Speaker
Description
As part of an effort to integrate generative AI into operation, a project focusing on establishing an AI Copilot to help guide experiments at the European XFEL has been initiated. Initially, a survey was designed and implemented to investigate which issues beamline staff face during operation, and that they think could benefit from an AI co-pilot. The results of the survey indicated that interactions with the data acquisition (DAQ) system during beamtimes was a common source of problems. Consequently, the first use case for this tool will focus on the DAQ. To this end, a device was developed, that subscribed to events in the control system, informing us on what data a model could expect to have access to from the live system. The AI Copilot would then consist of a model to detect anomalies, which a RAG-based knowledge assistant would then forward to the Zulip chat client, enabling scientists to communicate effectively with the Copilot through an interface that has already proven efficient in other internal applications. In this contribution we present the results of the survey and initial results from classifying the control system data the model may have access to. These activities fit into a larger effort of investigating generative AI to support facility operation.
