I appreciate you taking the time to write up your thoughts on something other than exclusively these tools 'usefulness' at writing code.

> The capacity for AI to oppress you is in direct relation to its economic value.

I think this assumes a level of rationality in these systems, corporate interests and global markets, that I would push back on as being largely absent.

> The power hunger is in direct proportion to the demand.

Do you think this is entirely the case? I mean, I understand what you are saying, but I would draw stark lines between "company" demand versus "user" demand. I have found many times the 'AI' tools are being thrust into nearly everything regardless of user demand. Spinning its wheels to only ultimately cause frustration. [0]

> Is it what's emptying drinking water aquifers?

It appears this is a problem, and will only continue to be such. [1]

> The combined water usage of all data centers in Arizona. All of them. Together. Which is over 100 DCs. All of them combined use about double what Tesla was expecting from just the Brandenburg Gigafactory to use before Musk decided to burn his reputation with EV consumers and Europeans for political point scoring.

I am unsure if I am getting what your statements here are trying to say. Would you be able to restate this to be more explicit in what you are trying to communicate.

[0] https://news.ycombinator.com/item?id=46493506

[1] https://www.forbes.com/sites/cindygordon/2024/02/25/ai-is-ac...

> I think this assumes a level of rationality in these systems, corporate interests and global markets, that I would push back on as being largely absent.

Could be. What I hope and suspect is happening is that these companies are taking a real observation (the economic value that I also observe in software) and falsely expanding this to other domains.

Even to the extent that these work, AI has clearly been over-sold in humanoid robotics and self-driving systems, for example.

> Do you think this is entirely the case? I mean, I understand what you are saying, but I would draw stark lines between "company" demand versus "user" demand. I have found many times the 'AI' tools are being thrust into nearly everything regardless of user demand. Spinning its wheels to only ultimately cause frustration. [0]

I think it is. Companies setting silly goals like everyone must use LLMs once a day or whatever, that won't burn a lot of tokens. Claude Code is available in both subscription mode and PAYG mode, and the cost of subscriptions suggests it is burning millions of tokens a month for the basic subscription.

Other heavy users who we would both agree are bad, are slop content farms. I cannot even guesstimate those, so would be willing to accept the possibility they're huge.

> It appears this is a problem, and will only continue to be such. [1]

I find no reference to "aquifers" in that.

Where it says e.g. "up to 9 liters of water to evaporate per kWh of energy used", the average is 1.9 l/kWh. Also, evaporated water tends to fall nearby (on this scale) as rain, so unless there's now too much water on the surface, this isn't a net change even if it all comes form an aquifer (and I have yet to see any evidence of DCs going for that water source).

It says "The U.S. relies on water-intensive thermoelectric plants for electricity, indirectly increasing data centers' water footprint, with an average of 43.8L/kWh withdrawn for power generation." - most water withdrawn is returned, not consumed.

It says "Already AI's projected water usage could hit 6.6 billion m³ by 2027, signaling a need to tackle its water footprint.", this is less than the famously-a-desert that is Arizona.

> I am unsure if I am getting what your statements here are trying to say. Would you be able to restate this to be more explicit in what you are trying to communicate.

That the water consumption of data centres is much much smaller than the media would have you believe. It's more of a convenient scare story than a reality. If water is your principal concern, give up beef, dairy, cotton, rice, almonds, soy, biofuels, mining, paper, steel, cement, residential lawns, soft drinks, car washing, and hospitals, in approximately that order (assuming the lists I'm reading those from are not invented whole cloth), before you get to data centres.

And again, I don't disagree that they're a problem, it's just that the "water" part of the problem is so low down the list of things to worry about as to be a rounding error.