We believe the power of AI should be accessible to all. Read our no-nonsense AI glossary of common AI-specific terminology in plain English.
Artificial intelligence (AI)
Systems or machines that mimic human intelligence to perform tasks and continuously improve themselves based on the information they collect.
(At Galvia, we are a big fan of computer scientist and technology entrepreneur Andrew Ng and recommend his ‘AI for Everyone Course’ on Coursera for those who want a more comprehensive introduction to AI).
Big Data
Data sets that are too large or complex to be dealt with by traditional data-processing application software.
Chatbot
A computer program that simulates human conversation (either written or spoken), allowing humans to interact with digital devices as if they were communicating with a real person.
(Read more on how the chatbot Cara is transforming student engagement at University of Galway, Ireland.)
ChatGPT
ChatGPT is like a robot that can understand and respond to what you say or write, in a way that sounds like it’s coming from a human. It’s really good at understanding language and can talk about a lot of different topics.
Conversational AI
A type of artificial intelligence that enables consumers to interact with computer applications the way they would with other humans.
Cloud computing
A general term for anything that involves delivering hosted services over the internet. These services are divided into three main categories or types of cloud computing: infrastructure as a service (IaaS), platform as a service (PaaS) and software as a service (SaaS).
Content Management System (CMS)
An application used to manage content, allowing multiple contributors to create, edit and publish.
Data set
A collection of related, discrete items of related data that may be accessed individually, in combination, or managed as a whole entity.
Decision Intelligence
An analysis of the decision-making process that evaluates how choices are made.
(Take a look at how our decision intelligence platform works.)
Explainable AI
A component of DI that enables the interpretation and understanding of artificial intelligence models and their decision-making processes. It provides transparency, accountability, and trustworthiness by explaining how and why AI systems arrive at specific outcomes.
Generative AI
It’s like a creative machine that can produce something new, like a painting or a story, based on what it has learned from examples.
Machine learning
An application of AI involving computer algorithms that can learn by finding patterns in sample data.
Model
A computer program designed to mimic human-like thinking and decision making by learning from data.
Natural Language Processing (NLP)
A field of artificial intelligence that uses computer algorithms to analyse or synthesise human speech and text.
Predictive Analytics
It is a field of data analytics that helps to anticipate what may happen in the future based on what has happened in the past.
Robotic Process Application
RPA stands for Robotic Process Automation, which is a technology that uses software robots or bots to automate repetitive and routine tasks in business processes.
Uncertainty Quantification
It’s the measurement of how unsure we are about predictions or decisions. It uses statistics and risk assessment to deal with variability, errors, and incomplete information, making decisions more reliable and robust.
Did you find our AI glossary helpful? Then download our guide on how to quickly start your organisation on their AI journey here.