A review of green artificial intelligence: Towards a more sustainable future
Verónica Bolón‐Canedo, Laura Morán‐Fernández, Brais Cancela, Amparo Alonso‐Betanzos
Universidade da Coruña
阅读操作
确认中在文库中上传 PDF 后可生成中文音频讲解。
摘要与影响
Green artificial intelligence (AI) is more environmentally friendly and inclusive than conventional AI, as it not only produces accurate results without increasing the computational cost but also ensures that any researcher with a laptop can perform high-quality research without the need for costly cloud servers. This paper discusses green AI as a pivotal approach to enhancing the environmental sustainability of AI systems. Described are AI solutions for eco-friendly practices in other fields (green-by AI), strategies for designing energy-efficient machine learning (ML) algorithms and models (green-in AI), and tools for accurately measuring and optimizing energy consumption. Also examined are the role of regulations in promoting green AI and future directions for sustainable ML. Underscored is the importance of aligning AI practices with environmental considerations, fostering a more eco-conscious and energy-efficient future for AI systems.
逐年被引趋势
关键指标
同类平均 = 1
同领域 · 同年份 · 同类型
Google Scholar 与 OpenAlex 的被引统计范围不同,数值存在差异属正常。
AI 辅助阅读
依据:摘要
可就本文提问;依据不足时会说明。
学术脉络
学科主题
物理Air Quality Monitoring and Forecasting
Impact of Light on Environment and Health · Energy Load and Power Forecasting
参考文献 111
此处列出前 3 条
引用本文 404
按被引量排序,此处列出前 3 条