Recent advancements in R have significantly simplified the integration of large language models (LLMs) into data workflows. This session offers a practical overview of how LLMs can be applied in R through a curated set of tools and packages. We highlight several LLM-related packages that boost productivity, support AI-assisted programming, and enable advanced tools such as retrieval-augmented generation (RAG). Real-world examples and demo are provided to demonstrate practical usage. This session is tailored for R users seeking to enhance their workflows with AI-powered capabilities and help illustrate how current available LLM-related package can work.
Mia Chen | Peng Zhang
CIMS Global | CIMS Global
Emerging trend of LLM development in R and implementation
Recent advancements in R have significantly simplified the integration of large language models (LLMs) into data workflows. This session offers a practical overview of how LLMs can be applied in R through a curated set of tools and packages. We highlight several LLM-related packages that boost productivity, support AI-assisted programming, and enable advanced tools such as retrieval-augmented generation (RAG). Real-world examples and demo are provided to demonstrate practical usage. This session is tailored for R users seeking to enhance their workflows with AI-powered capabilities and help illustrate how current available LLM-related package can work.