Databricks and Tonic.ai have partnered to simplify the process of connecting enterprise unstructured data to AI systems to reap the benefits of RAG. Learn how in this step-by-step technical how-to.

Ragie Corp., a new startup that helps developers build retrieval-augmented generation applications, launched today with $5.5 million in seed funding. Craft Ventures, Saga VC, Chapter One and Valor ...

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 ...

The advent of transformers and large language models (LLMs) has vastly improved the accuracy, relevance and speed-to-market of AI applications. As the core technology behind LLMs, transformers enable ...

Want smarter insights in your inbox? Sign up for our weekly newsletters to get only what matters to enterprise AI, data, and security leaders. Subscribe Now When large language models (LLMs) emerged, ...

The rapid advancements in artificial intelligence (AI) have led to the development of powerful large language models (LLMs) that can generate human-like text and code with remarkable accuracy. However ...

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 ...

Retrieval-augmented generation—or RAG—is an AI strategy that supplements text generation with information from private or proprietary data sources, according to Elastic, the search AI company. RAG ...

Retrieval-augmented generation (RAG) has become a go-to architecture for companies using generative AI (GenAI). Enterprises adopt RAG to enrich large language models (LLMs) with proprietary corporate ...