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NeurDB: an AI-powered autonomous data system

delete2024-09-13
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AI
S
Shaofeng Cai
G
Gang Chen
申妍燕 (Yanyan Shen)
K
Kian‐Lee Tan
Y
Yuncheng Wu
X
Xiaokui Xiao
丛悦 cover
丛悦 (Yue Cong)
张美慧 cover
张美慧 (Meihui Zhang)
Z
Zhanhao Zhao *
DOI:10.1007/s11432-024-4125-9delete
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Abstract

Abstract

En 中文
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 (AIxDB) promises a new generation of data systems, which will relieve the burden on end-users across all industry sectors by featuring AI-enhanced functionalities, such as personalized and automated in-database AI-powered analytics, and self-driving 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 AI-powered 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.
Keywords:
AIxDB
in-database AI
intelligent data system

Journal

Science China Information Sciences cover
Science China Information Sciences
IF:
7.6
Papers:
4.9K
Citations:
8.9K

Organization

S
shanghai jiao tong university
Scholars:
15.5W
Papers: 11.6W
Citations: 159
R
Renmin University of China
Scholars:
8.1K
Papers: 7.7K
Citations: 1.1W
B
beijing institute of technology
Scholars:
5.4W
Papers: 3.9W
Citations: 63
N
National University of Singapore
Scholars:
7.5W
Papers: 6.4W
Citations: 11.4W
Z
zhejiang university
Scholars:
17.4W
Papers: 12.0W
Citations: 152
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