Understanding AI terminology helps you evaluate tools, follow industry conversations, and make informed decisions. Here are the terms you’ll encounter most often, explained without jargon.
Essential AI Terms
Prompt
The text you type into an AI tool. Better prompts produce better outputs. Being specific, providing context, and giving examples are the keys to good prompting.
Token
The unit AI uses to process text. Roughly 4 characters or 3/4 of a word. Token limits determine how much text an AI can read and write in one conversation. GPT-4 handles ~128K tokens; Claude handles ~200K tokens.
Hallucination
When AI generates confident but incorrect information. It happens because AI generates plausible-sounding text, not verified facts. Always fact-check important claims.
Fine-tuning
Training an existing AI model on your specific data to improve performance for your use case. Like teaching a general assistant the specifics of your industry.
RAG (Retrieval-Augmented Generation)
A technique that gives AI access to specific documents or databases when generating responses. This is how AI chatbots answer questions about your company’s specific information.
Temperature
A setting that controls how creative or predictable AI outputs are. Low temperature = more predictable, consistent outputs. High temperature = more creative, varied outputs.
For practical application, see AI Best Practices.