Interest in and analysis of generative AI has exploded in the last few months with the arrival of OpenAI's ChatGPT and other generative AI tools like the image generator DALL-E 2. Generative AI is able to generate new data, such as text, images and audio, that is similar to existing data by responding to written prompts provided by the user. Many commentators and experts believe that ChatGPT is a game-changer, especially for learning and research as it has made the possibilities of generative AI accessible en-masse for the first time. Universities and other institutions are therefore working on how to respond to the challenges and opportunities generative AI presents and how it can be used in teaching, learning and research.
See the video below for a quick explainer of how ChatGPT and other generative AI tools operate:
ChatGPT's FAQ page provides some basic information about how ChaGPT works, its benefits, limitations and its privacy policy.
Overview of how ChatGPT works from UNSW Professor Toby Walsh
Dr Alan D Thompson provides a series of slides exploring how to write basic and advanced prompts for ChatGPT, using a range of everyday circumstances as examples.
Watch this short video from IBM Technology about how generative AI tools are built.
a report from Mantel Group, on ChatGPT and other large language models, how they work, and the implications for a number of sectors, including higher education.
Interview with Douglas Eck, senior research director at Google, that answers common questions about generative AI, large language models and machine learning.
blog posts and videos from the University of Sydney Business School. Information on how to write prompts and how generative AI works.
A glossary of terms associated with generative AI.
Blog of Professor Ethan Mollick, Wharton School of the University of Pennsylvania. Useful source for research and commentary on latest innovations and news on generative AI tools and what they are capable of producing.