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Speaker
Description
The ATLAS Collaboration is composed of around 6,000 scientists, engineers, developers, students and administrators, with decades of institutional documentation spread across wikis, code docs, meeting agendas, recommendations, publications, tutorials, and project management systems. With the advent of retrieval augmented generation (RAG) and sophisticated large language models (LLMs) such as GPT-4, there is now an opportunity to produce a “front door” to this intimidatingly large corpus. ChATLAS is an attempt to provide this entrypoint, as ATLAS’ official AI assistant and search system. In this contribution, we review the past year of developments, present the latest updates to the system, and introduce ongoing work to improve back-end performance, agentic information gathering, and science-centric design components.
