An AI model, an AI API, and an AI application are different layers of an AI system. Understanding how they work together is essential for building real-world AI applications.
A context window defines how much information an LLM can process at one time. Learn what tokens and context windows are, why they matter, and how they affect AI application performance.
Semantic Search finds information based on meaning and context rather than exact keywords. Learn how embeddings and vector search make modern AI-powered search more intelligent.
Vector databases store and search numerical embeddings efficiently, making them essential for RAG, semantic search, recommendation systems, and modern AI applications.
Retrieval-Augmented Generation (RAG) combines information retrieval with Generative AI to help an LLM answer questions using relevant external information. Learn how RAG works, why it is useful, and when you should choose RAG for an AI application.