TY - GEN
T1 - Database Meets Artificial Intelligence
T2 - 39th IEEE International Conference on Data Engineering, ICDE 2023
AU - Zhou, Xuanhe
AU - Chai, Chengliang
AU - Li, Guoliang
AU - Sun, Ji
N1 - Publisher Copyright:
© 2023 IEEE.
PY - 2023
Y1 - 2023
N2 - Database and Artificial Intelligence (AI) can benefit from each other. On one hand, AI can make database more intelligent (AI4DB). It is challenging for empirical database optimization techniques (e.g., configuration tuning, query optimization) to meet the high-performance requirement for large-scale database instances, various applications, diversified users. Learning-based techniques can alleviate this problem by exploring high-quality optimization strategies and reusing the historical data/models. On the other hand, database techniques can optimize AI models (DB4AI). AI is hard to deploy in real applications, because it requires developers to write complex codes and train complicated models. Database techniques can be used to reduce the complexity of using AI models, accelerate AI algorithms and provide AI capability inside databases. Thus, both DB4AI and AI4DB have been extensively studied recently.
AB - Database and Artificial Intelligence (AI) can benefit from each other. On one hand, AI can make database more intelligent (AI4DB). It is challenging for empirical database optimization techniques (e.g., configuration tuning, query optimization) to meet the high-performance requirement for large-scale database instances, various applications, diversified users. Learning-based techniques can alleviate this problem by exploring high-quality optimization strategies and reusing the historical data/models. On the other hand, database techniques can optimize AI models (DB4AI). AI is hard to deploy in real applications, because it requires developers to write complex codes and train complicated models. Database techniques can be used to reduce the complexity of using AI models, accelerate AI algorithms and provide AI capability inside databases. Thus, both DB4AI and AI4DB have been extensively studied recently.
KW - AI4DB
KW - Artificial-Intelligence
KW - DB4AI
KW - Database
UR - http://www.scopus.com/inward/record.url?scp=85167735289&partnerID=8YFLogxK
U2 - 10.1109/ICDE55515.2023.00377
DO - 10.1109/ICDE55515.2023.00377
M3 - Conference contribution
AN - SCOPUS:85167735289
T3 - Proceedings - International Conference on Data Engineering
SP - 3901
EP - 3902
BT - Proceedings - 2023 IEEE 39th International Conference on Data Engineering, ICDE 2023
PB - IEEE Computer Society
Y2 - 3 April 2023 through 7 April 2023
ER -