As the everyday use of AI has exploded in recent years, so have the energy demands of the computing infrastructure that supports it. But the environmental toll of these large data centers, which suck up gigawatts of power and require vast amounts of water for cooling, has been too diffuse and difficult to quantify.
  • sodium_nitride [she/her, any]@hexbear.netEnglish
    7·
    10 days ago

    On the upside, the study also outlines an actionable roadmap that would use smart siting, faster grid decarbonization and operational efficiency to cut these impacts by approximately 73% (carbon dioxide) and 86% (water) compared with worst‑case scenarios.

    From the paper’s abstrac5

    Although best practices may reduce emissions and water footprints by up to 73% and 86%, respectively, their effectiveness is constrained by current energy infrastructure limitations. These findings underscore the urgency of accelerating the energy transition and point to the need for AI companies to harness the clean energy potential of Midwestern states. Coordinating efforts of private actors and regulatory interventions would ensure the competitive and sustainable development of the AI sector.

    These dogshit journalists istg