{"id":32314,"date":"2026-03-31T02:20:49","date_gmt":"2026-03-31T02:20:49","guid":{"rendered":"https:\/\/www.cycloid.io\/article\/getting-started-with-measuring-ais-carbon-footprint\/"},"modified":"2026-03-31T02:20:49","modified_gmt":"2026-03-31T02:20:49","slug":"getting-started-with-measuring-ais-carbon-footprint","status":"publish","type":"article","link":"https:\/\/www.cycloid.io\/fr\/press\/getting-started-with-measuring-ais-carbon-footprint\/","title":{"rendered":"Getting started with measuring AI\u2019s carbon footprint"},"content":{"rendered":"
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According to Nvidia CEO Jensen Huang<\/a>, the amount of computation necessary to run artificial intelligence (AI) is 1,000 times higher than the computing power needed to run non-AI software.<\/p>\n

While traditional datacentre racks generate 20 to 40 kilowatts per rack, Ryan Hotchkin, senior director of datacentre and business management operations for SHI, says Nvidia is doubling that every year.<\/p>\n

\u201cWith the GB200s and NVL72s we\u2019re looking at 120 kilowatts per rack. More powerful graphic processing units [GPUs] equates to more demand for power distribution units [PDUs], and that has a knock-on effect on the electrical infrastructure,\u201d he adds.<\/p>\n<\/div>\n<\/div>\n

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View the<\/strong> full article here<\/strong><\/a>.<\/strong><\/p>\n

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