气候变化
奇迹
计算机科学
温室气体
连接(拓扑)
人性
全球变暖
数据科学
政治学
心理学
生态学
数学
社会心理学
生物
组合数学
法学
作者
David Rolnick,Priya L. Donti,Lynn H. Kaack,Kelly Kochanski,Alexandre Lacoste,Kris Sankaran,Andrew Slavin Ross,Nikola Milojevic-Dupont,Natasha Jaques,Anna Waldman‐Brown,Alexandra Sasha Luccioni,Tegan Maharaj,Evan D. Sherwin,S. Karthik Mukkavilli,Konrad P. Körding,Carla P. Gomes,Andrew Y. Ng,Demis Hassabis,John Platt,Felix Creutzig,Jennifer Chayes,Yoshua Bengio
摘要
Climate change is one of the greatest challenges facing humanity, and we, as machine learning (ML) experts, may wonder how we can help. Here we describe how ML can be a powerful tool in reducing greenhouse gas emissions and helping society adapt to a changing climate. From smart grids to disaster management, we identify high impact problems where existing gaps can be filled by ML, in collaboration with other fields. Our recommendations encompass exciting research questions as well as promising business opportunities. We call on the ML community to join the global effort against climate change.
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