AI Glossary
Plain-language definitions for the AI landscape.
A reference for individuals and teams getting up to speed with confidence.
Plain-Language Glossary
Speak the language of AI - without the jargon.
- AI (Artificial Intelligence)
- Software systems that perform tasks typically requiring human intelligence - like generating text, recognizing patterns, or making predictions.
- LLM (Large Language Model)
- An AI model trained on vast text data to understand and generate human-like language. Examples include ChatGPT and Claude.
- Prompt
- The instruction or question you give an AI tool. Better prompts produce better results.
- Hallucination
- When an AI generates output that sounds confident but is factually wrong. Always review before relying on AI output.
- Fine-tuning
- Adapting a general AI model to your specific use case, voice, or domain by training it on additional examples.
- RAG (Retrieval-Augmented Generation)
- A technique that lets AI answer questions using your own documents instead of relying only on its training data.
- Guardrails
- Rules and review steps that constrain how AI is used - to protect quality, safety, and compliance.
- Human-in-the-loop
- A workflow where a person reviews or approves AI output before it's used in a real decision or sent to a real audience.
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