

Not even remotely close to this scale… At most you could compare the energy usage to the miners in the crypto craze, but I’m pretty sure that even that is just a tiny fraction of what’s going on right now.


Not even remotely close to this scale… At most you could compare the energy usage to the miners in the crypto craze, but I’m pretty sure that even that is just a tiny fraction of what’s going on right now.


That is the fallacious paper millionaire argument. They have more than enough liquidity, can take loans against their “non-liquid” wealth, and are anyway working with multi-year plans to sell assets and have enough liquidity. I believe this is also explained in https://mkorostoff.github.io/1-pixel-wealth/ and there they also explain that the US market cap is bigger than their stocks and so. So they could sell a lot in one go, of course losing “efficiency”, but the market would be able to cope without any issue.
I think we are on the same side here judging from the rest of your comment, but I find it important to refute this typical argument, because it does not help that there is some sort of billionaire apologism by saying that they “don’t actually have this money in their bank account to spend”.
From the blog you quoted yourself:
(And likewise, the last graph of predictions for 2028)
From a quick read of that source, it is unclear to me if it factors in the electricity cost of training the models. It seems to me that it doesn’t.
I found more information here: https://www.technologyreview.com/2025/05/20/1116327/ai-energy-usage-climate-footprint-big-tech/
So, I’m not sure if those numbers for 2023 paint the full picture. And adoption of AI-powered tools was definitely not as high in 2023 as it is nowadays. So I wouldn’t be surprised if those numbers were much higher than the reported 22.7% of the total server power usage in the US.