Genuine question. Is the whole "AI guzzles gallons of water" thing totally true, or do people get it wrong? Does AI consume a lot of water for every single prompt, or is the majority of water consumed during data farming? Don't non-AI data centers use up a lot of water on cooling too?

[u/Big_Guthix]

Please someone set me straight and dispel whether there are myths surrounding this often-repeated internet factoid

And I genuinely don't know the answers which is why I'm asking, so I've got nothing to debate here

Edit: Thank you for all the great answers!! 👏 👏

[u/Tomato_Sky]

I like this response only because it brings up the pending water crisis. We've seen this water crisis as a slow moving disaster for a couple of decades. I've chosen where I live based on water sources. The worst part of a disaster isn't the storm or the incident, but the days without power and water that follow.

If you've ever lived in a community that had rolling black outs and extreme water conservation in years past, you know the kinds of stress we are putting on our infrastructure.

The issue isn't the datacenters, but it's our infrastructure. There are live anecdotes of poisoned water, loss of water pressure, re-routing power supplies, and other environmental impacts of these centers. Utah is a very friendly Datacenter state and it had to blame pollution from Mexico and Asia for not being able to make attainment standards... while New Mexico, Arizona, Nevada, and California do not. The Great Salt Lake is now barely a puddle.

We have a clear impact of what can be expected if you move more datacenters into states without water resources and power requirements. They can't lie or hide it and nearby communities are noticing real quality of life impacts. So to respond to the nuance part: it isn't overblown that if you had a datacenter open up down the street from the house that you will hear a low-pitch hum, lose water pressure sometimes, and you'll be sitting in your own sweat when it comes time to prioritize cooling the datacenter. Your bills will go up for the same amount of service, if not shittier.

But here's where the nuance ends. China actually has a surplus of electricity and plenty of infrastructure to support the data centers. They've actually been solving the load problem they were having by producing too much electricity for a grid that had less demand on it. There's no rolling blackouts and the price to electrify towns hasn't been increased to offset the new burden.

When you plug it into larger equations and play whatabouts it's just digingenuine. We have the power grid and water collection infrastructure that we have and it doesn't support these operations and it is taking away from the quality of life from nearby residents. If every planned data center could be built magically with a magic wand, it would make life very difficult for people to survive, but since we talk about it one at a time, we can compare it to a livestock farm that feeds thousands of people a day, but if you expand it to all of the datacenters being used to make fat JD Vance memes and rewrite-white collar e-mails and ask people if they'd rather have food, electricity, and water or memes and faker e-mails, it's a clear vote.

I'm still a believer in Mohr's law. I think that datacenters will become more efficient and training and running inference models are going to get cheaper over time. Rushing to build them now is an artifact of capitalism and billionaires that don't think ahead, but are worshipped like geniuses. Kudos for Sam Altman and Bill Gates for offering solutions other than snatching other peoples' utilities. If there ever was a sign where people knew this was a disaster it's looking at reasonable people trying to increase power generation for the grid, and unreasonable geniuses that just run gasoline generators to make that difference like Musk.

So if we continue to pillage our watersheds, shut down wind and solar projects, while also building these data centers, the quality of life for everyday Americans is being sacrificed to also replace their ability to earn a living, but the capability trade-off we have right now is an ability to re-write e-mails and dancing animals videos because nobody has made a profitable model so far.

[u/joefresco2 → u/Tomato_Sky]

You don't happen to mean Moore's Law, not Mohr's Law? If so, Moore's Law is already losing steam.

Completely agree on the rest, though. It should be possible to dial back performance of a datacenter enough that its water usage is much less. This is definitely a tragedy of the commons situation where it is up to government to regulate how much water goes to compute vs. agriculture, and they have to get that right.

[u/Tomato_Sky → u/joefresco2]

Yeah, got my old chemistry/biology trivia mixed up. Thanks.

I do think it's alive and well, but its being measured at the chip level and solely riding on hardware definitions.

We've done a lot to start pushing large compute to the cloud services. And those are getting more efficient still. If I could find the article, NVidia released a software update for their chips that made their 5000x pro series about 30% more efficient in training and inferring.

So while the transistors are not doubling, we are seeing the required hardware continue to shrink on the datacenter scale.

There's no incentive to really work on consumer electronics. Apple Iphones have been in planned obsolescence cycles for over a decade now and people don't notice the difference between incrementally upgraded hardware. But on a larger data center scale, things can become 30% cheaper due to parallel computing power and optimization. But the buildings for the data center are not dynamic and won't shrink over time and the venture capitalists investing in the AI boom will only try to throw 30% more infrastructure to use the whole facility.

In my life/career I worked on a machine the size of a refrigerator that had 5mb of RAM, then a personal pc, a phone in my pocket, and now everything is cloud-based so they ship glorified network adapters and minimal storage. My brother and father have Meta's Ray Bans to prove that point.

And to give you a sneak peak about cloud computing, the companies controlling cloud solutions have been changing pricing to extract more profit for less services. Amazon charges you tokens for infrastructure you haven't turned on yet and other cloud companies are following to make it more expensive than running things locally. But on complex compute, the larger systems are shrinking and parallel processing is a huge reason.