Policy

Amazon Plans Texas Data Center That Could Top US Pollution

Amazon is planning a Texas data center powered by an on-site natural gas plant permitted to emit 33 million tons of carbon dioxide annually, highlighting the environmental cost of the AI boom.

TechCrunch AI2 days agoPolicy
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Amazon is investing in a massive on-site power plant for a planned data center in Pecos County, Texas, that could become the single largest source of climate pollution in the United States. According to reports, the facility will burn natural gas to generate electricity. It has already received permits allowing it to release up to 33 million tons of carbon dioxide every year, a figure that surpasses the emissions of any other active power plant currently operating in the country.

An Amazon spokesperson defended the project, stating that the new on-site generation will prevent the facility from driving up electricity costs for local Texas families. However, the move highlights the growing tension between the tech industry's massive artificial intelligence expansion and its environmental commitments. Amazon previously co-founded a climate pledge to eliminate its carbon emissions by 2040, but the company reported that its carbon emissions actually rose by 16 percent last year. An Amazon representative acknowledged that "the world looks different now" compared to when the pledge was made, though they maintained that the company's core commitment remains unchanged.

For AI practitioners and enterprise developers, this development underscores a shifting reality in cloud infrastructure. As training and running large-scale AI models demand unprecedented amounts of electricity, cloud providers are increasingly turning to fossil fuels like natural gas to guarantee stable, continuous power. Developers who prioritize green computing may find it harder to minimize their indirect carbon footprints, as the underlying infrastructure of major cloud platforms relies more heavily on carbon-intensive energy sources to meet the relentless computational demands of modern machine learning.

This is our own summary of reporting by TechCrunch AI

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