Glossary of AI Terms

The world of AI is full of technical jargon. If you’ve come across a term that made you scratch your head, then this is the page for you! 

Algorithm
A set of mathematical instructions or rules that, especially if given to a computer, will help to calculate an answer to a problem.

Artificial Intelligence (AI)
A branch of computer science that aims to create machines that can perform tasks requiring human-like intelligence, such as learning, reasoning, and problem-solving.

Anthropomorphism
The attribution of human-like qualities to non-human entities or machines, like thinking a machine can "want" or "feel."

Bias
A systematic error introduced into the model either through the training data or the model architecture, which skews its decision-making or output.

Chatbot
A model designed to simulate conversation with human users, especially over the internet. Many chatbots, especially simpler ones, operate based on pre-written scripts or decision trees, guiding conversations through a series of branches based on user choices or keywords. 

ChatGPT 
ChatGPT is an advanced language model developed by OpenAI, designed for understanding and generating human-like text responses. “GPT” stands for Generative Pre-trained Transformer, emphasizing its ability to engage in conversational interactions and adapt to a wide range of tasks.

Data Mining
The process of extracting useful information and patterns from large data sets.

Data Set
A collection of information that is grouped together.

Deep Learning
A subfield of machine learning focused on training algorithms called neural networks to recognize patterns in large datasets. These neural networks attempt to simulate the behavior of the human brain—albeit far from matching its ability—to "learn" from large amounts of data.

Delimiter
Like a punctuation mark that tells AI, like ChatGPT, where one piece of information ends and another begins, helping it understand and organize data better. 

Discriminative Model
A type of statistical model used in machine learning that focuses on modeling the decision boundary between different classes or categories. 

Generative Model
A type of machine learning model that can generate new data instances similar to the data it was trained on.

Hallucination
In the context of AI and machine learning, hallucinations refer to generated outputs that contain inaccuracies, fabrications, or distortions.

Input 
Any data or information you provide to the AI system for processing. This can include text, images, commands, or any other form of data that the system is designed to understand and respond to. Sometimes used interchangeably with “Prompt.” 

Large Language Model (LLM)
An artificial intelligence model trained on vast amounts of text data to understand, generate, and interact with human language. These models, like OpenAI's GPT series, are capable of performing a wide array of language-related tasks due to their complex neural network architectures.

Multimodal
A subsect of generative AI tools that are capable of understanding, interpreting, and generating content across multiple types of data, such as text, images, and audio.

Model
A computational framework trained to generate new content resembling its training data. It learns from vast datasets to produce original outputs, mimicking patterns or styles learned during training.

Machine Learning
A type of artificial intelligence that enables computers to learn from experience and improve their performance on a specific task over time without being explicitly programmed.

Natural Language Processing (NLP)
A branch of AI that focuses on enabling machines to understand, interpret, and generate human language.

Neural Network
A computational model inspired by the human brain, consisting of interconnected nodes (neurons) that are used in machine learning and AI applications.

Output
What the AI provides you after processing your request, which can include text, images, data analysis results, or any other form of response that the system is designed to produce. The output is essentially the AI's answer or contribution to the conversation or task at hand.

Parameter
A variable used in machine learning algorithms that is learned from the training data. Millions, billions, or even trillions of these parameters are incorporated into a model’s neural network. 

Prompt
A question or request given to a computer program (such as an LLM) to generate a desired response. a specific type of input that is designed to elicit a particular response from the AI. It's a way of guiding the AI towards generating a specific type of content or answer. Prompts are often crafted with intention to direct the AI's output more precisely.

Prompt Engineering
The process of crafting an effective prompt to generate a specific response from AI tools.

Predictive Modeling
The use of historical data and algorithms to forecast future events or trends. It's a key tool in fields like finance and healthcare for making informed decisions based on predicted outcomes.

Training Data
The dataset used to train a machine learning model.

Transformer
A powerful type of computer program used in AI that can read, understand, and generate text by paying attention to the important parts of what it's processing. It's the technology behind many smart AI tools that can write stories, answer questions, or translate languages.