Even the US Government Says AI Requires Massive Amounts of Water

A Government Accountability Office report released this week reveals generative AI systems consume staggering amounts of water, with 250 million daily queries requiring over 1.1 million gallons -- all while companies provide minimal transparency about resource usage. The 47-page analysis [PDF] found cooling data centers -- which demand between 100-1000 megawatts of power -- constitutes 40% of their energy consumption, a figure expected to rise as global temperatures increase. Water usage varies dramatically by location, with geography significantly affecting both water requirements and carbon emissions. Meta's Llama 3.1 405B model has generated 8,930 metric tons of carbon, compared to Google's Gemma2 at 1,247.61 metric tons and OpenAI's GPT3 at 552 metric tons. The report confirms generative AI searches cost approximately ten times more than standard keyword searches. The GAO asserted about persistent transparency problems across the industry, noting these systems remain "black boxes" even to their designers. Read more of this story at Slashdot.

Apr 24, 2025 - 17:06

Even the US Government Says AI Requires Massive Amounts of Water

A Government Accountability Office report released this week reveals generative AI systems consume staggering amounts of water, with 250 million daily queries requiring over 1.1 million gallons -- all while companies provide minimal transparency about resource usage. The 47-page analysis [PDF] found cooling data centers -- which demand between 100-1000 megawatts of power -- constitutes 40% of their energy consumption, a figure expected to rise as global temperatures increase. Water usage varies dramatically by location, with geography significantly affecting both water requirements and carbon emissions. Meta's Llama 3.1 405B model has generated 8,930 metric tons of carbon, compared to Google's Gemma2 at 1,247.61 metric tons and OpenAI's GPT3 at 552 metric tons. The report confirms generative AI searches cost approximately ten times more than standard keyword searches. The GAO asserted about persistent transparency problems across the industry, noting these systems remain "black boxes" even to their designers.