The latest update of Bloom 2.3 now includes Graph Data Science features, allowing users to select from various algorithms and utilize the GDS plugin or AuraDS on self-managed databases. This development enables experimentation and visualization of supply chain data using Neo4j's Graph Data Science and Bloom, as demonstrated by Zach Blumenfeld in his blog series. Additionally, local GraphSummits are being held in EMEA and APAC regions, providing opportunities for attendees to engage with the community and learn about the capabilities of graph technology. Various tutorials and projects have been created to help developers get started with Neo4j and graph databases, including a Java-based AWS Lambda application and a .NET Core C# microservice. The use of graph databases is also highlighted as a solution to problems that other databases cannot address, such as surface critical information and analyzing semantic structure.