Going beyond simple Retrieval-Augmented Generation 

What is Retrieval-Augmented Generation (RAG)?  Retrieval-Augmented Generation (RAG) has become a powerful method for grounding large language models (LLMs) in content tailored to specific domains. In essence, RAG systems allow users to index a body of documents and ask questions concerning the content of those documents in natural language. The system responds by first retrieving […]

The LLM data dilemma: Ocean of dirt or drop of gold? 

By Dr. Toms Bergmanis, AI Researcher at Tilde Building AI systems capable of understanding and generating human language requires vast amounts of language data. This data is the foundation for an LLM’s ability to comprehend and produce human-like language. However, the cliche that not all data is created equal stands true here. So, this distinction […]