NeurDB: an AI-powered autonomous data system
作者机构：School of Computing National University of Singapore College of Computer Science and Technology Zhejiang University Department of Computer Science and Engineering Shanghai Jiao Tong University School of Information Renmin University of China School of Computer Science and Technology Beijing Institute of Technology
出 版 物：《Science China(Information Sciences)》 (中国科学:信息科学(英文版))
年 卷 期：2024年
核心收录：
学科分类：12[管理学] 1201[管理学-管理科学与工程(可授管理学、工学学位)] 081104[工学-模式识别与智能系统] 08[工学] 0835[工学-软件工程] 0811[工学-控制科学与工程] 0812[工学-计算机科学与技术（可授工学、理学学位）]
基 金：partially supported by the Lee Foundation in terms of Beng Chin Ooi’s Lee Kong Chian Centennial Professorship Fund NUS Faculty Development Fund supported by National Key Research and Development Program of China (Grant No. 2022YFB2703100) supported by National Key Research and Development Program of China (Grant No. 2022YFE0200500) supported by National Key Research and Development Program of China (Grant No. 2023YFB4503600) supported by National Natural Science Foundation of China (Grant No. 62072033)
摘 要：In the wake of rapid advancements in artificial intelligence (AI), we stand on the brink of a transformative leap in data systems. The imminent fusion of AI and DB (AI×DB) promises a new generation of data systems, which will relieve the burden on end-users across all industry sectors by featuring AIenhanced functionalities, such as personalized and automated in-database AI-powered analytics, and selfdriving capabilities for improved system performance. In this paper, we explore the evolution of data systems with a focus on deepening the fusion of AI and DB. We present NeurDB, an AI-powered autonomous data system designed to fully embrace AI design in each major system component and provide in-database AIpowered analytics. We outline the conceptual and architectural overview of NeurDB, discuss its design choices and key components, and report its current development and future plan.
同方期刊数据库