from companies arbing who can give them the best deal/timeline. Now you need to put money up if you even want a call back.

The problem is that most of the AI labs are popping up in TX that has a uniquely isolated electrical grid. Recall how the Texas cold snap a few years ago took down the grid for days. Turns out if you make a grid based on short term profit motifs, it's not going to be flexible enough to take new demand.

It's not the grid's technological limitation. We could have lived in a world with a more connected grid, more nibble utility commissions, and a lot less methane/carbon emissions as a result of it

Our kids are not going to be happy we spun up more CO2 generation for this.

This is a really long way of saying "We need to burn fossil fuels to make more money."

It didn't make long-term sense for our world before AI. It makes no more sense with AI.

Part of what bothers me with AI energy consumption isn't just how wasteful it might be from an ecological perspective, it's how brutally inefficient it is compared to the biological "state of the art" — 2000kcal = 8,368 kJ. 8,368 kJ / 86,400 s = 96.9 W.

So the benchmark is achieving human-like intelligence on a 100W budget. I'd be very curious to see what can be achieved by AI targeting that power budget.

What about renewables + battery storage? Does it take much longer to build? I can imagine getting a permit can take quite a long time, but what takes so long to set up solar panels and link them to batteries, without even having to connect them to the grid?

Here's my guess: there are lots of datacenters being built in Virginia, Pennsylvania, Indiana, Ohio, Illinois [1]. Also in Texas, Georgia, Arizona, Nevada and Utah.

I think the first 5 states have this in common: there are lots of coal burning power plants that were shut down, but can be restarted and hooked to the grid on a relatively short notice. The grid is also quite good in this region.

In Texas, it is likely that new power can be generated with a combination of solar, wind, gas, and fast permitting.

I don't have an explanation for Georgia.

For Arizona, and perhaps Nevada and Utah too, I think it is likely to be solar.

[1] https://www.axios.com/2025/12/18/data-center-growth-map-stat...

So all the predictable arguments aside...

Why is no one talking about the "other grid" capacity here?

Natural gas at this scale cannot be delivered by truck. It's piped in direct from fields, typically.

When do we run out of natural gas "grid" capacity in these locations? I can't imagine we're that overbuilt compared to the electrical grid itself?

The big freeze in Texas is a recent example of the natural gas grid having localized "brownouts" due to a few factors - one of which being the demand of all the natural gas peakers trying to fire at once.

Seems like this is the next infrastructure piece to have a supply crunch to me? There are places (North Dakota) so contranstrained by capacity to deliver gas to the "grid" that they simply flare it off because it's cheaper to pay the government to do that vs. lay pipe. This implies to me that natural gas is about to become more valuable.

Title should be "AI labs are raping the planet"

I enjoyed the detailed article despite how depressing it is. I never can blame business for finding a market-palatable solution.

However, it is worth saying that xAI’s “solution” was illegal, unhealthy for the local constituents, and stinks of corruption, https://insideclimatenews.org/news/17072025/elon-musk-xai-da....

I think it's funny that at no point in the article do they mention the idea of simply making LLMs more efficient. I guess that's not important when all you care about is winning the AI "race" rather then selling a long term sustainable product.

... and, all this for what ?

the rather uninformed question I had: but answered in comments below

was why not solar ? Yeah Hydrocarbons have no competition if you have to deploy power quickly

1.2GW is a small turbine - compared to the land & battery needed for Solar.

how about Gas ? if you're building in the middle of nowhere ? & there's no gas lines ?

"xAI entirely bypassed the grid and generated power onsite, using truck-mounted gas turbines and engines."

So they solved the power problem by consuming more fossil fuel. Got it.

I found Boom's pivot much less confusing after this article.

> Eighteen months ago, Elon Musk shocked the datacenter industry by building a 100,000-GPU cluster in four months. Multiple innovations enabled this incredible achievement, but the energy strategy was the most impressive. xAI entirely bypassed the grid and generated power onsite, using truck-mounted gas turbines and engines.

Wow, "truck-mounted gas turbines"? Who else could have mastered such a futuristic tech in so short a time? Seriously, who wrote this? Grok? And let's ignore that this needless burning of fossil fuel is making life on Earth harder for everyone and everything else.

Interesting choice of names: "Solar Turbines" - a wholly owned Caterpillar subsidiary that designs and manufactures industrial gas turbines.

That said, it is all pretty impressive.

> However, AI infrastructure cannot wait for the grid’s multiyear transmission upgrades. An AI cloud can generate revenue of $10-12 billion dollars per gigawatt, annually. Getting a 400 MW datacenter online even six months earlier is worth billions. Economic need dwarfs problems like an overloaded electric grid. The industry is already searching for new solutions.

wow, that's some logic. Environmentally unsound means of extracting energy directly damage the ecosystem in which humans need to live. The need for a functioning ecosystem "dwarfs" "problems" like billionaires not making enough billions. Fixing a ruined ecosystem would cost many more billions than whatever economic revenue the AI generated while ruining it. So if you're not harnessing the sun or wind (forget about the latter in the US right now, btw), you're burning things, and you can get lost with that.

This kind of short sighted thinking is because when folks like this talk about generating billions of dollars of worth, their cerebellums are firing up as they think of themselves personally as billionaires, corrupting their overall thought processes. We really need to tax billionaires out of existence.

TL;DR by saying fuck environment

The dialog around AI resource use is frustratingly inane, because the benefits are never discussed in the same context.

LLMs/diffusers are inefficient from a traditional computing perspective, but they are also the most efficient technology humanity has created:

> AI systems (ChatGPT, BLOOM, DALL-E2, Midjourney) and human individuals performing equivalent writing and illustrating tasks. Our findings reveal that AI systems emit between 130 and 1500 times less CO2e per page of text generated compared to human writers, while AI illustration systems emit between 310 and 2900 times less CO2e per image than their human counterparts.

Source: https://www.nature.com/articles/s41598-024-54271-x

Isn't spinning up huge amounts of power on inefficient engines going to make climate impacts worse?

TLDR: They're not reducing power consumption, they're just also using gas now. Buckle up for higher prices, the AI slop factory needs more power.

Power problem: solved

Natural Gas supply problem: worsened

Carbon in the atmosphere problem: worsened

> An AI cloud can generate revenue of $10-12 billion dollars per gigawatt, annually.

Citation needed.

> Wärtsilä, historically a ship engine manufacturer, realized the same engines that power cruise ships can power large AI clusters. It has already signed 800MW of US datacenter contracts.

This seems like a big reach for me. Their largest engine (and it is absolutely massive) "only" produces 80MW of power. The Brayton cycle is unbeatable if you need to keep scaling power up to ridiculous levels.

Economic * need dwarfs problems like an overloaded electric grid.

*greed.

We are well past the point that any economic growth at all is anything but a distribution of income problem.