Neo4j AuraDB is a cloud-based graph database service that enables users to load dump files from various sources, including Neo4j desktop and Sandbox. The company has recently released GDS 1.7.0, which introduces machine learning pipelines for graph native link prediction, making it easier for users to define and apply link prediction pipelines. Additionally, a new course on Graph Data Modeling is available, covering concepts of graph modeling and how to refactor existing models. The company also provides tutorials on Neo4j performance architecture, tuning, and creating clinical knowledge graphs with Spark NLP & Neo4j. Furthermore, Michael Hunger will show users how to get their dump files loaded into AuraDB free, while a deep dive into Neo4j link prediction pipeline and FastRP embedding algorithm is available for those interested in learning more about link predictions.