This is an automated archive made by the Lemmit Bot.
The original was posted on /r/collapse by /u/Cs1mp3x on 2025-11-10 15:30:34+00:00.
Okay, hear me out. This is pure speculation, but I’ve been following the AI boom and energy news, and there’s a pattern here that’s honestly kind of wild when you connect the dots.
The Setup:
Right now, the US is going absolutely balls-to-the-wall on AI infrastructure. Massive investments. US data centers hit 183 terawatt-hours of electricity in 2024, and projections say that’ll jump to 426 TWh by 2030 [1]. That’s more than the entire country of Pakistan uses.
And here’s the kicker - to power all this, they’re doubling down on natural gas. Over 40% of US data center electricity already comes from gas, and that number’s climbing fast [2]. Companies are literally building 30-year natural gas plants specifically for data centers [3]. Microsoft, Google, Meta - all in on this.
The Chinese Wildcard:
While the US is spending hundreds of billions building energy-hungry infrastructure, China just casually dropped DeepSeek. And apparently this thing runs on 10 to 40 times less energy than comparable US models [4].
Let me repeat that. 10 to 40 times less energy.
Their electricity costs are also half what the US pays ($0.08/kWh vs $0.18/kWh) [4]. Meanwhile, China added 278 gigawatts of solar in 2024 alone [5]. For context, that’s more solar than most countries have total. They’re also pushing this “East Data, West Computing” thing - basically moving data centers to regions with cheap renewable energy and favorable climates [6].
The Investment Trap:
The AI bubble is massive. Tech companies invested $750 billion in data centers in 2024-2025, with plans for $3 trillion more through 2029 [7]. AI capital spending literally contributed more to US GDP growth than consumer spending recently [8].
But - and this is important - 95% of generative AI projects are failing to increase revenue [7]. The industry would need to generate $2 trillion annually by 2030 to justify current costs. Current AI revenue? About $20 billion [9].
That’s… not great math.
So here’s where this gets interesting:
The US is locked into expensive, fossil-fuel dependent AI infrastructure with 30-year lifespans. China’s developing dramatically more efficient models at lower cost. There’s a potential AI bubble that makes dot-com look tame. And natural gas plants being built now that’ll lock the US into emissions for decades.
There’s also been noise about the petrodollar stuff - Saudi Arabia diversifying away from dollar-only oil sales [10][11]. No formal agreement ever existed (common misconception), but the trend toward multi-currency energy trading is real. Plus the US isn’t even dependent on Middle Eastern oil anymore thanks to shale. They’re the world’s largest producer now.
My theory:
What if the US bet everything on the wrong AI architecture at exactly the wrong moment?
Think about it. If energy efficiency becomes the determining factor in AI competition (which it’s starting to look like), and if the AI bubble pops hard (which analysts are increasingly worried about), the US could see:
- Massive stranded assets. All those gas-powered data centers become economic dead weight
- Loss of tech competitive advantage to more efficient systems
- Fiscal pressure as the “AI stimulus” evaporates
- Energy costs that can’t compete globally
The ironic twist? This might force the fastest energy transition in history, but through economic pain rather than planning. When those gas plants become economically unviable, when the AI infrastructure needs to be rebuilt around efficiency rather than raw power, the competitive pressure could drive renewable adoption faster than any climate agreement.
China’s basically showing the blueprint: efficient models + cheap renewables + strategic infrastructure placement. They’re generating over 10,000 TWh annually now - more than the US, EU, and India combined [12]. And they’re positioning themselves to meet all their electricity demand growth through 2026 with renewables and nuclear [13].
The thing is:
I’m not saying this is some coordinated plan. It’s not conspiracy, and it’s not coincidence. It’s more like… emergent complexity? Multiple actors pursuing their own rational interests, creating unpredictable system-wide effects nobody planned for.
The US tech sector is providing massive private stimulus while potentially building infrastructure that’ll be obsolete before it breaks even. That’s not sustainable. When the correction comes - and with AI companies losing billions while scrambling for revenue, it seems increasingly likely - it could reshape everything.
Where this could go:
Best case? Competitive pressure forces rapid adaptation and innovation. The US figures it out.
Worst case? The US is left with hundreds of billions in stranded fossil fuel assets right as the global economy shifts toward efficiency-first computing.
Either way, the next 5-10 years are going to be absolutely wild. We’re either watching the birth of a new economic order or the setup for one of the biggest market corrections in history.
Possibly both.
What do you think? Am I connecting dots that aren’t there, or is there something to this?
Sources:
[2] https://www.iea.org/reports/energy-and-ai/energy-supply-for-ai
[3] https://www.technologyreview.com/2025/05/20/1116272/ai-natural-gas-data-centers-energy-power-plants/
[4] https://thediplomat.com/2025/02/chinas-overlooked-ai-energy-edge-over-the-us-cheaper-energy/
[5] https://ember-energy.org/latest-insights/powering-chinas-new-era-of-green-electrification/
[6] https://dialogue.earth/en/energy/is-chinas-energy-system-ready-for-the-ai-boom/
[8] https://www.bloodinthemachine.com/p/the-ai-bubble-is-so-big-its-propping
[10] https://www.atlanticcouncil.org/blogs/econographics/is-the-end-of-the-petrodollar-near/
[13] https://energytracker.asia/energy-transition-in-asia-pacific/