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Artificial Intelligence : Definitions

This guide provides an introduction to artificial intelligence including definitions, copyright issues, and generative AI tools.

Terms

Artificial Intelligence or AI- computer systems that are designed to complete tasks that are generally done with human intelligence

Algorithm- takes an input (dataset) and generates an output (pattern that is found in the data) 

Foundation Model- a machine learning model trained on a large amount of data for easy adaption and application 

Types of AI

  • Generative AI- generates text, images, audio, or other media in response to user prompts 
  • Machine Learning (ML)- training computer systems to learn from data to improve their performance over time through experience. This is done by finding patterns in the sample data. 
  • Natural Language Processing (NLP)- uses algorithms to analyze human speech and text by looking for linguistic patterns (e.g. speech- to text converters, automatic translation) 
  • Large Language Model (LLM)- a type of machine learning that is trained on a vast amount of textual data to carry out language-related tasks. 
  • Chatbot- software that uses NLP and machine learning to simulate conversation with humans 

Hallucination- when an output that is generated which is inaccurate that can't be explained based on the training data 

Prompt- a question or task given to an AI system to evoke a response or output 

Prompt Engineering- the process of designing and refining prompts to obtain a certain response from the AI system 

 

 

Adapted from the University of Texas Libraries, the definitions were generated by Llama 2 an LLM and reviewed by their library staff and adapted for use here.