Summarize this content to 2000 words in 6 paragraphs in Arabic Stay informed with free updatesSimply sign up to the Artificial intelligence myFT Digest — delivered directly to your inbox.Informed readers already know that lots of energy will be needed to fuel hoped-for progress in machine learning, large language models and various other stuff that tech-industry salesmen classify as \u201cartificial intelligence\u201d. Barclays has a nice summary out today about AI\u2019s energy demand: Most of the world\u2019s more than 11,000 registered data centres are not yet involved in any kind of AI-related activity. Combined, their consumption of electricity (excluding cryptocurrencies) is about 1.0%-1.5% of the world\u2019s total, according to a mid-2024 report from the IEA2.However, data centres\u2019\u202fenergy demands could change dramatically in coming years, thanks to the dissemination of AI. According to a June 2024 analysis from Barclays Research \u2014 which uses a bottom-up approach based on utilities\u2019 forward-looking supply contracts \u2014 annual demand to power data centres in the US could grow by a range of 14%-21% every year through 2030. That would imply US data-centre demand roughly tripling by 2030, from 150-175 terawatt hours (TWh) in 2023 to as much as 560 TWh \u2014 equivalent to 13% of current US electricity demand.It\u2019s notable that the data-centre boom came at a very convenient time for the commercial real estate market, but that\u2019s perhaps a different story. From the bank: Headlines out of Virginia have already shown how \u201cbottlenecks\u201d can arise in energy supply, especially as data-centre construction tends to cluster in certain crucial regions. And the only energy source that really meets the demand? It seems that\u2019s mainly nuclear energy: If the internet has to be flooded with AI slop, we might as well get some clean energy out of it. <\/p>\n","protected":false},"excerpt":{"rendered":"
Summarize this content to 2000 words in 6 paragraphs in Arabic Stay informed with free updatesSimply sign up to the Artificial intelligence myFT Digest — delivered directly to your inbox.Informed readers already know that lots of energy will be needed to fuel hoped-for progress in machine learning, large language models and various other stuff that<\/p>\n","protected":false},"author":1,"featured_media":0,"comment_status":"open","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"footnotes":""},"categories":[63],"tags":[],"class_list":{"0":"post-168766","1":"post","2":"type-post","3":"status-publish","4":"format-standard","6":"category-tech"},"_links":{"self":[{"href":"https:\/\/globetimeline.com\/ar\/wp-json\/wp\/v2\/posts\/168766","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/globetimeline.com\/ar\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/globetimeline.com\/ar\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/globetimeline.com\/ar\/wp-json\/wp\/v2\/users\/1"}],"replies":[{"embeddable":true,"href":"https:\/\/globetimeline.com\/ar\/wp-json\/wp\/v2\/comments?post=168766"}],"version-history":[{"count":0,"href":"https:\/\/globetimeline.com\/ar\/wp-json\/wp\/v2\/posts\/168766\/revisions"}],"wp:attachment":[{"href":"https:\/\/globetimeline.com\/ar\/wp-json\/wp\/v2\/media?parent=168766"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/globetimeline.com\/ar\/wp-json\/wp\/v2\/categories?post=168766"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/globetimeline.com\/ar\/wp-json\/wp\/v2\/tags?post=168766"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}