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.
Vector databases store and search numerical embeddings efficiently, making them essential for RAG, semantic search, recommendation systems, and modern AI applications.
AI Agents go beyond simple chatbots by understanding goals, planning tasks, using tools, and taking actions. Learn how AI Agents work and how they differ from traditional chatbots.
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.