Whilst constant peer review and further statistics are required, its evident that the AI explosion will come with a hefty energy price tag.<\/p>\n
Here\u2019s what MIT\u2019s technology review had to say in May 2024<\/a>.<\/p>\n <\/p>\n Using AI for certain tasks can come with a significant energy price tag<\/strong>. With some powerful AI models, generating an image can require as much energy as charging up your phone. Create 1,000 images with a model like Stable Diffusion XL, and you\u2019ve produced as much carbon dioxide as driving just over four miles in a gas-powered car, according to the researchers Melissa spoke to.<\/p>\n But while generated images are splashy, there are plenty of AI tasks that don\u2019t use as much energy. For example, creating images is thousands of times more energy-intensive than generating text. And using a smaller model that\u2019s tailored to a specific task, rather than a massive, all-purpose generative model, can be dozens of times more efficient. In any case, generative AI models require energy, and we\u2019re using them a lot.<\/p>\n Electricity consumption from data centers, AI, and cryptocurrency could reach double 2022 levels by 2026<\/strong>, according to projections from the International Energy Agency<\/a>. Those technologies together made up roughly 2% of global electricity demand in 2022. Note that these numbers aren\u2019t just for AI\u2014it\u2019s tricky to nail down AI\u2019s specific contribution, so keep that in mind when you see predictions about electricity demand from data centers.<\/p>\n The news is slowly but surely bouncing through traditional media<\/a> too.<\/p>\n