To protect private information stored in text embeddings, it’s essential to de-identify the text before embedding and storing it in a vector database. In this article, we'll demonstrate how to ...

Elastic (NYSE: ESTC), the Search AI Company, today announced the availability of jina-embeddings-v5-text, a family of two small, Elasticsearch-native multilingual embedding models at 0.2B and 0.6B ...

Vector similarity search uses machine learning to translate the similarity of text, images, or audio into a vector space, making search faster, more accurate, and more scalable. Suppose you wanted to ...

Unlock the full InfoQ experience by logging in! Stay updated with your favorite authors and topics, engage with content, and download exclusive resources. Cory Benfield discusses the evolution of ...

Learn how to identify keyword cannibalization using OpenAI's text embeddings. Understand the differences between various models and make informed SEO decisions. This new series of articles focuses on ...

The emergence of vector databases and vector search for handling massive quantities of complex data have radically transformed the way AI is implemented and managed. As a specialized approach for ...

Vector databases unlock the insights buried in complex data including documents, videos, images, audio files, workflows, and system-generated alerts. Here’s how. The world of data is rapidly changing ...