By reducing the need to structure data, vector databases can speed up generative AI training times to dramatically improve our productivity.

How to build a local retrieval-augmented generation application using Postgres, the pgvector extension, Ollama, and the Llama 3 large language model.

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.

As AI transforms search, understanding vectors is key to staying visible. Here’s how to optimize your content for this new era of SEO.

Vector Databases excel in conducting large-scale similarity searches and streamlining data management for cutting-edge AI applications. Their key advantage lies in supporting specialized vector ...

Data preparation and structuring: Before feeding your data into a vector database, ensure it is properly formatted and structured.

Redis has recently announced the addition of Vector Set, a data type designed for vector similarity and a new option for AI applications. This new data type marks the first major contribution from ...