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Generative AI: Artificial Intelligence - Large Language Models

A guide to generative AI (artificial intelligence) and its impact on higher education.

AI Course for Educators

"(AI) is the use of computers to model the behavioral aspects of human reasoning and learning."

Artificial Intelligence. (2018). In P. Lagasse, & Columbia University, The Columbia encyclopedia (8th ed.). Columbia University Press. Credo Reference

We already encounter Artificial Intelligence in small ways in our everyday lives. Consider when people use face ID to unlock their smartphones (Facial Recognition) or text composition software such as Grammarly and Smart Compose in Gmail, both of which analyze and predict what we will type next in our emails and documents.

"AI is in our homes, our cars, and our phones, and the list goes on. AIs surround us every day. These devices learn about us, make decisions for us, and interpret and use our personal information in all sorts of non-obvious ways. As we go about our day - AIs decide everything from the best route to drive, to what movies are recommended to us, to what interest rates we get, and whether shops with cameras consider us risky" (Talagala, 2023).  

AI is also developing more and more every day. You may have heard about the recent release of ChatGPT, a chatbot that is highly conversational and can even respond to prompts by writing essays and other creative texts. There is also Lensa, an image app that lets you create custom and highly illustrative images from your photos.

What is an LLM or Large Language Learning Model?

A large language model is a type of artificial intelligence (AI) model that is trained to understand and generate human language. It works by analyzing a large amount of text, such as books, articles, and websites, and learning patterns and relationships within the text. Once it's been trained, the model can generate new text that's similar to the text it was trained on.

In simple terms, a large language model is a computer program that has been "taught" to understand and create human language by being fed a large dataset. The more text and examples the model is trained on, the more accurate and sophisticated it becomes at generating language that resembles human-written text.

Some examples of large language models include GPT-3, BERT, T5, and XLNet. They have been trained on a large dataset, and they can generate highly human-like text, answer questions, translate text, summarize, generate stories, and even write poems.


Talagala, N. (2023, January 11). Why 2023 will be the year of AI Education. Forbes. Retrieved January 11, 2023, from

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