Related papers: Data-centric AI: Perspectives and Challenges

Data-centric AI: Perspectives and Challenges

URL: http://arxiv.org/abs/2301.04819v3
Date: Sun, 2 Apr 2023 05:18:56 GMT
Title: Data-centric AI: Perspectives and Challenges
Authors: Daochen Zha, Zaid Pervaiz Bhat, Kwei-Herng Lai, Fan Yang, Xia Hu
Abstract summary: Data-centric AI (DCAI) advocates a fundamental shift from model advancements to ensuring data quality and reliability. We bring together three general missions: training data development, inference data development, and data maintenance.
Score: 51.70828802140165
License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Abstract: 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, inference data development, and data maintenance. We provide a top-level discussion on representative DCAI tasks and share perspectives. Finally, we list open challenges. More resources are summarized at https://github.com/daochenzha/data-centric-AI

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