RAG Isn’t a Modeling Problem. It’s a Data Engineering Problem.
Argues that RAG system failures stem from data engineering issues like fragmented data and governance, not from model or vector database choices.
Argues that RAG system failures stem from data engineering issues like fragmented data and governance, not from model or vector database choices.
A simple explanation of Retrieval-Augmented Generation (RAG), covering its core components: LLMs, context, and vector databases.
Weekly tech digest covering Azure OpenAI architecture, vector databases, AI anomaly detection, and an LLM self-cloning article.
Interview with Frank Liu on vector databases, embeddings, his career in ML/hardware, and work culture differences between China and the US.