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.