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 ...

Kinetica DB Inc., which sells a real-time analytics database for time-series and spatial workloads, took to the stage at Nvidia Corp.’s GTC conference today to unveil a new generative artificial ...

Kinetica, the real-time GPU-accelerated database for analytics and generative AI, unveiled at NVIDIA GTC its real-time vector similarity search engine that can ingest vector embeddings 5X faster than ...

COMMISSIONED: Whether you’re using one of the leading large language models (LLM), emerging open-source models or a combination of both, the output of your generative AI service hinges on the data and ...

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 ...

The latest release of the Couchbase database adds support for vector search, integration with Llamaindex and LangChain, and support for retrieval-augmented generation (RAG) techniques, all of which ...

Have you ever searched for something online, only to feel frustrated when the results didn’t quite match what you had in mind? Maybe you were looking for an image similar to one you had, or trying to ...