Buzzwords, Jargon & Legit Tech…

Do You Know What The AI Terms You Use Actually Mean?

Let’s face it — artificial intelligence is kind of “on trend” at the moment. SaaS companies, media firms and even makers of consumer products are claiming left and right that their products leverage AI or machine-learning left and right. Despite all of the talk there’s still a lot of confusion around which words mean what and how exactly to use them.

If you don’t understand the basics then you’ll have no idea how to separate the buzzwords & jargon from the legitimate technology.

We’ve put together a glossary of the most commonly used terms in AI to help bring everyone up to speed:

Algorithm: A formula or set of rules used to solve a problem or answer a question. Algorithms define a set of steps or actions to take in order to achieve the desired result.

Applied Artificial Intelligence: A term used to describe commercially viable “smart” systems, using AI to perform specific tasks. Also known as advanced information processing.

Artificial Intelligence: A term used to describe a machine displaying intelligent behavior, such as reasoning, learning and sensory processing. AI involves tasks that have historically been limited to humans and intelligent animals, such as decision-making and problem-solving.

Artificial General Intelligence: The term used to describe machine intelligence that can perform any task a human can. Some say this is impossible. This term is also sometimes referred to as “strong AI,” but many academics reserve “strong AI” for machine’s that can achieve consciousness (not yet possible).

Artificial Intelligence Marketing (AIM): AIM is a loose categorization of products, technologies, and services that use AI to enhance or automate marketing. This term has been around for a while, but it remains to be seen if it will catch on or be replaced, for instance by Machine Marketing which is also a term that’s begun to crop up recently.

Autonomous: Autonomous refers to the ability to act without being controlled by an outside force. Driverless cars are considered autonomous vehicles because the cars do not require humans to steer, brake or accelerate.

Chatbots (Bots): Bots are programs that interact directly with customers via natural language processing (NLP, see below). Many companies are already using chatbots for customer support, but the category is changing and innovating constantly, and new applications are cropping up, namely in the B to B space. Marketers predict that they will embrace chatbots as enthusiastically as they did apps circa 2013.

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.

Data Mining: Data mining is a process of sifting through large quantities of data and identifying patterns or other useful information. Data mining is a strong potential application for AI systems.

Deep Learning: Deep learning refers to a type of machine learning that is focused on complex problems, including understanding the relationships between complicated and large data sets. Deep learning software attempts to mimic the performance of the higher-level thought processes of the human brain.

Machine Learning: Machine learning is a type of AI in which a computer has the ability to learn independently without being controlled by a human operator. The goal of machine learning research is to get computers to write rules without being programmed to do so.

Neural Networks: A neural network is a framework used for deep learning. Neural networks involve passing input data through layers of neuronal nodes that are dynamically weighed to generate the desired output, a system designed to mimic the process of intelligent thought in the human brain.

Supervised learning: A type of machine learning in which data sets train the machine to generate the desired algorithms. You can think of it like a teacher supervising a student, this is more common than unsupervised learning. This is commonly used for instance in radiology where algorithms have reached higher levels of accuracy than humans in detecting bone fractures thanks to training through labelled data.

Turing Test: A test of AI’s ability to pass as human. In Alan Turing’s original conception, an AI would be judged by its ability to converse through written text.

Unsupervised learning: A type of machine learning algorithm used to draw inferences from data sets consisting of input data without labeled responses. The most common unsupervised learning method is cluster analysis.

Have you seen these terms used incorrectly or did you already have a good understanding of their meanings? Let us know your thoughts!