AI’s Unending Thirst

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In last week’s newsletter, I described artificial intelligence as data-hungry. But the technology is also quite thirsty, relying on data centers that require not just a tremendous amount of energy, but water to cool themselves with.

Karen Hao, a contributing writer at The Atlantic, recently visited one such data center in Goodyear, Arizona. Microsoft owns the facility, which may eventually use an estimated 56 million gallons of drinking water each year—“equivalent to the amount used by 670 Goodyear families,” Karen notes. No one’s at risk of going thirsty, but as Karen writes, “the supply of water in the region is quite limited, and the more that’s taken up by data centers, the less there is for, say, supplying tap water to new housing.”

I followed up with Karen to ask about AI’s growing demands on our environment. It’s still a matter of debate whether the technology is truly worth its immense costs, even as tech companies commit more and more resources to it. How should we be thinking about all of this? “Companies are laying down data centers faster than ever in the race to build generative AI, but there has been very little accounting of their impacts on the environment,” Karen told me. “There’s a narrowing window in which the public should be asking: Is this what we want? Once the facilities have been built, it will be much more difficult to reverse the decision.”

— Damon Beres, senior editor

AI Is Taking Water From the Desert

By Karen Hao

One scorching day this past September, I made the dangerous decision to try to circumnavigate some data centers. The ones I chose sit between a regional airport and some farm fields in Goodyear, Arizona, half an hour’s drive west of downtown Phoenix. When my Uber pulled up beside the unmarked buildings, the temperature was 97 degrees Fahrenheit. The air crackled with a latent energy, and some kind of pulsating sound was emanating from the electric wires above my head, or maybe from the buildings themselves. With no shelter from the blinding sunlight, I began to lose my sense of what was real.

Microsoft announced its plans for this location, and two others not so far away, back in 2019—a week after the company revealed its initial $1 billion investment in OpenAI, the buzzy start-up that would later release ChatGPT. From that time on, OpenAI began to train its models exclusively on Microsoft’s servers; any query for an OpenAI product would flow through Microsoft’s cloud-computing network, Azure. In part to meet that demand, Microsoft has been adding data centers at a stupendous rate, spending more than $10 billion on cloud-computing capacity in every quarter of late. One semiconductor analyst called this “the largest infrastructure buildout that humanity has ever seen.”

I’d traveled out to Arizona to see it for myself. The Goodyear site stretched along the road farther than my eyes could see. A black fence and tufts of desert plants lined its perimeter. I began to walk its length, clutching my phone and two bottles of water. According to city documents, Microsoft bought 279 acres for this location. For now, the plot holds two finished buildings, thick and squat, with vents and pipes visible along their sides. A third building is under construction, and seven more are on the way. Each will be decked out with rows of servers and computers that must be kept below a certain temperature. The complex has been designated partly for OpenAI’s use, according to a person familiar with the plan. (Both Microsoft and OpenAI declined to comment on this assertion.) And Microsoft plans to absorb its excess heat with a steady flow of air and, as needed, evaporated drinking water. Use of the latter is projected to reach more than 50 million gallons every year.

Read the full article.

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P.S.

Earlier this week, President Joe Biden signed legislation that could result in a TikTok ban if the app isn’t divested from its Chinese parent company. As Charlie Warzel writes for The Atlantic, this will be a more complicated process than it seems—particularly when it comes to the app’s powerful AI algorithm.

— Damon