Schema for AI search: How to identify and prioritize entity gaps

Schema markup does more than power rich results. Build a knowledge graph, assess entity coverage, and find gaps in AI ...
Diginomica

Wikidata adds AI vectors to graph and knowledge bases. Here's why

Wikidata has built the semantic web backbone supporting knowledge cards in popular engines. Now, it's extending this foundation using a vector database to enhance its existing knowledge graph 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 ...

EY re-envisions RAG around multimodal knowledge graphs to improve accuracy

Retrieval-augmented generation is a standard way to ground large language models in enterprise information, but new research ...
Analytics India Magazine

Why Enterprise AI Needs to Move Beyond Traditional RAG

Traditional RAG typically retrieves relevant text from a vector database and supplies it to an LLM as context. Automation ...
Geeky Gadgets

What is a Vector Database Powering Semantic Search & AI Applications

Have you ever searched for something online, only to feel frustrated when the results didn’t quite match what you had in mind? Maybe you were looking for an image similar to one you had, or trying to ...
InfoQ

Spanner Graph: Google Introduces Graph Database on Spanner

At the recent Cloud Next conference in Tokyo, Google announced Spanner Graph, a managed feature that integrates graph, relational, search, and AI capabilities within Spanner. This new database ...