Will LLMs reshape, supercharge, or kill data science? (VLDB 2023 Panel)
Summary: Examines how LLMs can be applied to structured data and data‑science workflows, potentially transforming long‑standing DB problems and automating modeling, cleaning, and query tasks. Contrasts augmentation vs. disruptive scenarios, grounded in prototypes and deployments. (summarized by gpt-5-mini on Feb 09 2026)
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Authors
- 1. Alon Halevy
- 2. Yejin Choi
- 3. Avrilia Floratou
- 4. Michael J. Franklin
- 5. Natasha Noy
- 6. Haixun Wang
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