Vector databases power RAG, semantic search, recommendations, and memory. Learn how indexing, filtering, and hybrid retrieval ...

Companies across every industry increasingly understand that making data-driven decisions is a necessity to compete now, in the next five years, in the next 20 and beyond. Data growth — unstructured ...

Vector databases don't get as much love as their flashier counterparts, large language models (LLMs). But the startups building them are still crucial to the current AI revolution, and investors are ...

Vector databases enable semantic searches but might also store sensitive data. Learn how to build a vector database security ...

Zilliz, the company behind Milvus, the world’s most widely adopted open-source vector database, recently announced the ...

Data Cloud Vector Database will unify all business data, including unstructured data like PDFs, emails, and transcripts, with CRM data to enable grounding of AI prompts and Einstein Copilot, ...

Couchbase on Tuesday launched a new version of its database platform, highlighted by improved vector indexing and retrieval capabilities aimed at making it faster to develop enterprise-grade AI ...

In the age of generative AI (genAI), vector databases are becoming increasingly important. They provide a critical capability for storing and retrieving high-dimensional vector representations, ...

Learn how to use vector databases for AI SEO and enhance your content strategy. Find the closest semantic similarity for your target query with efficient vector embeddings. A vector database is a ...

When Edo Liberty was completing his Ph.D. in Computer Science at Yale on random projections, he could have hardly known that a decade later it would be a fundamental component of modern AI. Liberty is ...