Turing Test

Artificial Intelligence

The simulation of human intelligence processes by computer systems, including learning, reasoning, and self-correction.

Artificial General Intelligence

A hypothetical form of AI that possesses the ability to understand, learn, and apply knowledge across any intellectual task a human can perform.

Artificial Narrow Intelligence

AI systems designed and trained for a specific task or narrow range of tasks, such as image recognition or language translation.

Artificial Superintelligence

A theoretical level of AI that surpasses human cognitive abilities across all domains, including creativity and social intelligence.

AI Ethics

The branch of ethics examining moral issues surrounding the development, deployment, and impact of artificial intelligence on society.

Cognitive Computing

Computing systems that simulate human thought processes using self-learning algorithms, data mining, pattern recognition, and natural language processing.

Ontology

A formal representation of knowledge as a set of concepts, categories, and relationships within a specific domain.

Semantic Web

An extension of the World Wide Web that enables machines to interpret and process web content through standardised semantic metadata.

Chinese Room Argument

A thought experiment by John Searle arguing that executing a program cannot give a computer genuine understanding or consciousness.

Weak AI

AI designed to handle specific tasks without possessing self-awareness, consciousness, or true understanding of the task domain.

Strong AI

A theoretical form of AI that would have consciousness, self-awareness, and the ability to truly understand rather than simulate understanding.

Symbolic AI

An approach to AI that uses human-readable symbols and rules to represent problems and derive solutions through logical reasoning.

A semiconductor designed specifically for AI and machine learning computations, optimised for parallel processing and matrix operations.

A centralised repository for storing, versioning, and managing trained AI models across an organisation.

The principle of ensuring AI systems make equitable decisions without discriminating against any group based on protected attributes.

A technique combining information retrieval with text generation, allowing AI to access external knowledge before generating responses.

A metric for evaluating the quality of machine-generated text by comparing it to reference translations or texts.

The process of determining cause-and-effect relationships from data, going beyond correlation to establish causation.

Architectures that enable AI agents to store, retrieve, and reason over information from past interactions, providing continuity and personalisation across conversations.

A method of problem-solving that represents all possible states of a system and searches for a path from initial to goal state.