Learn how vector databases enable advanced AI applications, semantic search, and efficient data retrieval for unstructured datasets.

Vector databases serve as a sort of long-term memory for LLMs, such as OpenAI ’s GPT-4 and Llama from Meta. By storing and indexing the mathematical representations of pieces of text trained by the ...

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.

Parallels between our brains and vector databases go deeper than retrieval. Both excel at compression, organizing and identifying patterns.

Whether IT leaders opt for the precision of a Knowledge Graph or the efficiency of a Vector DB, the goal remains clear—to harness the power of RAG systems and drive innovation, productivity, and ...

Vector database company Qdrant believes its new search algorithm, BM42, will make RAG more efficient and cost-effective.

VCs are hungry to back vector database startups and other behind-the-scenes tech that improves AI. Vector databases store and structure data that LLMs can then pull from. Business Insider has ...

The mighty Z80 processor ran the code at astounding speed, proving retro-tech got a lot of things right A Microsoft senior ...

Startup Zilliz Inc. today debuted a new release of its flagship offering, a managed vector database called Zilliz Cloud that artificial intelligence models can use to hold information. Redwood ...

A vector is a mathematical structure that can represent documents, purchase logs and many other types of information. Storing records in this form makes it easier for AI models to understand their ...