AI in Higher Education Guide
Welcome to the Library guide on using Artificial Intelligence (AI) Research Tools. Our goal is to provide a fundamental introduction to AI technology and its use in the academic research process.
Artificial Intelligence Terms and Concepts to Know
Artificial intelligence (AI)
Artificial intelligence refers to technology that allows computers to mimic human cognitive functions such as learning, problem-solving, and pattern recognition, enabling them to perform tasks that normally require human intelligence. The term "artificial intelligence" was first coined by Stanford professor John McCarthy in 1955. McCarthy originally defined artificial intelligence as “the science and engineering of making intelligent machines.”
- Examples: Word suggestions while typing, recommended songs in playlists, suggested articles
Machine learning
A sub-field of computer science in which a computer system learns how to complete a task by learning to recognize patterns and make predictions. Rather than being explicitly programmed, the system learns by processing massive amounts of training data repetitiously. It uses neural networks, programmatic structures modeled after the human brain, to extract information from the data and recognize patterns within it.
Large language models (LLMs)
Large language models are a type of AI model that use machine learning to recognize, process, and mimic human language. They are trained on massive amounts of text in order to learn patterns and relationships in language and communicate effectively with humans. Large language models often sound as if they have thoughts and feelings because they have been trained on human-generated text and replicate its patterns.
Natural language processing (NLP)
Natural language processing is a sub-field of computer science and AI that allows computers to understand, mimic, and generate human language. It enables users to interact with AI models using human language rather than programmed commands. Large language models are typically considered a type of natural language processing model.
- Examples: Digital assistants such as Siri, Alexa, and Google Assistant
Generative AI (GenAI)
Generative AI refers to AI systems that create new, unique content rather than simply aggregating or regurgitating already-existing content. AI-generated content can include text, images, audio, video, and even code. Generative AI systems use machine learning to recognize patterns in existing content, and then base their output on those patterns. As a result, AI-generated content resembles existing content, but is actually a new creation. However, not all uses of AI are generative; generally speaking, in order for a particular use of AI be considered generative, the output must contain significant content that the user did not include in the input.
-
Examples: ChatGPT, Perplexity, Google Gemini
Sources:
IBM. What is AI? IBM. https://www.ibm.com/topics/artificial-intelligence
Ray, Susanna. 10 AI Terms Everyone Should Know. Microsoft. https://news.microsoft.com/10-ai-terms/?OCID=lock1
Stanford University Human Centered Artificial Intelligence (HCAI). Artificial Intelligence Definitions. Stanford University. https://hai.stanford.edu/sites/default/files/2020-09/AI-Definitions-HAI.pdf
University of North Florida. Artificial Intelligence Definitions. Office of Faculty Excellence. https://www.unf.edu/ofe/ai/definitions.html