#aidatacenters — Public Fediverse posts
Live and recent posts from across the Fediverse tagged #aidatacenters, aggregated by home.social.
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Um... ☢️
A #Michigan #NuclearPlant shut down for good is being switched back on for #AI power
Story by Everett Sloane, September 6, 2026
"A nuclear plant on the shore of Lake Michigan that shut down for good four years ago is now weeks or months away from producing electricity again, in what would be the first time in American history a retired commercial reactor has been brought back online. #Palisades #Nuclear Generating Station, in #CovertTownship, Michigan, ceased operating in 2022 after Entergy concluded it no longer made economic sense to keep running. Its new owner, #HoltecInternational, is now racing to restart it, betting that the same wave of electricity demand from artificial intelligence #datacenters reshaping the U.S. power grid can justify resurrecting a plant that was, until recently, on a path toward permanent teardown. The attempt is being closely watched across the utility industry because more than a dozen other reactors were permanently retired nationwide over the past decade, and each one is a potential candidate for the same kind of revival if Palisades proves it can be done safely and on budget."
#AISucks #AIDatacenters #NoNukesForAI #NoNukes #Holtec #PalisadesNuclearPlant #PalisadesNPP #WaterIsLife #LakeMichigan #RethinkNotRestart #AIBoom 💥
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Um... ☢️
A #Michigan #NuclearPlant shut down for good is being switched back on for #AI power
Story by Everett Sloane, September 6, 2026
"A nuclear plant on the shore of Lake Michigan that shut down for good four years ago is now weeks or months away from producing electricity again, in what would be the first time in American history a retired commercial reactor has been brought back online. #Palisades #Nuclear Generating Station, in #CovertTownship, Michigan, ceased operating in 2022 after Entergy concluded it no longer made economic sense to keep running. Its new owner, #HoltecInternational, is now racing to restart it, betting that the same wave of electricity demand from artificial intelligence #datacenters reshaping the U.S. power grid can justify resurrecting a plant that was, until recently, on a path toward permanent teardown. The attempt is being closely watched across the utility industry because more than a dozen other reactors were permanently retired nationwide over the past decade, and each one is a potential candidate for the same kind of revival if Palisades proves it can be done safely and on budget."
#AISucks #AIDatacenters #NoNukesForAI #NoNukes #Holtec #PalisadesNuclearPlant #PalisadesNPP #WaterIsLife #LakeMichigan #RethinkNotRestart #AIBoom 💥
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Um... ☢️
A #Michigan #NuclearPlant shut down for good is being switched back on for #AI power
Story by Everett Sloane, September 6, 2026
"A nuclear plant on the shore of Lake Michigan that shut down for good four years ago is now weeks or months away from producing electricity again, in what would be the first time in American history a retired commercial reactor has been brought back online. #Palisades #Nuclear Generating Station, in #CovertTownship, Michigan, ceased operating in 2022 after Entergy concluded it no longer made economic sense to keep running. Its new owner, #HoltecInternational, is now racing to restart it, betting that the same wave of electricity demand from artificial intelligence #datacenters reshaping the U.S. power grid can justify resurrecting a plant that was, until recently, on a path toward permanent teardown. The attempt is being closely watched across the utility industry because more than a dozen other reactors were permanently retired nationwide over the past decade, and each one is a potential candidate for the same kind of revival if Palisades proves it can be done safely and on budget."
#AISucks #AIDatacenters #NoNukesForAI #NoNukes #Holtec #PalisadesNuclearPlant #PalisadesNPP #WaterIsLife #LakeMichigan #RethinkNotRestart #AIBoom 💥
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Um... ☢️
A #Michigan #NuclearPlant shut down for good is being switched back on for #AI power
Story by Everett Sloane, September 6, 2026
"A nuclear plant on the shore of Lake Michigan that shut down for good four years ago is now weeks or months away from producing electricity again, in what would be the first time in American history a retired commercial reactor has been brought back online. #Palisades #Nuclear Generating Station, in #CovertTownship, Michigan, ceased operating in 2022 after Entergy concluded it no longer made economic sense to keep running. Its new owner, #HoltecInternational, is now racing to restart it, betting that the same wave of electricity demand from artificial intelligence #datacenters reshaping the U.S. power grid can justify resurrecting a plant that was, until recently, on a path toward permanent teardown. The attempt is being closely watched across the utility industry because more than a dozen other reactors were permanently retired nationwide over the past decade, and each one is a potential candidate for the same kind of revival if Palisades proves it can be done safely and on budget."
#AISucks #AIDatacenters #NoNukesForAI #NoNukes #Holtec #PalisadesNuclearPlant #PalisadesNPP #WaterIsLife #LakeMichigan #RethinkNotRestart #AIBoom 💥
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Um... ☢️
A #Michigan #NuclearPlant shut down for good is being switched back on for #AI power
Story by Everett Sloane, September 6, 2026
"A nuclear plant on the shore of Lake Michigan that shut down for good four years ago is now weeks or months away from producing electricity again, in what would be the first time in American history a retired commercial reactor has been brought back online. #Palisades #Nuclear Generating Station, in #CovertTownship, Michigan, ceased operating in 2022 after Entergy concluded it no longer made economic sense to keep running. Its new owner, #HoltecInternational, is now racing to restart it, betting that the same wave of electricity demand from artificial intelligence #datacenters reshaping the U.S. power grid can justify resurrecting a plant that was, until recently, on a path toward permanent teardown. The attempt is being closely watched across the utility industry because more than a dozen other reactors were permanently retired nationwide over the past decade, and each one is a potential candidate for the same kind of revival if Palisades proves it can be done safely and on budget."
#AISucks #AIDatacenters #NoNukesForAI #NoNukes #Holtec #PalisadesNuclearPlant #PalisadesNPP #WaterIsLife #LakeMichigan #RethinkNotRestart #AIBoom 💥
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#GorhamME officials consider permanent ban on #Datacenters
Several cities and towns in Maine already have moratoriums on data centers, and others are looking to do the same.
by WGME Staff, Fri, September 4, 2026
GORHAM (WGME) -- "The Town of Gorham is considering a permanent ban on data centers.
"The town already passed a moratorium in June, temporarily banning them.
"On Tuesday, town councilors voted unanimously to have the planning board schedule a public hearing and find out if the ban should become permanent.
"Before the ban could go into effect, the planning board will need to vote to change the town's land use and development code."
Read more:
https://wgme.com/news/local/gorham-officials-consider-permanent-ban-on-data-centers-maine-economy#MainePol #DatacenterMoratorium #DatacenterMoratoriums #Datacentres #DatacentreMoratorium #Hyperscale #Hyperconsumption #AIDatacenters #NoisePollution #LightPollution #WaterIsLife #EnergyWaste
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#Texas Gov. #GregAbbott on #AIDataCenter Backlash: 'They Dug Their Own Grave'
Jennifer Oliver O'Connell, August 23, 2026
"#NewYork Gov. #KathyHochul (D) and #Kentucky Gov. #AndyBeshear (D) have pushed back against the expansion of #AIDataCenters in their respective states. But with the increasing backlash from communities and individuals toward new #datacenter construction and expansion, even governors that have embraced the #AIRevolution, like #Pennsylvania's #JoshShapiro (D), are now moderating and talking about scaling back.
"Texas Gov. Greg Abbott (R) is one governor whose state has embraced the data center expansion. In November 2025, Abbott declared that Texas is the 'epicenter of AI development' in his announcement of #Google building three data center campuses to the tune of $40 million dollars.
"Fast forward to August of 2026, and Abbott acknowledges that much of the community resistance to the construction of new and existing data centers is the fault of the AI companies."
[...]
"Abbott is not wrong. According to a report from #DataCenterWatch, 64 billion in data center projects have been blocked or delayed in #Arizona, #Utah, #Missouri, #Oregon, and #California, to name a few. Even formerly friendly #Virginia is pushing back. #CommunityOpposition surrounds the lack of information provided and the lack of accountability taken towards the citizens who will be most affected.
"Water and power concerns loom large. Many of the newer development concepts, like entrepreneur #KevinOLeary 's 9 megawatt #StratosProject in #Utah, will have their own self-sustaining water and power systems. However, this did not prevent the backlash by #environmentalists and local activists to shut the Stratos Project down, and Utah state lawmakers ultimately backpedaled from their original approval and requested O'Leary cut the project's 400,000-acre footprint down to 10,000, about 75 percent. "
#AISucks #AIDataCenters #AIResistance #USPol #WorldPol #Datacenters #Datacentres #AIDatacentres #WaterIsLife #NoisePollution #LandIsLife #EnergyConsumption
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#SamAltman and others at #OpenAI are trying wicked hard to convince folks that they're all about saving #Nature... Buying #JackieAndShadow's home and now this... Um, sorry Sam and friends. It doesn't make up for the #NoisePollution, #WaterPollution, pollution from #EnergyConsumption , etc. for the #AIHouseOfCards... But folks are seeing right through that!
#OpenAI flew influencers to a #NatureResort to fix its image. The internet called it #greenwashing.
OpenAI flew a group of influencers to a $2,000-a-night wellness resort to warm up the public mood around #AI. Days before a reported $500bn #Datacentre deal, the internet called it greenwashing, and the creators got the backlash.
August 4, 2026
"The event, branded 'Summer Camp,' ran at Wildflower Farms, a resort in New York’s #HudsonValley where rooms can top $2,000 a night, Business Insider reported. Creators posted farm-to-table dinners under bistro lights, a beekeeping session, and classes on OpenAI’s tools. They went home with branded canvas bags and jars of honey.
"The videos were soft-focus and lighthearted. The comments were not. Across TikTok, Reddit, X and Instagram, people called the trip 'dystopian' and accused OpenAI of greenwashing. One commenter told TechCrunch the issue was timing: '#TheWorldIsOnFire. It’s not a great time to brag about your $5,000-a-night suite.' "
Read more:
https://thenextweb.com/news/openai-summer-camp-influencer-retreat-greenwashing-backlash#NoDatacenters #TheWorldIsBurning #USPol #AISucks #BigPower #BigData #ResistDataCenters #PowerCorruptionAndLies #AIDatacenters
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#AIIndustry to world: 'Somebody stop us'
Story by John Herrman, July 30, 2026
"More than 1,200 employees at AI firms, including top executives at #OpenAI, #Anthropic, #Meta, and #Google, have signed on to a statement calling for an 'option to buy time to address emerging risks, develop security measures, and strengthen oversight' in the face of 'a real risk that capability development rapidly accelerates beyond our ability to understand or control the resulting systems.' AI could 'help create a dramatically better future, but that outcome is not guaranteed,' they say. Companies and countries are under 'intense competitive pressure' not to slow things down unilaterally, the statement says, and the world currently lacks 'the technical and governance tools to deliberately pace fronter-wide progress.' "
https://www.msn.com/en-us/news/other/ai-industry-to-world-somebody-stop-us/ar-AA294Fpu
Archived version:
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#Mississippi homeowners blame a noisy #DataCenter plant for sleepless nights. The mayor's advice? "Consider selling."
By Lauren Fichten, July 16, 2026
"It was 4 a.m. on a Sunday and 46-year-old Jason Haley was once again wide awake.
"The suburban silence that Haley had grown used to in his two decades as a resident of #SouthavenMS, had, for the last few months, been replaced by a constant whirring, like an airplane hovering over his home, he said.
"The noise keeping Haley awake was coming from a plant powering #ElonMusk's #xAI #datacenters in the area, according to a lawsuit filed in June against the company and its subsidiary, #MZXTech. Haley and two other #Southaven residents, who live within a mile of the plant, allege in the suit that 'near-constant' noise and vibrations are causing negative physical and psychological health effects.
"The filing comes amid growing #resistance toward data center development, with the majority of Americans opposing local construction of a data center, according to a Gallup poll published earlier this year.
"Similar disputes are playing out across the country, like in #MountPleasantWI, where a lawsuit this month filed by residents alleges a data center emits 'unreasonable and excessive noise' onto residents' properties and in #LowellMA [a city with a large #Latino population -- #EnvironmentalRacism], where noise from a data center's cooling center 'disrupts neighbors' sleep,' according to an April suit.
"There are more than 4,000 data centers in the U.S., according to a recent United Nations report. To power the data centers, developers are building their own plants, sometimes with little warning to residents like Haley.
"Haley reached out to Southaven Mayor Darren Musselwhite about the noise in emails he shared with CBS News. In one last November, he urged Musselwhite to drive through the neighborhood 'and take a listen to the constant #HighPitch noises.' "
" 'I am aware of the noise and working on a solution with xAI officials,' Musselwhite had responded to Haley an hour later. 'It is a problem,' he said in another email later in the day.
"But soon, another sleepless night rolled around and Haley was emailing the mayor again.
""Anyone else I can reach out to?" Haley wrote to Musselwhite. "It's almost 4 am and I can hear it from my bed. The high pitch and roaring combined is full force at this time. My ears are ringing. I can't live in this. How was this ever approved?"
[In a later email, this was Musselwhite's response] "I know they want houses for employees, so you may want to consider selling your home." 😡
Read more:
https://www.cbsnews.com/news/mississippi-elon-musk-xai-data-center-power-plant-noise/#ElonSucks #BigDataSucks #NoisePollution #BigData
#CorporateColonialism #WaterIsLife #LandIsLife #AirIsLife #USPol
#AISucks #DatacenterMoratorium
#AIDatacenters #EnvironmentalRacism
#PreyingOnThePoor #EnergyVampires #ResistAI -
#Indigenous at the #UnitedNations Expose #AIDatacenters and Racially-Biased #Misinformation
By #BrendaNorrell, #CensoredNews, July 14, 2026
GENEVA -- "The mediocre, middle-of-the-road approach to #AI at the United Nations was countered by testimony today from #IndigenousPeoples pointing out that #ArtificialIntelligence is not a solution, and is doing great harm to Indigenous with derogatory misinformation and massive #datacenters that are poisoning the #land, #water and #air.
"#JaimieWilliams, #MiamiNation in #Indiana, speaking on behalf of the Society of Native Nations, at the U.N. Expert Mechanism on the Rights of Indigenous Peoples, responded to the A.I. summary presented this morning. Williams said the summary does not reflect the true impact of artificial intelligence, particularly in the way the technology is powered.
" 'AI data centers are rapidly being constructed on the land of Indigenous Peoples without free, prior and #InformedConsent from us.'
" 'My people came out of the water, the #SaintJosephRiver in the southeast of #LakeMichigan, along that river there are several data centers,' she said, pointing out that Indigenous across #TurtleIsland share similar stories.
" 'These sacred waterways and lands are being used for A.I. data centers.'
" 'I was once convinced artificial intelligence could help my tribe build our language and culture, but AI is not a sustainable solution.'
" 'There is currently no available technology available to power A.I. without poisoning the water, drying up the rivers and causing further contamination in the territories of Indigenous Peoples, who are already disproportionately affected.' "
Read more:
https://bsnorrell.blogspot.com/2026/07/indigenous-at-united-nations-expose-ai.html#BigData #BigDataSucks #CorporateColonialism #WaterIsLife #LandIsLife #AirIsLife #ProtectTheSacred #USPol
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💾 𝐈𝐬 𝐈𝐭 𝐒𝐦𝐚𝐫𝐭 𝐅𝐨𝐫 𝐍𝐞𝐰 𝐘𝐨𝐫𝐤 𝐒𝐭𝐚𝐭𝐞 𝐓𝐨 𝐏𝐮𝐭 𝐀 𝐌𝐨𝐫𝐚𝐭𝐨𝐫𝐢𝐮𝐦 𝐎𝐧 𝐀𝐈 𝐃𝐚𝐭𝐚 𝐂𝐞𝐧𝐭𝐞𝐫𝐬?
As in New Yorker I have mixed feelings about this.
On the one hand we need to maintain enough power generation in-state to support current residents and businesses. We already import energy from Quebec that is sent via power lines to New York City. Also, electricity in New York state is not inexpensive compared to other states in the country.
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#Wyoming - #Meta #Datacenter water discharges suspended after #contaminating the city's reclamation water supply with [ #AntibioticResistant ] #bacterium — system offline for months for cleaning, closed-loop cooling system purge spread rare metal-resistant bacteria in #Cheyenne’s water system
The city has revoked the Meta contractor's discharge privileges.
By Luke James
July 4, 2026"The Cheyenne Board of Public Utilities has stopped accepting industrial wastewater from data center fill-and-flush and closed-loop cooling operations after tracing a rare bacterium in the city's reclaimed water to #GoatSystemsLLC, the entity Meta uses to build its Cheyenne campus. In a notice reported by Cowboy State Daily, the Board said Goat Systems was in significant noncompliance for discharging water carrying #CupriavidusGilardii, a metal-resistant bacterium that interfered with two water reclamation plants and pushed the reuse system offline for months of cleanup. The Board revoked the contractor's fill-and-flush discharge privileges on March 24, and a wider suspension now covers every data center connected to city services.
"#FillAndFlush is a commissioning step in which crews fill a cooling loop's piping with water, flush it to clear debris before the system is run, and then send the used water to drain. Goat Systems routed that flush water, which contained Cupriavidus gilardii, into Cheyenne's sanitary sewer, Frank Strong, the Board's engineering and water resource division manager, told the Wyoming Tribune Eagle. Strong said the fill water had been purchased from the Board itself and that the origin of the bacterium remains unknown, but said that lab staff caught it in February during routine fecal-bacteria sampling. 'This isn't something we normally test for,' Strong told the paper.
"#Microsoft and #Nvidia market #SealedLiquidLoops as a near-#ZeroWater alternative to evaporative cooling, an approach that is spreading quickly as #AIDataCenters expand into more communities. Microsoft describes cooling systems that are filled once during construction and then recirculate the same water, while Nvidia's Rubin platform runs a coolant that is 75% water and 25% propylene glycol. That one-time fill, however, is the step that produces a discharge, and the flush water leaves the site before the loop is sealed.
"Strong went on to add that the Board's concern extends past the finding of the bacterium, because closed-loop systems can carry #glycol and other #chemicals that municipal treatment plants aren't built to process. #CheyenneWY sprays its reclaimed water on #parks, golf courses, and other #GreenSpaces, and the Board worried the bacterium could become an aerosol hazard during irrigation. Cupriavidus gilardii isn't a regulated contaminant, yet the discharge disrupted treatment sufficiently to trigger pass-through and interference findings under the Cheyenne City Code and federal pretreatment rules.
"Meta said that it's supporting its general contractor, #Fortis, which stopped discharging and began hauling wastewater offsite, and that independent testing found no trace of the substance. Testing at the #DryCreek and #CrowCreek facilities cleared in late June, and the reuse system is back online. Cheyenne City Councilman Pete Laybourn called the disclosure 'a very, very unpleasant surprise.' The Board hasn't said how the suspension affects other Cheyenne data centers still under construction."
#DataCenters #WaterIsLife #NoWaterForAI #BigDataLies #NoWaterForDatacenters
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#WestbrookME considers moratorium on #AIDataCenters as debate grows across #Maine
Story by Drew Peters, 5/18/2026
"The Westbrook City Council is expected to decide Monday whether to temporarily halt new #Datacenter development as communities across Maine continue weighing the benefits and risks tied to the growing artificial intelligence industry.
"The proposal would create a 180-day moratorium on new data center projects in Westbrook. City leaders said the pause would give officials time to update ordinances and better understand how large-scale facilities could impact the city’s electric grid, water supply, and taxpayers.
"The discussion comes as Maine communities increasingly debate the future of AI-related infrastructure. Last month, Gov. #JanetMills vetoed a bill that would have imposed a statewide moratorium on data centers.
" 'This is a subject that has the potential to destroy our community,' Westbrook resident Marnie Ward said ahead of the meeting.
"Ward said she has followed reports of data center development in other parts of the country and worries promises made by developers may not always be fulfilled.
" 'Places where companies have promised to put in things like their own electrical generation and they don’t do it,' Ward said.
"She questioned whether the economic benefits outweigh the environmental and infrastructure costs.
" 'What’s the benefit, and does the benefit of having one of these data centers outweigh the costs it’s going to be?' Ward said.
"Mayor David Morse said the proposed moratorium is intended to help the city prepare before a project proposal arrives."
#ResistBigData #MaineResists
#MainePol #DatacenterMoratoriums #DatacentersSuck #Datacenters #NoisePollution #WaterIsLife #EnergyConsumption #AISucks -
'#DataColonialism': Native Communities Fight #AI #DataCenters on #IndigenousLand
#DemocracyNow, April 22, 2026
"The artificial intelligence industry’s #DataCenter boom is the latest chapter in a long history of #EnvironmentalRacism and resource exploitation in vulnerable Native communities, says Oglala Lakota and Northern Cheyenne activist #KrystalTwoBulls, the executive director of #HonorTheEarth, an Indigenous-led #EnvironmentalJustice organization that is tracking over 100 proposed data center projects on tribal and rural lands. We speak to Two Bulls about the myriad impacts of what she calls a 'modern-day iteration' of '#SettlerColonialism,' including #NoisePollution, #cancers and respiratory illnesses, water depletion, #EnergyGrid overload and even '#EcologicalCollapse.' As tech companies set their sights on Indigenous lands, Two Bulls says, 'We’re always the one that ends up having to sacrifice our relationship to land, air, water, our communities and our nonhuman relatives.' "
Read / listen / watch:
https://www.democracynow.org/2026/4/22/krystal_twobulls_indigenous_lands_data_centers#AirIsLife #WaterIsLife #AISucks #AIDataCenters #CorporateColonialism #ResistAI
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This was my rabbit hole for today - a fun and fact filled romp through AI datacentre (& other) water usage discussion from Hank Green:
Why is Everyone So Wrong About AI Water Use??
https://www.youtube[.]com/watch?v=H_c6MWk7PQc
As always - Hank takes a complex topic and breaks it down into small enough, saccharine-and-sarcasm flavoured bites that even someone as woefully under-educated and attention span deficient as I can feel smart about stuff like this.
That being said - the episode is about 23 minutes and change long - which is roughly 20 minute longer than my normal attention span lasts for web based thingies. But certainly well worth the watch.
Not gonna lie though - he did indicate that this was a hard subject to talk about accurately, as there are a number of intertwined factors that the majority of people simply can't (nor should be expected to) understand.
Dear readers - I am happy to report that I am in the majority in this case. But on to the content of the make-you-feel-smart video:
Sam Altman says that the average ChatGPT query uses around 0.000085 gallons of water, or roughly 1 15th of a teaspoon. But then, at the same time, somehow a Morgan Stanley projection predicted annual water use for cooling and electricity generation by AI data centers could reach around 1,000 billion liters by 2028. That's a trillion liters, an 11-fold increase from 2024 estimates.
Given that Morgan Stanley does appear to release the data and methodology for their calculations, and OpenAI, does not - I am apt to find Morgan Stanley more credulous, and that's phrase that I've personally never used before.
So - OpenAI First
First, Sam is talking about the water use per query. But importantly, different queries work different ways with AI. And many queries will actually result in multiple queries you never even see.
This kind of like the folks who make Fig Newtons™ list the caloric count of a serving size to be that of, say, 2 Fig Newtons™, rather than say - a whole sleeve. [1]
However . . .
This is something Sam Altman knows, but it's not something that most people know. Behind the scenes, when you ask GPT-5 a question, it frequently "thinks". They call this reasoning models.
And it "thinks" by, like, preparing and sending out other queries and then reading the results of those queries and then sending out more queries. And then maybe, like, it might spur a search of the internet. So if you ask it a somewhat complex question, it will run an initial query and then it will take that response.
It will evaluate it using another query. It sometimes runs follow-ups until it's happy with the final answer. All those extra queries are additional queries.
So one query might not be one query. Sometimes it is, but sometimes it's a bunch. So this in itself might multiply this 1/15th of a teaspoon by, like, 15.
Most LLM queries are at least 3 queries disguised in a trench-coat.
And then there's the more in-depth analysis:
Even while we're using one model like GPT-5, which is actually a bunch of models all stuck together, OpenAI and its competitors are constantly training newer, bigger versions that no one can use yet. And to create these models, like the system runs for weeks or months on enormous clusters of GPUs burning through electricity and water for cooling. It's not really fair to treat that training footprint as separate from every conversation you have with the model.
The conversation could not happen without the training. So if you wanted to be honest, you've got to make some choices. So probably you would want to spread the water used to train all of the models in GPT-5 and spread it across every query people make.
Problem here is no one knows how to do that accurately because OpenAI doesn't share this information, which is part of why it is so easy to get numbers that are both fairly correct and very different from each other. And part of why it's so easy to lie about this from either direction.
So - how does one get to these truly massive estimates of water usage?
We know that data centers use lots of water, but they also use a lot of electricity. And you know what else uses a lot of water? Power plants, specifically thermoelectric power plants. So, a lot of power plants work in the following way.
First, you make heat, then you expose water to that heat, it expands into steam, and that expansion drives past a turbine, and that turbine then spins and that creates the electricity. But then on the other side of this, no one ever thinks about what happens. It doesn't just vent out into the atmosphere.
And according to the US Geological Survey, electricity generation accounts for, get this, 40% of all freshwater withdrawals in the United States. Now, this is confusing though, because the power plants then just put a lot, not all, but a lot of that water back. So, a lot of this water is intake and then return.
So it's not apples to apples in terms of comparing water usage of datacentres to that of powerplants, but at the same time - none of this occurs in a vacuum, and water is a finite resource - whether it's processed for municipal use or not.
Every place has a finite hydrological budget. A certain amount of water that can be pulled from rivers, lakes, reservoirs, or aquifers without causing real harm. You can shift where the strain shows up, because maybe it's in municipal treatment capacity, but maybe it's in an overdrawn aquifer, or maybe it's in a river whose temperature or flow is already stressed.
But you cannot escape the fact that water is locally limited. A data center drawing from a lake is not competing with households for tap water, but it is drawing from the same watershed. And in a lot of places, that watershed is already fully allocated.
Guess where (cough Texas) a lot of these datacentre proposals are being submitted where local aquifers are likely already oversubscribed. But I'm sure that the local folks are putting their Very Best People™ on solving this and won't be wooed by intangible promises of many monies and much jobs as a result of a potential build-out.
But in the grand scheme of things - datacentre water usage is a drop in the bucket (pun like so totally intended) compared to some other uses - specifically corn farming in the states, which brings with it it's own set of peccadilloes, peculiarities and pork barreling.
On average, it takes between 600,000 and 1 million gallons of irrigation water to grow an acre of corn, depending on rainfall and region. Corn uses orders of magnitude more water than AI. According to the US Department of Agriculture, US corn production requires around 20 trillion gallons of water per year, compared to the total estimated global AI data center water use of around 260 billion gallons.
In other words, American corn alone uses nearly 80 times more water annually than all of the world's AI servers combine. And I totally forgive you if you are thinking right now, okay, Hank, yes, but corn is food. We eat it.
Food is very important for people. But that's the thing. We don't eat it.
Maybe 1% of corn is eaten by humans. A lot of it is eaten by livestock. But 40% of it is burned in our cars and trucks.
That acre of corn that evaporated a million gallons of irrigation water will get you roughly 500 gallons of ethanol. So before we even talk about processing, every gallon of ethanol already carries an irrigation footprint of around 1500 gallons of water. Extend that to 40% of the US corn crop.
I mean that may seem like whataboutism, but I see it as perspective setting.
When we talk about water use, it makes sense that you and I don't have a deep understanding of all of this complexity. You do not need to have the level of complexity that you now have having watched this I don't really need to have it either. The reality is some areas are right up against their hydrological budgets.
They can't have new uses. Others have room. Some uses, like irrigating the entire corn belt, involve staggering amounts of water that we've just learned to see as normal.
And I get why people jump on AI water use. Wasting water feels immoral. We are told our whole lives to turn off that sink while we brush.
I'll leave you all with some of my favorites from the conclusion, which I will undoubtedly shamelessly steal and quote in some form or another in the future:
I think that our entire economy is being wagered by not very many people making very strange choices based on an imagining of the future that is, honestly, I don't think likely to occur. Which is not the topic of the video, but I ended up here anyway because I started talking about what I'm most worried about. Like, I can't predict the future.
There seems to be a great deal of debate over whether these tools are actually that useful at all, which I can't find a place in. Like, I just simply don't know. But we cannot predict the future.
We cannot even, apparently, agree upon the present. But yes, in conclusion, resource analysis is complex, the incentives are weird, and we have a very long history of underestimating how dumb corn ethanol is. And all of that combined means that it is very easy to lie about AI water use.
And that's why I drink. [2]
[1]: Shamelessly stolen from the brilliant stand up comedy of Brian Regan.
[2]: Shamelessly stolen from the brilliant stand up comedy of Doug Stanhope#AI #AISlop #AIDataCenters #WaterUsage #RabbitHole #CornSubsidies #UsPol
-
This was my rabbit hole for today - a fun and fact filled romp through AI datacentre (& other) water usage discussion from Hank Green:
Why is Everyone So Wrong About AI Water Use??
https://www.youtube[.]com/watch?v=H_c6MWk7PQc
As always - Hank takes a complex topic and breaks it down into small enough, saccharine-and-sarcasm flavoured bites that even someone as woefully under-educated and attention span deficient as I can feel smart about stuff like this.
That being said - the episode is about 23 minutes and change long - which is roughly 20 minute longer than my normal attention span lasts for web based thingies. But certainly well worth the watch.
Not gonna lie though - he did indicate that this was a hard subject to talk about accurately, as there are a number of intertwined factors that the majority of people simply can't (nor should be expected to) understand.
Dear readers - I am happy to report that I am in the majority in this case. But on to the content of the make-you-feel-smart video:
Sam Altman says that the average ChatGPT query uses around 0.000085 gallons of water, or roughly 1 15th of a teaspoon. But then, at the same time, somehow a Morgan Stanley projection predicted annual water use for cooling and electricity generation by AI data centers could reach around 1,000 billion liters by 2028. That's a trillion liters, an 11-fold increase from 2024 estimates.
Given that Morgan Stanley does appear to release the data and methodology for their calculations, and OpenAI, does not - I am apt to find Morgan Stanley more credulous, and that's phrase that I've personally never used before.
So - OpenAI First
First, Sam is talking about the water use per query. But importantly, different queries work different ways with AI. And many queries will actually result in multiple queries you never even see.
This kind of like the folks who make Fig Newtons™ list the caloric count of a serving size to be that of, say, 2 Fig Newtons™, rather than say - a whole sleeve. [1]
However . . .
This is something Sam Altman knows, but it's not something that most people know. Behind the scenes, when you ask GPT-5 a question, it frequently "thinks". They call this reasoning models.
And it "thinks" by, like, preparing and sending out other queries and then reading the results of those queries and then sending out more queries. And then maybe, like, it might spur a search of the internet. So if you ask it a somewhat complex question, it will run an initial query and then it will take that response.
It will evaluate it using another query. It sometimes runs follow-ups until it's happy with the final answer. All those extra queries are additional queries.
So one query might not be one query. Sometimes it is, but sometimes it's a bunch. So this in itself might multiply this 1/15th of a teaspoon by, like, 15.
Most LLM queries are at least 3 queries disguised in a trench-coat.
And then there's the more in-depth analysis:
Even while we're using one model like GPT-5, which is actually a bunch of models all stuck together, OpenAI and its competitors are constantly training newer, bigger versions that no one can use yet. And to create these models, like the system runs for weeks or months on enormous clusters of GPUs burning through electricity and water for cooling. It's not really fair to treat that training footprint as separate from every conversation you have with the model.
The conversation could not happen without the training. So if you wanted to be honest, you've got to make some choices. So probably you would want to spread the water used to train all of the models in GPT-5 and spread it across every query people make.
Problem here is no one knows how to do that accurately because OpenAI doesn't share this information, which is part of why it is so easy to get numbers that are both fairly correct and very different from each other. And part of why it's so easy to lie about this from either direction.
So - how does one get to these truly massive estimates of water usage?
We know that data centers use lots of water, but they also use a lot of electricity. And you know what else uses a lot of water? Power plants, specifically thermoelectric power plants. So, a lot of power plants work in the following way.
First, you make heat, then you expose water to that heat, it expands into steam, and that expansion drives past a turbine, and that turbine then spins and that creates the electricity. But then on the other side of this, no one ever thinks about what happens. It doesn't just vent out into the atmosphere.
And according to the US Geological Survey, electricity generation accounts for, get this, 40% of all freshwater withdrawals in the United States. Now, this is confusing though, because the power plants then just put a lot, not all, but a lot of that water back. So, a lot of this water is intake and then return.
So it's not apples to apples in terms of comparing water usage of datacentres to that of powerplants, but at the same time - none of this occurs in a vacuum, and water is a finite resource - whether it's processed for municipal use or not.
Every place has a finite hydrological budget. A certain amount of water that can be pulled from rivers, lakes, reservoirs, or aquifers without causing real harm. You can shift where the strain shows up, because maybe it's in municipal treatment capacity, but maybe it's in an overdrawn aquifer, or maybe it's in a river whose temperature or flow is already stressed.
But you cannot escape the fact that water is locally limited. A data center drawing from a lake is not competing with households for tap water, but it is drawing from the same watershed. And in a lot of places, that watershed is already fully allocated.
Guess where (cough Texas) a lot of these datacentre proposals are being submitted where local aquifers are likely already oversubscribed. But I'm sure that the local folks are putting their Very Best People™ on solving this and won't be wooed by intangible promises of many monies and much jobs as a result of a potential build-out.
But in the grand scheme of things - datacentre water usage is a drop in the bucket (pun like so totally intended) compared to some other uses - specifically corn farming in the states, which brings with it it's own set of peccadilloes, peculiarities and pork barreling.
On average, it takes between 600,000 and 1 million gallons of irrigation water to grow an acre of corn, depending on rainfall and region. Corn uses orders of magnitude more water than AI. According to the US Department of Agriculture, US corn production requires around 20 trillion gallons of water per year, compared to the total estimated global AI data center water use of around 260 billion gallons.
In other words, American corn alone uses nearly 80 times more water annually than all of the world's AI servers combine. And I totally forgive you if you are thinking right now, okay, Hank, yes, but corn is food. We eat it.
Food is very important for people. But that's the thing. We don't eat it.
Maybe 1% of corn is eaten by humans. A lot of it is eaten by livestock. But 40% of it is burned in our cars and trucks.
That acre of corn that evaporated a million gallons of irrigation water will get you roughly 500 gallons of ethanol. So before we even talk about processing, every gallon of ethanol already carries an irrigation footprint of around 1500 gallons of water. Extend that to 40% of the US corn crop.
I mean that may seem like whataboutism, but I see it as perspective setting.
When we talk about water use, it makes sense that you and I don't have a deep understanding of all of this complexity. You do not need to have the level of complexity that you now have having watched this I don't really need to have it either. The reality is some areas are right up against their hydrological budgets.
They can't have new uses. Others have room. Some uses, like irrigating the entire corn belt, involve staggering amounts of water that we've just learned to see as normal.
And I get why people jump on AI water use. Wasting water feels immoral. We are told our whole lives to turn off that sink while we brush.
I'll leave you all with some of my favorites from the conclusion, which I will undoubtedly shamelessly steal and quote in some form or another in the future:
I think that our entire economy is being wagered by not very many people making very strange choices based on an imagining of the future that is, honestly, I don't think likely to occur. Which is not the topic of the video, but I ended up here anyway because I started talking about what I'm most worried about. Like, I can't predict the future.
There seems to be a great deal of debate over whether these tools are actually that useful at all, which I can't find a place in. Like, I just simply don't know. But we cannot predict the future.
We cannot even, apparently, agree upon the present. But yes, in conclusion, resource analysis is complex, the incentives are weird, and we have a very long history of underestimating how dumb corn ethanol is. And all of that combined means that it is very easy to lie about AI water use.
And that's why I drink. [2]
[1]: Shamelessly stolen from the brilliant stand up comedy of Brian Regan.
[2]: Shamelessly stolen from the brilliant stand up comedy of Doug Stanhope#AI #AISlop #AIDataCenters #WaterUsage #RabbitHole #CornSubsidies #UsPol
-
This was my rabbit hole for today - a fun and fact filled romp through AI datacentre (& other) water usage discussion from Hank Green:
Why is Everyone So Wrong About AI Water Use??
https://www.youtube[.]com/watch?v=H_c6MWk7PQc
As always - Hank takes a complex topic and breaks it down into small enough, saccharine-and-sarcasm flavoured bites that even someone as woefully under-educated and attention span deficient as I can feel smart about stuff like this.
That being said - the episode is about 23 minutes and change long - which is roughly 20 minute longer than my normal attention span lasts for web based thingies. But certainly well worth the watch.
Not gonna lie though - he did indicate that this was a hard subject to talk about accurately, as there are a number of intertwined factors that the majority of people simply can't (nor should be expected to) understand.
Dear readers - I am happy to report that I am in the majority in this case. But on to the content of the make-you-feel-smart video:
Sam Altman says that the average ChatGPT query uses around 0.000085 gallons of water, or roughly 1 15th of a teaspoon. But then, at the same time, somehow a Morgan Stanley projection predicted annual water use for cooling and electricity generation by AI data centers could reach around 1,000 billion liters by 2028. That's a trillion liters, an 11-fold increase from 2024 estimates.
Given that Morgan Stanley does appear to release the data and methodology for their calculations, and OpenAI, does not - I am apt to find Morgan Stanley more credulous, and that's phrase that I've personally never used before.
So - OpenAI First
First, Sam is talking about the water use per query. But importantly, different queries work different ways with AI. And many queries will actually result in multiple queries you never even see.
This kind of like the folks who make Fig Newtons™ list the caloric count of a serving size to be that of, say, 2 Fig Newtons™, rather than say - a whole sleeve. [1]
However . . .
This is something Sam Altman knows, but it's not something that most people know. Behind the scenes, when you ask GPT-5 a question, it frequently "thinks". They call this reasoning models.
And it "thinks" by, like, preparing and sending out other queries and then reading the results of those queries and then sending out more queries. And then maybe, like, it might spur a search of the internet. So if you ask it a somewhat complex question, it will run an initial query and then it will take that response.
It will evaluate it using another query. It sometimes runs follow-ups until it's happy with the final answer. All those extra queries are additional queries.
So one query might not be one query. Sometimes it is, but sometimes it's a bunch. So this in itself might multiply this 1/15th of a teaspoon by, like, 15.
Most LLM queries are at least 3 queries disguised in a trench-coat.
And then there's the more in-depth analysis:
Even while we're using one model like GPT-5, which is actually a bunch of models all stuck together, OpenAI and its competitors are constantly training newer, bigger versions that no one can use yet. And to create these models, like the system runs for weeks or months on enormous clusters of GPUs burning through electricity and water for cooling. It's not really fair to treat that training footprint as separate from every conversation you have with the model.
The conversation could not happen without the training. So if you wanted to be honest, you've got to make some choices. So probably you would want to spread the water used to train all of the models in GPT-5 and spread it across every query people make.
Problem here is no one knows how to do that accurately because OpenAI doesn't share this information, which is part of why it is so easy to get numbers that are both fairly correct and very different from each other. And part of why it's so easy to lie about this from either direction.
So - how does one get to these truly massive estimates of water usage?
We know that data centers use lots of water, but they also use a lot of electricity. And you know what else uses a lot of water? Power plants, specifically thermoelectric power plants. So, a lot of power plants work in the following way.
First, you make heat, then you expose water to that heat, it expands into steam, and that expansion drives past a turbine, and that turbine then spins and that creates the electricity. But then on the other side of this, no one ever thinks about what happens. It doesn't just vent out into the atmosphere.
And according to the US Geological Survey, electricity generation accounts for, get this, 40% of all freshwater withdrawals in the United States. Now, this is confusing though, because the power plants then just put a lot, not all, but a lot of that water back. So, a lot of this water is intake and then return.
So it's not apples to apples in terms of comparing water usage of datacentres to that of powerplants, but at the same time - none of this occurs in a vacuum, and water is a finite resource - whether it's processed for municipal use or not.
Every place has a finite hydrological budget. A certain amount of water that can be pulled from rivers, lakes, reservoirs, or aquifers without causing real harm. You can shift where the strain shows up, because maybe it's in municipal treatment capacity, but maybe it's in an overdrawn aquifer, or maybe it's in a river whose temperature or flow is already stressed.
But you cannot escape the fact that water is locally limited. A data center drawing from a lake is not competing with households for tap water, but it is drawing from the same watershed. And in a lot of places, that watershed is already fully allocated.
Guess where (cough Texas) a lot of these datacentre proposals are being submitted where local aquifers are likely already oversubscribed. But I'm sure that the local folks are putting their Very Best People™ on solving this and won't be wooed by intangible promises of many monies and much jobs as a result of a potential build-out.
But in the grand scheme of things - datacentre water usage is a drop in the bucket (pun like so totally intended) compared to some other uses - specifically corn farming in the states, which brings with it it's own set of peccadilloes, peculiarities and pork barreling.
On average, it takes between 600,000 and 1 million gallons of irrigation water to grow an acre of corn, depending on rainfall and region. Corn uses orders of magnitude more water than AI. According to the US Department of Agriculture, US corn production requires around 20 trillion gallons of water per year, compared to the total estimated global AI data center water use of around 260 billion gallons.
In other words, American corn alone uses nearly 80 times more water annually than all of the world's AI servers combine. And I totally forgive you if you are thinking right now, okay, Hank, yes, but corn is food. We eat it.
Food is very important for people. But that's the thing. We don't eat it.
Maybe 1% of corn is eaten by humans. A lot of it is eaten by livestock. But 40% of it is burned in our cars and trucks.
That acre of corn that evaporated a million gallons of irrigation water will get you roughly 500 gallons of ethanol. So before we even talk about processing, every gallon of ethanol already carries an irrigation footprint of around 1500 gallons of water. Extend that to 40% of the US corn crop.
I mean that may seem like whataboutism, but I see it as perspective setting.
When we talk about water use, it makes sense that you and I don't have a deep understanding of all of this complexity. You do not need to have the level of complexity that you now have having watched this I don't really need to have it either. The reality is some areas are right up against their hydrological budgets.
They can't have new uses. Others have room. Some uses, like irrigating the entire corn belt, involve staggering amounts of water that we've just learned to see as normal.
And I get why people jump on AI water use. Wasting water feels immoral. We are told our whole lives to turn off that sink while we brush.
I'll leave you all with some of my favorites from the conclusion, which I will undoubtedly shamelessly steal and quote in some form or another in the future:
I think that our entire economy is being wagered by not very many people making very strange choices based on an imagining of the future that is, honestly, I don't think likely to occur. Which is not the topic of the video, but I ended up here anyway because I started talking about what I'm most worried about. Like, I can't predict the future.
There seems to be a great deal of debate over whether these tools are actually that useful at all, which I can't find a place in. Like, I just simply don't know. But we cannot predict the future.
We cannot even, apparently, agree upon the present. But yes, in conclusion, resource analysis is complex, the incentives are weird, and we have a very long history of underestimating how dumb corn ethanol is. And all of that combined means that it is very easy to lie about AI water use.
And that's why I drink. [2]
[1]: Shamelessly stolen from the brilliant stand up comedy of Brian Regan.
[2]: Shamelessly stolen from the brilliant stand up comedy of Doug Stanhope#AI #AISlop #AIDataCenters #WaterUsage #RabbitHole #CornSubsidies #UsPol
