AI: Artificial Intelligence Resources

This guide will provide you with basic information on Artificial Intelligence, particulary Large Language Models (LLMs) and examples of which AI tools may be the most useful for your research.

• Choosing Your AI Tool
  • Scite
  • Chat GPT
  • Claude
  • Gemini
  • NotebookLM
  • Perplexity
  • Research Rabbit
  • SciSpace
• Disipline-Related Resources
• Citing & Publishing Issues
• Additional UND Resources

Artificial Intelligence (AI) has been around for quite some time. The official definition from the Oxford English Dictionary (OED) is "The capacity of computers or other machines to exhibit or simulate intelligent behaviour; the field of study concerned with this. In later use also: software used to perform tasks or produce output previously thought to require human intelligence, esp. by using machine learning to extrapolate from large collections of data. Also as a count noun: an instance of this type of software; a (notional) entity exhibiting such intelligence." 

Most conversation today focuses on generative artificial intelligence (generative AI), defined by OED as: Artificial intelligence designed to produce output, esp. text or images, previously thought to require human intelligence, typically by using machine learning to extrapolate from large collections of data; (also) a system, piece of software, etc., used to create content in this way". 

This guide is going to focus on generative AI, specifically the Large Language Models (LLMs) that can be used. Each LLM will have different strenghts, and it will be up to the user to determine which is best for their purposes. This guide will also provide current resources on the constantly evolving dissussion of AI in the academic world.

Machine Learning: "Rather than being programmed with rules to produce answers, computers receive data and the answers expected from the data and, as a result, produce rules by identifying patterns between the two” (UNESCO)"

• artificial neural networks: a kind of AI machine learning that uses "...a method of mimicking the way the human brain learns, through its connection of neurons, using a computer model.3 This form of AI can evaluate complex relationships between inputs and outputs through a hidden layer (or layers) of calculations" (CADATH 2018)
• deep learning: "...a form of artificial neural network with many hidden layers between inputs and outputs that allow the program to analyze complex data of various structures.8 In health care, a common form of deep learning is the convolutional neural network" (CADATH 2018)
• generative AI: deep learning models that use data to “generate statistically probable outputs when prompted" (IBM 2023) ChatGPT is an example of generative AI.
• large language models: “… trained on large text datasets to learn to predict the next word in a sentence and, from that, generate coherent and compelling human-like output in response to a question or statement." (UNESCO)
  • examples: ChatGPT, Bard
  • A July 2023 Ars Technica post provides this jargon-free "gentle primer" on how LLMs work.
• Natural Language Processing​: "...(NLP) is a branch of AI concerned with understanding and interpreting human language.6,10,11 In health care, NLP could be used to analyze the content of electronic medical records or as an automated agent to respond to patient questions" (CADATH 2018)
  • example: Google search engine

Do you have comments or questions?

This guide to artificial intelligence is very much a work in progress, and we would love to hear your thoughts on other resources we can include or issues to be addressed!

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