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Table of Contents
1. Introduction
2. Background of Data-Centric AI
3. Definitions
4. Need for Data-centric AI
5. Tasks in Data-centric AI
6. Representative Tasks
7. Conclusion
Summary
This paper provides a comprehensive overview of data-centric artificial intelligence, highlighting the importance of systematically engineering data for building AI systems. It discusses the shift towards data-centric AI, the goals of training data development, inference data development, and data maintenance, and the challenges and methods in achieving data excellence. The authors emphasize the significance of enhancing data quality and quantity to improve AI performance and address potential issues with data in AI systems.