AI Glossary
Plain-English definitions of AI terms and concepts — no technical background required.
Popular Terms
The most searched AI terms, explained simply.
LLM (Large Language Model)
AI Models
An AI model trained on massive amounts of text data to understand and generate human-like language.
Prompt
Prompt Engineering
The input or instruction you give an AI tool to get a specific response or output.
Generative AI
AI Models
AI that can create new content — text, images, audio, or video — based on patterns it has learned.
AI Agent
AI Tools & Platforms
An AI system that can perform tasks autonomously, often by using tools or making decisions on its own.
Fine-tuning
Machine Learning Basics
The process of further training an AI model on specific data to improve its performance for a particular task.
Hallucination
AI Models
When an AI generates information that sounds plausible but is factually incorrect or made up.
Browse All Terms
Explore the full glossary from A to Z.
A
AI Agent
AI Tools & PlatformsAn AI system that can perform tasks autonomously, often by using tools or making decisions on its own.
API
AI Tools & PlatformsA way for different software programs to communicate with each other, often used to connect AI tools.
B
Bias (AI Bias)
AI EthicsUnfair or skewed results from an AI model, often caused by imbalanced training data.
C
Chatbot
AI Tools & PlatformsA program that simulates conversation with users, often powered by AI.
D
Dataset
Machine Learning BasicsA collection of data used to train or test an AI model.
Diffusion Model
AI ModelsA type of AI model commonly used to generate images by gradually refining random noise.
F
Fine-tuning
Machine Learning BasicsThe process of further training an AI model on specific data to improve its performance for a particular task.
G
Generative AI
AI ModelsAI that can create new content — text, images, audio, or video — based on patterns it has learned.
GPT
AI ModelsGenerative Pre-trained Transformer — a type of AI model architecture used in tools like ChatGPT.
H
Hallucination
AI ModelsWhen an AI generates information that sounds plausible but is factually incorrect or made up.
I
Inference
Machine Learning BasicsThe process of an AI model generating output based on new input, after it has been trained.
L
LLM (Large Language Model)
AI ModelsAn AI model trained on massive amounts of text data to understand and generate human-like language.
M
Machine Learning
Machine Learning BasicsA field of AI where systems learn patterns from data instead of being explicitly programmed.
Multimodal AI
AI ModelsAI that can understand and work with multiple types of input, like text, images, and audio together.
N
No-code AI
AI Tools & PlatformsTools that let you build AI-powered apps or automations without writing code.
O
Open-source AI
AI ModelsAI models whose code and/or weights are publicly available for anyone to use or modify.
P
Prompt
Prompt EngineeringThe input or instruction you give an AI tool to get a specific response or output.
Prompt Engineering
Prompt EngineeringThe practice of crafting effective inputs to get better results from AI models.
R
RAG (Retrieval-Augmented Generation)
AI ModelsA technique where an AI model retrieves relevant information before generating a response, improving accuracy.
S
Synthetic Data
Machine Learning BasicsArtificially generated data used to train AI models when real data is limited.
T
Token
AI ModelsA piece of text (word or part of a word) that an AI model processes — used to measure input/output length and cost.
Training Data
Machine Learning BasicsThe data used to teach an AI model how to perform a task.
V
Vector Database
AI Tools & PlatformsA database designed to store and search data based on meaning/similarity, often used with AI search and RAG.