AI Glossary

The simulation of human intelligence processes by machines, especially computer systems.

A subset of AI that provides systems the ability to automatically learn and improve from experience without being explicitly programmed.

A subset of machine learning that uses neural networks with many layers (hence 'deep') to analyze various factors of data.

Computing systems inspired by the biological neural networks that constitute animal brains, designed to recognize patterns.

A field of AI that gives computers the ability to understand text and spoken words in the same way humans can.

A type of AI model trained on vast amounts of text data to understand and generate human-like text.

The process of designing effective inputs (prompts) for AI systems to get desired outputs.

AI systems that can generate new content, such as text, images, audio, or video, based on what they've learned from existing data.

A deep learning model architecture that uses self-attention mechanisms, forming the basis for many modern language models.

The process of taking a pre-trained model and further training it on a specific dataset for a particular task.

A type of machine learning where an agent learns to make decisions by taking actions in an environment to maximize some notion of reward.

A field of AI that enables computers to derive meaningful information from digital images, videos, and other visual inputs.