It won’t magically make bad data good.It won’t remove all hallucinations.It won’t replace judgment. Read the full article: Building a Graph-First RAG Taught Me
A new approach to Retrieval-Augmented Generation (RAG) called Graph-First RAG emphasizes that while LLMs are powerful, they cannot overcome fundamental data quality issues or replace human judgment. This method highlights that the trustworthiness of LLM outputs is intrinsically linked to the quality and structure of the underlying data, rather than solely relying on the model's capabilities. AI
IMPACT Highlights that the effectiveness of RAG systems is fundamentally limited by data quality, urging a focus on data curation over model-centric solutions.