The latest trends in software development from the Computer Weekly Application Developer Network. This is a guest post for the Computer Weekly Developer Network (CWDN) written by Chris Mahl in his ...

Retrieval-Augmented Generation (RAG) is rapidly emerging as a robust framework for organizations seeking to harness the full power of generative AI with their business data. As enterprises seek to ...

Vectara Inc., a startup that helps enterprises implement retrieval-augmented generation in their applications, has closed a $25 million early-stage funding round to support its growth efforts. The ...

Unlock the full InfoQ experience by logging in! Stay updated with your favorite authors and topics, engage with content, and download exclusive resources. Cory Benfield discusses the evolution of ...

Retrieval Augmented Generation (RAG) is supposed to help improve the accuracy of enterprise AI by providing grounded content. While that is often the case, there is also an unintended side effect.

If you looked under the hood of generative AI (GenAI) technologies over the last year or so, you probably came across the concept of retrieval augmented generation (RAG). RAG has gained a lot of buzz, ...

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 ...

We’ve been living through the generative AI boom for nearly a year and a half now, following the late 2022 release of OpenAI’s ChatGPT. But despite transformative effects on companies’ share prices, ...

COMMISSIONED: Retrieval-augmented generation (RAG) has become the gold standard for helping businesses refine their large language model (LLM) results with corporate data. Whereas LLMs are typically ...

Many medium-sized business leaders are constantly on the lookout for technologies that can catapult them into the future, ensuring they remain competitive, innovative and efficient. One such ...