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explores the environmental implications of generative AI. On this page, we glance at why this engineering is so useful resource-intensive. A 2nd piece will look into what specialists are performing to reduce genAI’s carbon footprint and other impacts.
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Even though it is actually hard to estimate exactly how much power is needed to manufacture a GPU, a kind of powerful processor that could cope with intense generative AI workloads, It could be greater than what is necessary to provide a simpler CPU because the fabrication process is much more elaborate. A GPU’s carbon footprint is compounded because of the emissions linked to materials and product transport.
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Chandrakasan adds that the get more info consortium’s vision is rooted in MIT’s Main mission. “I am thrilled and honored to assist progress one among President Kornbluth’s strategic priorities all over artificial intelligence,” he states.
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