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AI and our energy future

It’s well documented that AI is a power-hungry technology. But there has been far less reporting on the extent of that hunger, how much its appetite is set to grow in the coming years, where that power will come from, and who will pay for it. For the past six months, MIT Technology Review’s team of reporters and editors have worked to answer those questions. The result is an unprecedented look at the state of AI’s energy and resource usage, where it is now, where it is headed in the years to come, and why we have to get it right. 

At the centerpiece of this package is an entirely novel line of reporting into the demands of inference—the way human beings interact with AI when we make text queries or ask AI to come up with new images or create videos. Experts say inference is set to eclipse the already massive amount of energy required to train new AI models. We were so startled by what we learned reporting this story that we also put together a brief on everything you need to know about estimating AI’s energy and emissions burden. 

And then we went out into the world to see the effects of this hunger. We take you into the deserts of Nevada, where data centers in an industrial park the size of Detroit demand ever more water to keep their processors cool and running. In Louisiana, where Meta plans its largest-ever data center, we expose the dirty secret that will fuel its AI ambitions—along with those of many others. Separately, we have a look at why the clean energy promise of powering AI data centers with nuclear energy will long remain elusive. 

Finally, we also look at the reasons to be optimistic, and examine why future AI systems could be far less energy intensive than today’s.


This work was supported by a grant from the Tarbell Center for AI Journalism.


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We did the math on AI’s energy footprint. Here’s the story you haven’t heard.

The emissions from individual AI text, image, and video queries seem small—until you add up what the industry isn’t tracking and consider where it’s heading next.

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Everything you need to know about estimating AI’s energy and emissions burden

We unfortunately can’t fit all our context and caveats in a story that’s supposed to be readable.

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The data center boom in the desert

Apple, Google, and other tech companies are planning huge AI or cloud storage data centers near Reno, sparking fears of water strains in America’s driest state.

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AI could keep us dependent on natural gas for decades to come

Electricity demand from AI data centers is driving a surge in new natural-gas power plants around the country. What does that mean for our clean-energy aspirations?

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 Can nuclear power really fuel the rise of AI?

Tech giants are looking for more energy, but building new reactors takes time.

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Four reasons to be optimistic about AI’s energy usage

There are reasons to be concerned about the climate impact of artificial intelligence, but all hope is not lost. Here’s why.

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AI’s energy impact is still small—but how we handle it is huge

The rising energy cost of data centers is a vital test case for how we deal with the broader electrification of the economy.