The text discusses a project at Neo4j aimed at harnessing large language models (LLMs) with graph database technology, specifically knowledge graphs. The goal is to enhance the accuracy, transparency, and predictability of LLM output by integrating it with graph databases. Two initial use cases are identified: developing a natural language interface for knowledge graphs, which simplifies data selection, querying, and processing, and creating knowledge graphs from unstructured data sources, such as text documents. The project aims to improve the interaction between users and their connected data using Neo4j and LLMs, with prototypes to be developed in the future. The project is openly documented on a GitHub repository, where updates will be posted by the development team.