Speaker
Description
Modern accelerators face data challenges exceeding manual analysis. Fragmented architectures (e.g., EPICS) further hinder ML model generalization. We present Project Poseidon, a unified platform designed to standardize large time-series analysis for Foundation Models and Autonomous Agents.
Poseidon's control-system-agnostic framework includes a unified database, modular analysis engine, and facility adoption layers. This decoupling enables multi-facility data aggregation, essential for training Large Observation Models (LOMs). We discuss Poseidon's role in enabling agentic workflows to monitor large systems exceeding 50,000+ variables, detect complex correlations, and autonomously trigger corrections, shifting operations to intelligent, predictive oversight.
| In which format do you inted to submit your paper? | LaTeX |
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