Kind of sad to see AI water use as the first listed issue motivating this.

It is a completely fake concern. See here: https://blog.andymasley.com/p/the-ai-water-issue-is-fake

There is so much nuance and context missing that I can't see this as anything other than astroturfing.

I can get behind "AI water use is not a serious concern" if all you are talking about is selling inference, and you're comparing some sort of usage metric (e.g. "water use per request"). Water and power use for inference is on the level of other heavy Internet products like video streaming or cloud compute.

There is a lot I can't ignore, though. Model training is incredibly demanding, so much that OpenAI was trying to get $1 trillion in investment to practically double the number of data centers in the United States by 2030. That is a serious concern when we have to make decisions between, say, consumer water availability and tech investment in water-scarce areas like Arizona and New Mexico.

In Oregon, there are some unique problems with Amazon's water deals in Umatilla, where they are increasing nitrate concentration of the local groundwater through evaporative cooling, and refusing to pay for on-site treatment.

I can go on about other environmental harms, but I think you should take a more nuanced look at the issue. Having ChatGPT summarize a news article is not an unreasonable demand compared to other compute activities, but AI in general is driving compute demand so high that the general public is forced to reckon with a problem that's been there since the beginning: the expansion, operation and use of the Internet has physical environmental consequences.

Okay. There are other criticisms of datacenter buildout that make this kind of product valuable. Moving on.