GPU

A study from Cambridge University and the Chinese Academy of Sciences warns that by 2030, generative AI could produce e-waste on an unprecedented scale, with projected volumes reaching millions of tons annually. As AI hardware life cycles shorten to meet the demand for computational power, researchers emphasize the urgent need for sustainable practices. Proposed solutions like hardware reuse, efficient component updates, and a circular economy approach could significantly mitigate AI's environmental impact, potentially reducing e-waste by up to 86%.