Rohan Paul@rohanpaul_ai · XGreg Brockman指出，公众对AI数据中心用水量的认知存在偏差，主要源于混淆了“取水量”与“耗水量”。他解释，现代数据中心多采用闭环冷却系统，如同“密封水池”，水在系统内循环吸热，而非像“流水龙头”般持续消耗新鲜水源。因此，系统可容纳大量水，但日常补充的新鲜水很少。OpenAI的Stargate项目博客也证实，其站点采用闭环冷却，全面运行后年耗水量仅相当于一栋办公楼或约四个家庭的用水量。公众辩论常因不了解冷却技术差异而过度简化。
Greg Brockman explains how the public story about AI data center water use is partly wrong.
Because the cooling-systems use a closed-loop design that circulates the same stored water instead of constantly pulling fresh water.
i.e. it works less like a running tap and more like a sealed pool， where water absorbs heat from servers， moves through cooling equipment， then returns to the same circuit.
The argument here is not that AI infrastructure has no resource cost， but that public debate often mixes up different cooling designs and treats every data center as if it burns through water the same way.
The important distinction is water withdrawal versus water consumption， because a site can hold a large amount of water inside its pipes while using far less new water day to day.