One plain-English sentence per term — then why it actually matters for your business.
Agentic AI refers to AI systems that can plan, take multi-step actions, and use tools autonomously to achieve a goal, rather than just responding to a single prompt.
Core ConceptsAI hallucination is when an AI model confidently generates information that sounds plausible but is factually incorrect or entirely made up.
Core ConceptsArtificial Intelligence (AI) is the field of computer science focused on building systems that can perform tasks — like recognizing speech, making decisions, or generating text — that normally require human intelligence.
Training & Fine-tuningFine-tuning is the process of further training an existing AI model on a smaller, specific dataset so it performs better on a particular task or domain.
Model TypesGenerative AI refers to AI systems that create new content — text, images, audio, video, or code — rather than just analyzing or classifying existing data.
Model TypesA Large Language Model (LLM) is an AI model trained on massive amounts of text that can understand and generate human-like language, such as GPT, Claude, or Gemini.
Core ConceptsMachine Learning (ML) is a branch of AI where systems learn patterns from data and improve at a task without being explicitly programmed for every rule.
Core ConceptsA neural network is a machine learning model structure loosely inspired by the human brain, made of layers of connected nodes that learn to recognize patterns in data.
Prompt EngineeringPrompt Engineering is the practice of crafting clear, specific instructions for an AI model to get accurate, useful, and consistent responses.
Model TypesRetrieval-Augmented Generation (RAG) is a technique that lets an AI model look up relevant information from your own documents before answering, instead of relying only on what it was trained on.
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