Foundation models are multi-dataset and multi-task machine learning methods that once pre-trained can be fine-tuned for a large variety of downstream applications. The successful development of such general-purpose models for physics data would be a major breakthrough as they could improve the achievable physics performance while at the same time drastically reduce the required amount of...
- first prototype of our fully local OpenAI alternative
- first integrations
- what we plan next
Based on the LLM (Large Language Model) and RAG (Retrieval-Augmented Generation) technologies, the FS-EC group has developed a technical documentation and code retrieval Q&A AI Agent. This Agent will be further enhanced by integrating historical Q&A information from the ticket system, aiming to co-develop a professional Q&A AI Agent for beam scientists and users.
This talk presents applications of Large Language Model (LLM)-powered tools for enhancing daily accelerator operation. First, an overview of LLM tools that utilize Retrieval Augmented Generation (RAG) techniques is provided, demonstrating how existing knowledge bases, such as electronic logbooks, can be leveraged. Additionally, an advanced ReAct prompting approach (Reasoning and Action) is...
