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The Editor's AI Dictionary: Key Terms You Need to Know

Updated: Feb 26

Artificial Intelligence is transforming the publishing industry. It's important to know tech jargon to stay relevant and understand the changes happening around you in the editing world.


That's why I've crafted The Editor's AI Dictionary—to demystify AI vocabulary and help you navigate the crossroads of technology and editing. In this guide, we'll break down the core AI terms into easy-to-understand definitions and include real-world examples of AI you likely already use in your everyday life.


Ready to crack the code? Let's dive in.


Artificial Intelligence

Computer systems that can perform tasks typically requiring human intelligence, such as understanding natural language, recognizing patterns, and adapting to new situations.


Example: smart thermostat that automatically adjusts temperature



Model

A single AI system


Example: Google’s Bard


Machine Learning

A type of artificial intelligence that allows systems to learn and improve from experience without being programmed with specific instructions.


Example: facial recognition



Neural Network

A computing system inspired by the structure of the human brain. It consists of a collection of nodes, or "neurons," and the connections between them. These networks are key components of many machine learning models and can recognize patterns and relationships in data.


Example: handwriting recognition for check processing




Generative AI

A type of Artificial Intelligence that makes new content by drawing on what it has previously learned from existing content.


Example: Midjourney, which creates an image from a text prompt

(This is what I used to create the computer in the image above.)



Language Model / Large Language Model

A type of Artificial Intelligence model that can understand and generate text in a human-like manner. It learns patterns in language. Then, when given a piece of text, it predicts what comes next. A Large Language Model is trained on a bigger amount of text/information and has a better understanding of nuanced language and reasoning.


Example: predictive text on iPhone texting, ChatGPT



Generative Pretrained Transformer (GPT)

The type of artificial intelligence tool ChatGPT is. “Generative” means it can create data. "Pretrained" means it has already learned from a vast amount of text. "Transformer" means the type of neural network it uses, which is good at understanding relationships between sentences.


Example: ChatGPT



Chatbot

A computer program that lets people talk to a Large Language Model in a conversational manner via text or voice. This often looks like a person asking the chatbot a question, and the chatbot answering with the requested information.


Example: Amazon's Alexa



Prompt/Input

A piece of text given to a Large Language Model for it to respond to.


Example: “What are the arguments for and against having a rabbit as a pet?”



Response/Output

The text the Large Language Model generates in reply to the prompt.


Example: “Here are the arguments for and against having a rabbit as a pet. Pro: 1) They don’t require walks...”


Hallucination

When a chatbot answers with false information.


Example: an attorney who asked ChatGPT for legal cases, which he then used in court filings, not knowing ChatGPT invented the cases and they did not exist





Erin Servais helps editors upskill through AI. Her AI for Editors course is known worldwide as the #1 AI course for editors of all types, including medical editors, finance editors, education editors, corporate communications editors, and book editors.


Erin serves on the board of directors for ACES: The Society for Editing and has presented about editing, entrepreneurship, and Artificial Intelligence for the Professional Editors Network, Editors Canada, the Northwest Editors Guild, the Editorial Freelancers Association, and ACES.

Email Erin: Erin@aiforeditors.com







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