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AI's energy footprint

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.

This is true for most of the name-brand models you’re accustomed to, like OpenAI’s ChatGPT, Google’s Gemini, and Anthropic’s Claude, which are referred to as “closed.” The key details are held closely by the companies that make them, guarded because they’re viewed as trade secrets (and also possibly because they might result in bad PR). And indeed, the moves by leading AI companies to fire up nuclear power plants and create data centers of unprecedented scale suggest that their vision for the future would consume far more energy than even a large number of these individual queries. They offered ways that companies could disclose more information without violating trade secrets, such as anonymized data-sharing arrangements, but their report acknowledged that the architects of this massive surge in AI data centers have thus far not been transparent, leaving them without the tools to make a plan.

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