> What I'm saying is that using gigawatts of power for "AI" in this day and age is madness
Why? American datacentres--of all types--use about 250 TWh per year, with another 500 TWh additional capacity expected by 2030 [1]. American paper manufacturing used about that much energy in 2018 [2].
If I read the data right (1) the US currently produces roughly 4,000 TWh of electricity every year. 500 TWh is a significant portion of that! The US will need a lot of additional capacity for things like electric cars and heat pumps. Most of the effort should be going towards that, not huge data centers attending to unproven demand (how many people will pay the real price for ChatGPT once the VC subsidy ends remains to be proven).
The sources for some of the future data centers will be local and not necessarily influence the US grid. Consider also that cement production uses about 3000 TWh per year worldwide, and aluminium smelting uses about 1000 TWh per year.
A lot of that cement production still uses fossil fuels.
In my mind, all the electricity production capacity we can build needs to go to the electrification of the existing economy, not new stuff and especially not the current brand of AI.
The US electricity grid is a complex problem at the interface of state and local governments and cannot scale quickly. There are no major concerns with scaling up the local electricity production however, other than the installation time (and safety, if nuclear). Reliability is easier to solve locally than for a huge grid.
How? Also, why? Why are datacentres the use to tamp down on versus other industrial and commercial uses?
This reminds me of California rationing residential water use so alfalfa farmers can flood their fields.