Algorithm - A set of rules that a machine follows to learn how to do a task.

Artificial Intelligence (AI) -  A technology that simulates or mimics human intelligence with systems that learn, problem solve and make decisions. 

Big data - Massive and complex data sets that are collected quickly and studied to reveal patters and trends. 

Chatbot - A software application designed to imitate human communication through text or voice. 

Data mining -  The process of analyzing datasets in order to discover new patterns.

Deep Learning  - A learning technique that uses algorithms to improve outcomes through repetition without human intervention. 

Emergent behavior - Unexpected or unintended abilities enabled by learning patterns and rules from training data. 

Generative AI (GenAI) - Technology that creates content (text, video, code, and images) using patterns from large, trained data sets. 

Hallucination - A confident but completely wrong answer provided by an AI tool. 

Large Language Models (LLMs) - A powerful AI model that has been trained on a massive amount of text data. 

Machine Learning (ML) - The process of training from data without being explicitly programmed for every scenario. 

Natural Language Processing (NLP) - A type of AI that enables computers to understand spoked and written language. 

Neural Network (neural net) - The structure of a deep learning model. It is a computer system designed to function like the human brain.

Prompt - The text or command you give AI to generate a response.

Reinforcement Learning - A training method where AI learns by trial and error, receiving rewards for correct answers and penalties for incorrect ones. 

Supervised Learning -  A training method where structured datasets are used to train and develop an algorithm.

Unsupervised Learning - A training method where the algorithm is asked to make inferences from the datasets.