arXiv:2608. 12915v1 Announce Type: cross Abstract: The rapid growth of LLM inference is shifting sustainability concerns from one-time training to continuous serving, where infrastructure decisions shape energy use, carbon emissions, water consumption, and service quality.
By Nicoletta Tsiopani, Moysis Symeonides, George Pallis, Marios D. Dikaiakos
arXiv:2609.33965v2 Announce Type: replace-cross
Abstract: We describe a methodology for estimating the per-token energy cost of cloud-hosted large language model (LLM) inference, separating between i...
By Joshua Horswill, Ross Hunter, Matt Clifford, James Hall
arXiv:2606. 10660v1 Announce Type: cross Abstract: AI inference services -- API subscriptions, enterprise chat tools, and SaaS products with embedded AI features -- fall unambiguously within Scope 3 Category 1 under the Corporate Sustainability Reporting Directive (CSRD), which requires disclosure for fiscal years starting January 2024.
By Guillermo Llopis (SOMA AI, Barcelona)
arXiv:2605. 23348v2 Announce Type: replace-cross Abstract: AI power demand is growing at an unprecedented rate while power grids are often ailing and struggle to keep up.
By Tella Rajashekhar Reddy, Atharva Deshmukh, Liangcheng Yu, Chaojie Zhang, Mike Shepperd, Rohan Gandhi, Anjaly Parayil, Srinivasan Iyengar, Ajay Manchepalli, Debopam Bhattacherjee
arXiv:2606. 00811v1 Announce Type: cross Abstract: Data centers now account for 4.
By Dana Golden, Aruna Balasubramanian, Niranjan Balasubramanian
arXiv:2608. 09998v1 Announce Type: new Abstract: Artificial Intelligence (AI) and Machine Learning (ML) have become powerful tools for supporting and automating complex human tasks.
By Samar Garrab, Sarra Boughriou, Manel BenSassi