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Welcome to the AI Literacy Resource Guide
This guide provides an introductory overview of generative artificial intelligence, also known as gen AI and how and when it might be appropriate to use in your academic career. We define and explain what generative AI is; we will highlight best practices for the application of gen AI; and we will spotlight the risks and limitations to consider with this technology.
Glossary of Terms
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Algorithm
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A set of instructions or rules that a machine follows to perform a task or solve a problem. |
Large Language Model (LLM) |
The mathematical representation of a system or process that is used by AI to make predictions or decisions. |
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Chatbot |
A program that simulates conversation with users, often through text, to assist with tasks or answer questions. |
Machine Learning (ML) |
A type of AI that allows computers to learn from data and improve over time without being explicitly programmed. |
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Computer Vision |
A field of AI that enables machines to "see" and understand images or videos. |
Natural Language Processing (NLP) |
The ability of machines to understand, interpret, and respond to human language. |
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Data Mining |
The process of analyzing large sets of data to uncover patterns, trends, and useful information. |
Prompt |
A prompt is the text or instruction you provide to the AI to get it to generate something. The more specific the prompt, the more specific the results. |
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Deep Learning |
A type of machine learning that uses neural networks with many layers to analyze complex data, like images or speech. |
Training Data |
The dataset used to teach a machine learning model how to recognize patterns and make predictions. |
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Generative Artificial Intelligence (AI) |
A type of artificial intelligence that creates new content, like images, text, music, or even video, based on patterns it has learned from existing data. Instead of just analyzing or recognizing things, it can generate something original that looks, sounds, or reads like it was made by a hum |
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