Key applications of vector databases include semantic search, retrieval-augmented generation (RAG) for AI systems, and similarity search for recommendations and anomaly detection.

In this work we explore the use of semantic similarity techniques to enhance the management of Non-Conformity in emerging industrial environments. Small and new companies lack historical data which ...

MEVD is currently a separate package with no relation to Microsoft.Extensions.AI, which is where embedding-related types such as IEmbedding and IEmbeddingGenerator live. Because of this, MEVD doesn't ...

Elastic, the Search AI Company, today announced the Elasticsearch Open Inference API now supports Hugging Face models with native chunking through the integration of the semantic_text field. With ...

Sentence-Level Semantic Internal Links For SEO How to do internal linking for SEO in a way that complements Google's semantic understanding of content ...

Vector databases and search aren’t new, but vectorization is essential for generative AI and working with LLMs. Here's what you need to know. One of my first projects as a software developer was ...