VentureBeat

Architectural patterns for graph-enhanced RAG: Moving beyond vector search in production

Retrieval-augmented generation (RAG) has become the de facto standard for grounding large language models (LLMs) in private data. The standard architecture — chunking documents, embedding them into a ...
CIO

Vector Database vs. Knowledge Graph: Making the Right Choice When Implementing RAG

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 ...
TechCrunch

With Neptune Analytics, AWS combines the power of vector search and graph data

There’s been a debate of sorts in AI circles about which database is more important in finding truthful information in generative AI applications: graph or vector databases. AWS decided to leave the ...
Nature

Graph Signal Processing Techniques and Applications

Graph Signal Processing (GSP) extends classical signal processing to data defined on irregular domains represented by graphs. In GSP, measurements or features are treated as signals on the vertices of ...