AI Glossary

Essential artificial intelligence terms explained simply for business decision makers.

A

Interface allowing applications to communicate with each other. APIs enable integrating AI features into your existing tools.

Computer program capable of simulating conversation with a human user, often used for automated customer service.

Subdomain of machine learning using deep neural networks to learn complex representations of data.

Process of adapting a pre-trained AI model to a specific use case by retraining it on your company's own data.

Language model architecture developed by OpenAI, capable of generating coherent and contextual text.

Phenomenon where an AI model generates false or invented information presented as true. Important to monitor in critical applications.

Large-scale language model trained on vast amounts of text, capable of understanding and generating natural language.

Branch of AI enabling machines to learn from data without being explicitly programmed for each task.

AI domain focused on interaction between computers and human language. Used for text understanding and generation.

Technology that converts images of text into editable text data usable by software.

Instruction or query sent to an AI model to obtain a response. Prompt quality directly influences response quality.

Technique combining information retrieval from a knowledge base with AI text generation for more accurate responses.

Profitability indicator measuring gain relative to initial investment. Crucial for evaluating the relevance of an AI solution.

Basic unit used by language models to process text. A token can represent a word, part of a word, or a character.