From Large Language Models to Databases and Back A discussion on research and education

Angela Bonifati (1, 2) , Sihem Amer-Yahia (3) , Chen Lei (4, 5) , Li Guoliang (6, 7) , Shim Kyuseok (8) , Xu Jianliang , Yang Xiaochun

1 LIRIS - Laboratoire d'InfoRmatique en Image et Systèmes d'information
2 BD - Base de Données
3 LIG - Laboratoire d'Informatique de Grenoble
4 OHSU - Oregon Health and Science University [Portland]
5 THU - Tsinghua University [Beijing]
6 Institut de cardiologie [CHU Pitié-Salpêtrière]
7 Xjtu - Xi'an Jiaotong University
8 SNU - Seoul National University [Seoul]

Tianjin, China. The title of the panel was "What does LLM (ChatGPT) Bring to Data Science Research and Education? Pros and Cons". It was moderated by Lei Chen and Xiaochun Yang. The discussion raised several questions on how large language models (LLMs) and database research and education can help each other and the potential risks of LLMs.

Domaines: Informatique [cs]

Angela Bonifati, Sihem Amer-Yahia, Chen Lei, Li Guoliang, Shim Kyuseok, et al.. From Large Language Models to Databases and Back A discussion on research and education. SIGMOD record, 2023, 52 (3), pp 49-56. ⟨10.1145/3631504.3631518⟩. ⟨hal-04370096⟩