Glossary

The world of Artificial Intelligence has a lot of jargon. Here are a few terms that you should know as you work through this learning experience.

Artificial Intelligence (AI):

The broad field of computer science that enables machines to simulate human intelligence, including learning, problem-solving, perception, and language understanding.

Machine learning (ML):

A subset of AI that allows systems to learn from data without being explicitly programmed. It involves algorithms that can identify patterns and make predictions.

Generative AI:

A type of AI that can create new, original content (like text, images, audio, or code) that resembles real-world data it was trained on.

Large language models (LLMs):

A type of Generative AI specifically designed to understand, generate, and process human language, often trained on vast amounts of text data.

Neural networks:

Computational models inspired by the human brain, consisting of interconnected nodes (neurons) that process and transmit information.

Natural language processing

The processing of the interactions between computer and human language.

Data set

A collection of data; a machine-readable file of related records.

Training data:

The data set used to teach an AI model.

Algorithms:

A set of rules or instructions followed by a computer to solve a problem.

Hallucinations

Responses generated by AI that contain false or misleading information but are represented as facts.