The simulation of human intelligence processes by machines, especially computer systems. These processes include learning, reasoning, and self-correction.

A subset of AI where systems learn from data without explicit programming. Algorithms identify patterns and make predictions based on input data.

A subset of ML using artificial neural networks with multiple layers (hence "deep") to analyze data and extract complex features. Often used for image recognition, natural language processing, etc.

ML algorithm trained on labeled data; the algorithm learns to map inputs to outputs based on the provided examples.

ML algorithm trained on unlabeled data; the algorithm identifies patterns and structures in the data without explicit guidance.

ML algorithm learns through trial and error by interacting with an environment and receiving rewards or penalties.

AI branch focusing on enabling computers to understand, interpret, and generate human language.

AI branch enabling computers to "see" and interpret images and videos.

AI systems designed to mimic the decision-making ability of a human expert in a specific domain.

The design, construction, operation, and application of robots. Often integrated with AI for autonomous behavior.

Computing systems inspired by the biological neural networks that constitute animal brains. Used in ML and DL.

A set of rules or steps used to solve a problem or complete a task. Essential to AI systems.

The process of discovering patterns and insights from large datasets. Crucial for training AI models.

Extremely large and complex datasets that require specialized tools and techniques for analysis. Often used to train AI models.

Systematic and repeatable errors in AI systems that can lead to unfair or discriminatory outcomes. Often arises from biased training data.

The development of AI systems whose decisions and reasoning are transparent and understandable to humans.

AI systems capable of generating new content, such as text, images, or music.

AI-powered programs designed to simulate human conversation.

A test of a machine's ability to exhibit intelligent behavior equivalent to, or indistinguishable from, that of a human.

The study of ethical considerations related to the development and deployment of AI systems.