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.
A Large Language Model (LLM) is an AI model trained on large amounts of text to understand and generate human-like language. Learn what LLMs are, how they work, how they are trained, and where they are used, with simple, real-world examples.
Prompt Engineering is the process of designing clear and effective instructions for AI models. Learn what prompt engineering is, why it matters, and how better prompts can produce more accurate and useful AI responses.
Generative AI can create text, images, audio, video, and code from simple instructions. But how does it actually generate this content? This guide explains the basic process of Generative AI in simple language with practical examples.
Artificial Intelligence, Machine Learning, and Deep Learning are closely related technologies, but they are not the same thing. This guide explains their differences with simple examples so anyone can understand how they work together.
