AI Glossary

Here are some key terms and definitions in the field of Artificial Intelligence.

Artificial Intelligence (AI)

The field of computer science that focuses on creating intelligent machines that can perform tasks that typically require human intelligence.

Artificial General Intelligence (AGI)

A hypothetical type of AI that can perform any intellectual task that a human can, and potentially surpass human intelligence.

Artificial Narrow Intelligence (ANI)

The current state of AI, where machines are designed to perform specific tasks, such as recognizing faces or playing games, but are not capable of general intelligenc

Deep Learning (DL)

A subset of ML that uses neural networks with multiple layers to learn and extract complex features from data.

Machine Learning (ML)

A set of algorithms that are modeled after the structure and function of the human brain, used for tasks such as image and speech recognition, natural language processing, and more.

Natural Language Processing (NLP)

A branch of AI that deals with the interaction between computers and human languages, used for tasks such as sentiment analysis, chatbots, and language translation.

Neural Networks (NN)

A subfield of AI that involves training algorithms to learn patterns and make predictions based on data, without being explicitly programmed.

Reinforcement Learning (RL)

A type of Machine Learning where an agent learns to interact with an environment and maximize a reward signal through trial-and-error.


The field of designing, building, and programming robots, which are autonomous or semi-autonomous machines that can perform a wide range of tasks.

Supervised Learning

A type of Machine Learning where the algorithm is trained on labeled data, with the goal of making accurate predictions on new, unseen data.

Unsupervised Learning

A type of Machine Learning where the algorithm is trained on unlabeled data, with the goal of finding patterns and structure within the data.