With demand for enterprise retrieval augmented generation (RAG) on the rise, the opportunity is ripe for model providers to offer their take on embedding models. French AI company Mistral threw its ...

Agentic RAG lets an AI system plan, reformulate, and iterate over retrieval rather than making one fixed search before generation. This guide explains the mechanism, trade-offs, evaluation, and ...

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 ...

What if the key to unlocking next-level performance in retrieval-augmented generation (RAG) wasn’t just about better algorithms or more data, but the embedding model powering it all? In a world where ...

Chroma’s latest large language model, Context-1, introduces a new benchmark for retrieval-augmented generation (RAG) by combining precision, speed and cost-efficiency. Developed as a fine-tuned ...

In the past two years, businesses have been trying to fit large language models (LLMs) into support, analytics, development, and internal automation like never before. Along with the increasing ...

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 ...