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Microsoft tests biomimicry to blend data centers into Texas landscapes

Microsoft is experimenting with biomimicry—designing data centers to resemble natural landscapes—to ease local opposition in cities like San Antonio. The company plans to integrate native trees, pollinator gardens, and restored ecosystems at over 20 US and German sites, following a 2022 project in the Netherlands. It also aims to buffer noise and visual impact with plant barriers, citing…

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Key points

  • Microsoft plans biomimicry at over 20 US and German data centers, including native trees and pollinator gardens
  • San Antonio’s 2022 data center project cut **2,600 trees** over 33 acres, sparking local protests
  • Texas data centers used **25 billion gallons of water** in 2025; HARC estimates 0.5–2.7% of state water use by 2030

Critics argue these efforts are insufficient to offset broader concerns: Texas data centers consumed 25 billion gallons of water in 2025, and Microsoft’s carbon emissions rose 25% last year. Advocates like Councilmember Ric Galvan and Public Citizen’s Adrian Shelley demand stricter limits on water use, pollution, and tree removal. A statewide moratorium on new data center projects was imposed in August, pending audits of electricity and water demands. Microsoft’s Community-First AI Infrastructure plan, announced in January, remains untested in practice.

Full story from The Verge AI · by Justine CalmaOpen source ↗

If a data center is camouflaged in the woods, will anyone hate it?

The Verge AI · 2 October 2026

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This text was published by The Verge AI and written by Justine Calma. It is reproduced here with attribution so you can read it in full; the rights remain with the publisher. Read it at the source ↗

Topics · follow one to build your own front page
MicrosoftChevronPublic CitizenRoot-Pike Watershed Initiative Network (Root-Pike WIN)Ric GalvanKaitlin ChuziJennifer LyonsDave GiordanoAdrian ShelleyErin Kinney

The headline, key points and digest above were generated by Digest AI's editorial model from the linked sources. Automated summaries can contain errors: the sources are the record. Spotted a mistake? Tell us. Published by Martin K., who runs Digest AI and handles corrections.

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