AI Glossary
Confused by AI jargon? We explain the most common terms in plain English so you can make better decisions.
LLM (Large Language Model)
An AI system trained on massive amounts of text data to understand and generate human-like language. Examples include GPT-4 (OpenAI) and Claude (Anthropic).
Generative AI
A type of AI that can create new content, such as text, images, audio, or video, based on the data it was trained on.
Prompt Engineering
The art of crafting specific instructions (prompts) to get the best possible output from an AI model.
RAG (Retrieval-Augmented Generation)
A technique that gives an AI model access to external data (like your company's documents) to provide more accurate and up-to-date answers.
Context Window
The maximum amount of information (tokens) an AI model can "remember" or process at one time during a conversation.
Hallucination
When an AI model generates information that sounds confident but is factually incorrect or nonsensical.
Freemium
A pricing model where the basic features are free to use, but advanced features or higher usage limits require a paid subscription.
Token
The basic unit of text that an LLM processes. A token can be a word, a part of a word, or even a single character.
NLP (Natural Language Processing)
A field of AI focused on the interaction between computers and human language, enabling machines to read, understand, and respond to text.