This guide is intended as a resource to help navigate the quickly evolving terrain of generative AI, providing a starting point to help users learn the issues surrounding the use of AI, including an overview of popular AI research tools, guidance on crafting prompts in these tools, and resources related to core AI ethical concerns and issues.
Due to the rapid changing landscape of AI, this guide will be periodically updated to reflect current information.
Generative AI refers to a branch of artificial intelligence that focuses on creating or generating new content, such as images, text, music, or videos, using machine learning algorithms. Unlike traditional AI systems that are designed to perform specific tasks, Generative AI is a subset of artificial intelligence (AI) that creates (aka generates) content based on the data and examples it was trained on.
Presently, many of the common generative AI tools and models utilize natural language as an input to create text, images, audio, video, code, and other media. The most well known generative AI tools, such as ChatGPT, are powered by large language models (LLMs). LLMs are trained on massive amounts of text in order to understand user input (prompt) and generate a response by predicting the most likely desired sequence of words and sentences.
Although the responses from generative AI tools such as ChatGPT can give the impression that the underlying AI model is able to critically analyze the user prompt, it is important to understand that generated outputs are based on predictive models based patterns in the text that the models were trained on. Equally important, it is essential to understand both the capabilities and limitations of these tools, particularly when using them for academic and research purposes.
