Chroma’s Context-1 is a 20B retrieval-augmented model that beats ChatGPT 5 on search, using agentic loops to improve relevance at low latency.

What is Retrieval-Augmented Generation (RAG)? Retrieval-Augmented Generation (RAG) is an advanced AI technique combining language generation with real-time information retrieval, creating responses ...

In this episode of eSpeaks, Jennifer Margles, Director of Product Management at BMC Software, discusses the transition from traditional job scheduling to the era of the autonomous enterprise. eSpeaks’ ...

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 ...

In the era of generative AI, large language models (LLMs) are revolutionizing the way information is processed and questions are answered across various industries. However, these models come with ...

Retrieval Augmented Generation (RAG) is a groundbreaking development in the field of artificial intelligence that is transforming the way AI systems operate. By seamlessly integrating large language ...

Plate Lunch Collective was built for AI search. One year in, the Hawaii-based agency helps brands in North America get ...

Dark Matter launches Ask Aiva, an AI assistant embedded in the Empower LOS that lets lenders query origination data in plain ...

How to implement a local RAG system using LangChain, SQLite-vss, Ollama, and Meta’s Llama 2 large language model. In “Retrieval-augmented generation, step by step,” we walked through a very simple RAG ...