LLM integration into EPICS

The utilization of large language models (LLMs) such as ChatGPT has seen a remarkable increase in various fields over the past few years. These models have demonstrated their versatility and capability in understanding and generating human-like text, making them invaluable tools in numerous applications. In this project, we explore the integration of a LLM into the Experimental Physics and Industrial Control System (EPICS). The primary focus of this integration is to employ the LLM for advanced image processing and spatial analysis on images obtained from the beamlines. By leveraging the capabilities of the LLM, we aim to enhance the accuracy and efficiency of image interpretation, enabling more precise data analysis and decision-making within the EPICS framework. This integration not only showcases the potential of LLMs in scientific and industrial applications but also sets the stage for future advancements in automated control systems.

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Publication Details

Journal
OSTI OAI (U.S. Department of Energy Office of Scientific and Technical Information)
Published
2024-10-25
DOI
https://doi.org/10.18429/jacow-linac2024-thpb040
Primary Topic
Mathematics, Computing, and Information Processing
Type
article
Field-Weighted Citation Impact
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article

LLM integration into EPICS

Alex Sobhani, Ethan Adams
OSTI OAI (U.S. Department of Energy Office of Scientific and Technical Information)
Mathematics, Computing, and Information Processing
article

LLM integration into EPICS

Alex Sobhani, Ethan Adams
article en

Abstract

The utilization of large language models (LLMs) such as ChatGPT has seen a remarkable increase in various fields over the past few years. These models have demonstrated their versatility and capability in understanding and generating human-like text, making them invaluable tools in numerous applications. In this project, we explore the integration of a LLM into the Experimental Physics and Industrial Control System (EPICS). The primary focus of this integration is to employ the LLM for advanced image processing and spatial analysis on images obtained from the beamlines. By leveraging the capabilities of the LLM, we aim to enhance the accuracy and efficiency of image interpretation, enabling more precise data analysis and decision-making within the EPICS framework. This integration not only showcases the potential of LLMs in scientific and industrial applications but also sets the stage for future advancements in automated control systems.

OSTI OAI (U.S. Department of Energy Office of Scientific and Technical Information)
Oak Ridge National Laboratory (US)
Openalex Percentile: Top 80%
Mathematics, Computing, and Information Processing
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