Google’s June 2025 Core Update just finished. What’s notable is that while some say it was a big update, it didn’t feel ...

Google's new Graph Foundation Model delivers up to 40 times greater precision and has been tested at scale on spam detection.

The intersection of large language models and graph databases is one that’s rich with possibilities. The folks at property graph database maker Neo4j today took a first step in realizing those ...

The addition of vectors to Neo4j now brings another way to further bring in more context to the graph database for enhanced search as well as helping to enable generative AI and large language ...

Whether IT leaders opt for the precision of a Knowledge Graph or the efficiency of a Vector DB, the goal remains clear—to harness the power of RAG systems and drive innovation, productivity, and ...

The team responsible for BioCypher accomplished precisely this by taking a big corpus of medical research papers, building a large language model around them, and then deriving a knowledge graph ...

The second limitation is the lack of large graph processing optimizations. Many official model implementations overlook certain coding details, leading to scaling issues when processing large graphs.

First, graphs can be very large: Data sizes of 10-100TB are not uncommon. ... (GNN) to generate vector space representations for the entities in the graph.

A sui generis, multi-model open source database, designed from the ground up to be distributed. ArangoDB keeps up with the times and uses graph, and machine learning, as the entry points for its ...