2nd GSI/FAIR AI Workshop

Abstract: AI-assisted operation of the Super-FRS will be tested during the commissioning activities in 2027. The approach treats the language model as a reasoning engine rather than a knowledge base: it retrieves from the facility's own data, computes with tested tools, and cites what it used. The data itself already exists — S-FRSRoot delivers physics-grade output from the DAQ streams, and the EPICS layer delivers the machine state. Everything runs on local hardware, so no data leaves GSI.
Two agents are in operation today. The first answers questions from the PID detector documentation and gives the page it came from. The second investigates EPICS slow-control parameters through a fixed set of read-only analysis tools, so every number it reports comes from a real measurement.
Commissioning will put both under real conditions, and it will also shape the next generation: predictive maintenance on an archived machine state, a shift assistant that carries context across hand-overs, AI-assisted beam tuning, and an agent that writes and compiles S-FRSRoot analysis classes on request, so that a new observable costs a sentence instead of a week of coding.
The same recipe applies to any experiment that has documentation, a control system, and an analysis framework.