vector-databases

Explore Retrieval-Augmented Generation (RAG), a powerful technique that enhances Large Language Models (LLMs) by grounding their responses in external, up-to-date, and domain-specific information, mitigating hallucinations and improving factual accuracy. This lesson covers its core components, workflow, and practical considerations.

Dive into the world of vector databases, specialized systems designed to store and query high-dimensional vector embeddings efficiently. Learn how these databases power semantic search, recommendation systems, and large language model applications by finding semantically similar data points at scale.