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 ...

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

All the large language model (LLM) publishers and suppliers are focusing on the advent of artificial intelligence (AI) agents and agentic AI. These terms are confusing. All the more so as the players ...

Performance. Top-level APIs allow LLMs to achieve higher response speed and accuracy. They can be used for training purposes, as they empower LLMs to provide better replies in real-world situations.

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 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).

The hype and awe around generative AI have waned to some extent. “Generalist” large language models (LLMs) like GPT-4, Gemini (formerly Bard), and Llama whip up smart-sounding sentences, but their ...