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In particular, graphics cards have become central to AI training, with frequent hardware updates required to meet escalating computational demands. However, the environmental damages of graphics cards production remain understudied.\n  This study addresses this gap by estimating the environmental damages associated with graphics cards production over the past decade (2013-2025). We analyze trends in energy consumption, carbon emissions and resource depletion.\n  We compile and provide a dataset documenting the environmental damages of NVIDIA workstation graphics cards production since 2013. Our analysis of this dataset reveals a steady increase in production-related impacts over the period.\n  Our finding highlights the ","title":"The Rising Unsustainability of AI Graphics Cards Production","url":"https://arxiv.org/abs/2607.01258","vendor":"arxiv_cs_ai"},"summary":"arXiv:2607.01258v1 Announce Type: cross \nAbstract: The rapid advancement of Artificial Intelligence (AI) has been accompanied by significant increases in computational and environmental costs, driven by large-scale investments in AI infrastructure, hardware, and software. In particular, graphics cards have become central to AI training, with frequent hardware updates required to meet escalating computational demands. However, the environmental damages of graphics cards production remain understudied.\n  This study addresses this gap by estimating the environmental damages associated with graphics cards production over the past decade (2013-2025). We analyze trends in energy consumption, carbon emissions and resource depletion.\n  We compile and provide a dataset documenting the environmental damages of NVIDIA workstation graphics cards production since 2013. 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