Vectara, an early pioneer in Retrieval Augmented Generation (RAG) technology, is raising a $25 million Series A funding round today as demand for its technologies continues to grow among enterprise ...

Much of the interest surrounding artificial intelligence (AI) is caught up with the battle of competing AI models on benchmark tests or new so-called multi-modal capabilities. But users of Gen AI's ...

A new study from Google researchers introduces "sufficient context," a novel perspective for understanding and improving retrieval augmented generation (RAG) systems in large language models (LLMs).

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 ...

A consistent media flood of sensational hallucinations from the big AI chatbots. Widespread fear of job loss, especially due to lack of proper communication from leadership - and relentless overhyping ...

RAG can make your AI analytics way smarter — but only if your data’s clean, your prompts sharp and your setup solid. The arrival of generative AI-enhanced business intelligence (GenBI) for enterprise ...

To operate, organisations in the financial services sector require hundreds of thousands of documents of rich, contextualised data. And to organise, analyse and then use that data, they are ...

Retrieval-augmented generation breaks at scale because organizations treat it like an LLM feature rather than a platform discipline. Enterprises that succeed with RAG rely on a layered architecture.