40+ Artificial Intelligence Definitions, Industry Technology and Explanations

Learn common Artificial Intelligence technologies (AI, ML, NLP) terminology.

Our artificial intelligence technology glossary is a complete AI 101 guide to help you understand this new technology by explaining commonly used terms and their meanings.

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Adaptive Algorithm

An algorithm that changes its behavior at the time it is run, based on information available and on a prior defined reward mechanism.


A sequence of instructions or rules which tells a computer what to do, whether that’s completing a task or solving a problem. A number of logical operations can be chain together to achieve complicated tasks, calculations, procession or reasoning.


An Application Programming Interface (API), is a set of functions and procedures for building software. It makes it easier to develop a computer program by providing all the building blocks, which are then put together by the developer.

Artificial Intelligence (Singular Technology)

A machine’s capability to reproduce cognitive functions otherwise associated with man, such as problem solving, discovery and learning.

Artificial Intelligence (Collective Disciplinary Field)

A disciplinary field of computer science concentrated on intelligent agents that perceive and act to satisfy an objective without being explicitly programmed how to do so.

An algorithm that attempts to mimic the human brain, with layers of connected “neurons” sending information to each other.


Autonomous refers to the ability to act independently without any outside control. An AI system is autonomous if it doesn’t need help from people. Driverless cars utilise autonomy; the cars do not require humans to navigate, steer, brake or accelerate.

Black Box

A system which can be viewed in terms of its inputs and outputs, but the observer has no knowledge of what’s happening on the inside. A black box AI system could be mistaken for human intellect.

When an algorithm’s decision-making process or output can’t be easily explained by the computer or the researcher behind it.


Any of the various communication platforms where a chatbot can go live such as Facebook Messenger, Viber, WhatsApp, Skype etc.


A computer program or an artificial intelligence that conducts a conversation via auditory or textual methods.

Cognitive Computing

A computerized model that mimics the way the human brain thinks. It involves self-learning through the use of data mining, natural language processing, and pattern recognition.

Computer Vision

An interdisciplinary field that deals with how computers can be made to gain high-level understanding from digital images or videos. From the perspective of engineering, it seeks to automate tasks that the human visual system can do.

Conversational AI

A branch of artificial intelligence that focuses on interpreting human language and communicating with humans. It includes advanced features of AI such as NLP, machine learning, and neural networks.

Conversational Interface

The point in where the computer system intakes the natural language; in which case,  speech recognition will always be spoken natural language.

Conversational UI

The conversational user interface (Conversational UI) that a user interacts with, when they use a messaging platform such as Facebook Messenger or Viber. The user interface determines how the experience looks and feels for users in terms of tone, humor, language, and graphical elements such as buttons, menus and images.

Decision Tree

A decision support tool and branching method for deriving strategies and their possible consequences, including resource costs and utility. Decision Tree’s illustrate all possible outcomes and assign them values so that decisions can be automated.

Deep Learning (DL)

A part of the broader family or machine learning methods, which involved researching and designing algorithms that can learn with multiple levels of abstraction.

Alternative description of “robots with A.I. capabilities.”

Game AI

A form of A.I. specific to gaming that uses an algorithm to replace randomness. It is a computational behavior used in non-player characters to generate human-like intelligence and reaction-based actions taken by the player.

Also called GANs, a class of artificial intelligence algorithms used in unsupervised machine learning, implemented by a system of two neural networks contesting with each other in a zero-sum game framework.


These are rules drawn from experience used to solve a problem more quickly than traditional problem-solving methods in A.I. While faster, a heuristic approach typically is less optimal than the classic methods it replaces.


Represents a mapping between what a user says and what action should be taken by a chatbot. These are the core blocks that make up building a conversation. For example, if a user wants to book a flight on a chatbot, that is his or her intent. Most intents would be defined upfront, and then refining or defining of intents would take place from customer interactions.


Machine Learning (ML)

A field of computer science that uses statistical techniques to give computers the ability to “learn” with data, without being explicitly programmed to do so. ML is how computers are provided with the knowledge with data, observations, and real-world interaction.

Natural Language Processing (NLP)

A field of computer science and Artificial Intelligence that is concerned with the interactions between how computers understand, interpret, and manipulate human language. AI leverages NLP to interpret, understand, and respond to human communication.

Neural Network

A computer system or program that is modeled on the operations of neurons of the human brain and nervous system. The large number of processors involved operate in tiers – the first receiving raw input, and each successive tier receiving the processed version. Furthermore, each node has it’s own knowledge, including rules that have either been programmed or developed itself. Only the last tier produces the output.


A node is where different points of a conversation flow intersect.


Pattern Recognition

A branch of machine learning that focuses on the recognition of patterns and regularities in data, although it is in some cases considered to be nearly synonymous with machine learning.


The smallest unit of speech. Phonemes help distinguish one word from another.


The use of a search algorithm to cut off undesirable solutions to a problem in an A.I. system. It reduces the number of decisions that can be made by the A.I. system.


Python is a widely used high-level programming language for general-purpose programming, created by Guido van Rossum and first released in 1991.


Reinforcement Learning (RL)

(also called Deep Reinforcement Learning) An area of Machine Learning concerned with how software agents should determine the behavior by providing reward feedback to improve performance and maximize some notion of cumulative reward.


An interdisciplinary branch of engineering and science that includes mechanical engineering, electronics engineering, computer science, and others.

Speech Recognition

The ability of a machine or program to identify words and phrases in spoken language and convert them to a machine-readable format.

Speech Engine

The software that takes spoken input, compares it to available vocabulary and assigns meaning to it.

Supervised Learning

The Machine Learning task of learning a function that maps an input to an output based on input and desired outcome.

Strong AI

An area of A.I. development that is working toward the goal of making A.I. systems that are as useful and skilled as the human mind.

This method tries to take training data used for one thing and reused it for a new set of tasks, without having to retrain the system from scratch.

Turing test

A test developed by Alan Turing that tests the ability of a machine to mimic human behavior. The test involves a human evaluator who undertakes natural language conversations with another human and a machine and rates the conversations.

Unsupervised Learning

The Machine Learning task of inferring a function that describes the structure of data that has not been classified or categorized. The algorithm must act without guidance or prior training to work with unsorted data.


Also known as “Narrow AI”, A.I. which can do just one thing at a time, such as play chess or recognize breeds of dogs. The opposite of Weak A.I. would be strong A.I., also known as artificial general intelligence (A.G.I.), which would have the capability to do anything that most humans can do.