AI Glossary

Essential artificial intelligence terms explained simply for business decision makers.

A

API (Application Programming Interface)

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

C

Chatbot

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

D

Deep Learning

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

F

Fine-tuning

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

G

GPT (Generative Pre-trained Transformer)

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

H

Hallucination

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

L

LLM (Large Language Model)

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

M

Machine Learning

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

N

NLP (Natural Language Processing)

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

O

OCR (Optical Character Recognition)

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

P

Prompt

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

R

RAG (Retrieval-Augmented Generation)

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

T

Token

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