Retrieval-Augmented Generation (RAG) and Large Language Models (LLMs) are two distinct yet complementary AI technologies. Understanding the differences between them is crucial for leveraging their ...
Join our daily and weekly newsletters for the latest updates and exclusive content on industry-leading AI coverage. Learn More More companies are looking to include retrieval augmented generation (RAG ...
Data integration startup Vectorize AI Inc. says its software is ready to play a critical role in the world of artificial intelligence after closing on a $3.6 million seed funding round today. The ...
BERLIN & NEW YORK--(BUSINESS WIRE)--Qdrant, the leading high-performance open-source vector database, today announced the launch of BM42, a pure vector-based hybrid search approach that delivers more ...
In 2026, contextual memory will no longer be a novel technique; it will become table stakes for many operational agentic AI deployments. At the beginning of the modern generative AI era, purpose-built ...
Teradata’s partnership with Nvidia will allow developers to fine-tune NeMo Retriever microservices with custom models to build document ingestion and RAG applications. Teradata is adding vector ...
RAG is a pragmatic and effective approach to using large language models in the enterprise. Learn how it works, why we need it, and how to implement it with OpenAI and LangChain. Typically, the use of ...
Qdrant, the developer of a high-performance, open-source vector database, today announced it has raised $28 million in early-stage funding led by Spark Capital enhance its offering for generative ...