Sustainable AI Review
Artificial Intelligence has become a powerful tool, but its environmental implications are growing concerns. A new review examines ways to reduce the carbon footprint of AI models.
The increasing deployment of large-scale AI models, particularly Deep Learning architectures, has raised concerns about their environmental impact. These models require substantial computational resources, resulting in high energy demands and associated carbon emissions. A recent paper on arXiv presents a systematic review of research on Green AI, Green DL, and optimization techniques aimed at mitigating the environmental effects of AI models. The review also compares several carbon measurement tools for estimating emissions generated by AI algorithms, providing insights into the environmental implications of AI development. This study contributes to the ongoing discussion about sustainable AI practices, highlighting the need for environmentally conscious AI development. The paper is available on arXiv, a leading platform for research in computer science, at https://arxiv.org/abs/2608.09998.
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