The decades-long pursuit to capture, organize and apply the collective knowledge within an enterprise has failed time and again because available software tools were incapable of understanding the ...

Retrieval-augmented generation breaks at scale because organizations treat it like an LLM feature rather than a platform ...

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.

Enterprises are increasingly adopting hybrid AI models that combine generative AI with retrieval, reasoning, and memory modules for specific use cases. RAG fits perfectly into this architecture by ...

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 ...

AI tends to make things up. That’s unappealing to just about anyone who uses it on a regular basis, but especially to businesses, for which fallacious results could hurt the bottom line. Half of ...

There’s growing interest in making AI more practical, especially through techniques like retrieval-augmented generation (RAG). And it’s not just AI developers or enterprise tech teams who see the ...