AI Fundamentals

An AI system is a complete machine-based setup that takes input, uses one or more AI models to produce outputs such as predictions, content, recommendations or decisions, and acts on them within a real environment.

An AI model is a program that has learned patterns from data and uses them to turn new input into an output, such as a prediction, a label or generated text. It is the trained 'brain' inside most AI products.

Machine intelligence is the ability of a machine to learn, reason and act on information in ways that look intelligent. The term is often used as a synonym for artificial intelligence, with a stronger focus on learning systems.

Superintelligence is a hypothetical form of AI that would far exceed the best human minds in almost every area, including science, strategy and social skills. It is the level beyond general AI and a central topic in AI safety.

AGI, or artificial general intelligence, is the term AI labs and researchers use for a system that matches or beats human ability across most intellectual tasks. It is the stated goal of several major AI companies, but definitions and timelines vary widely.

General AI is the idea of a machine that can learn and perform any intellectual task a human can, and transfer what it learns from one area to another. It sits between narrow AI and superintelligence and does not exist yet.

Narrow AI, also called weak AI, is artificial intelligence built to do one specific task or a small set of related tasks. Every AI system in use today, from spam filters to chatbots, is narrow AI.

Artificial intelligence (AI) is the field of building computer systems that perform tasks we normally link to human thinking, such as understanding language, recognising images, making predictions and solving problems.