The year 2022 has been marked by several breakthrough results in the domain of generative AI, culminating in the rise of tools like ChatGPT, able to solve a variety of language-related tasks without specialized training. In this talk, I outline novel opportunities in the context of data management, enabled by these advances. I discuss several recent research projects, aimed at exploiting advanced language processing for tasks such as parsing a database manual to support automated tuning, or mining data for patterns, described in natural language. Finally, I discuss our recent and ongoing research, aimed at synthesizing code for SQL processing in general-purpose programming languages, while enabling customization via natural language commands.
Immanuel Trummer is assistant professor for computer science at Cornell University. His research covers various aspects of large-scale data management with the goal of making data analysis more efficient and more user-friendly. His publications were selected for “Best of VLDB”, for the ACM SIGMOD Research Highlight Award, and for publication in CACM as CACM Research Highlight. He is a recipient of the Google Faculty Research Award and alumnus of the German National Academic Foundation.