Building a RAG application with Llama 3.1 and pgvector

Tech giants are in an AI arms race, with OpenAI's closed models competing against Meta's open-source Llama 3.1. The post demonstrates how to build a Retrieval-Augmented Generation (RAG) application using Llama 3.1 and pgvector, leveraging Postgres for vector databases. It covers creating embeddings, setting up a vector database with Neon, and deploying an AI app that provides inspirational quotes, highlighting the power and cost-effectiveness of open-source AI models.