Speaker: Daria Stepanova (Bosch Center for Artificial Intelligence)
Keywords: Neuro-symbolic AI, knowledge graphs, answer set programming, applications
Abstract
Neuro-symbolic AI combines the data-driven strengths of machine learning with the logical reasoning and transparency of symbolic systems, offering a transformative approach for industrial applications. While significant progress has been made in academic research, industrial adoption remains in its early stages. In this talk, I will present our journey at Bosch in trying to bridge the gap between research and real-world use cases, focusing on the combination of Answer Set Programming (ASP) and Knowledge Graphs with machine learning methods, e.g., large language models. I will present our attempts to apply these hybrid AI approaches in diverse domains such as conceptual system configuration, production optimization, and market analysis, while also highlighting key open research questions. Part of the work presented in this talk is the result of a collaboration between Bosch and the Vienna University of Technology.
Download the tutorial slides (PDF)
Interested in a position at Bosch (Master thesis, PhD scholarship, or a full-time position)? Please reach out to me directly at daria.stepanova@de.bosch.com.