Native integrations reduce setup time and ongoing maintenance by making it easy to ingest, index, and continuously ...

A core element of any data retrieval operation is the use of a component known as a retriever. Its job is to retrieve the relevant content for a given query. In the AI era, retrievers have been used ...

In today’s data-driven world, efficient data retrieval has become critical for organizations striving to maintain a competitive edge. Slow retrieval processes and high operational costs are common ...

High-performance open-source vector database Qdrant today announced the launch of BM42, a new pure vector-based hybrid search approach for modern artificial intelligence and retrieval-augmented ...

OpenAI has acquired Rockset, developer of a high-powered data search and analytics database that will become part of the data retrieval infrastructure underlying its generative AI software products.

Retrieval-augmented generation, or RAG, integrates external data sources to reduce hallucinations and improve the response accuracy of large language models. Retrieval-augmented generation (RAG) is a ...

RAG is an approach that combines Gen AI LLMs with information retrieval techniques. Essentially, RAG allows LLMs to access external knowledge stored in databases, documents, and other information ...

Forward-looking: Researchers around the world are embracing DNA-based storage right now. Mixing digital data and biology could bridge the best of both worlds, though a few challenges are still slowing ...

AI’s power is premised on cortical building blocks. Retrieval-Augmented Generation (RAG) is one of such building blocks enabling AI to produce trustworthy intelligence under a given condition.