Data-centric AI: Perspectives and Challenges

被引:0
|
作者
Zha, Daochen [1 ]
Bhat, Zaid Pervaiz [2 ]
Lai, Kwei-Herng [1 ]
Yang, Fan [1 ]
Hu, Xia [1 ]
机构
[1] Rice Univ, Houston, TX 77005 USA
[2] Texas A&M Univ, College Stn, TX USA
关键词
D O I
暂无
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
The role of data in building AI systems has recently been significantly magnified by the emerging concept of data-centric AI (DCAI), which advocates a fundamental shift from model advancements to ensuring data quality and reliability. Although our community has continuously invested efforts into enhancing data in different aspects, they are often isolated initiatives on specific tasks. To facilitate the collective initiative in our community and push forward DCAI, we draw a big picture and bring together three general missions: training data development, evaluation data development, and data maintenance. We provide a top-level discussion on representative DCAI tasks and share perspectives. Finally, we list open challenges to motivate future exploration.
引用
收藏
页码:945 / 948
页数:4
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