BLACK BOX: a system or model whose internal workings are hidden from the user or operator, making it challenging to understand how it arrives at its decisions or predictions.
DEEP LEARNING: A subset of machine learning that uses neural networks with multiple layers to model and solve complex problems.
GENERATIVE AI: A branch of artificial intelligence that focuses on creating new data, such as text, images, or music, using machine learning techniques.
HALLUCINATIONS: Occur when an AI system generates information that, while it may seem plausible, is actually inaccurate or nonsensical
LARGE LANGUAGE MODELS: Sophisticated AI systems, powered by deep learning and trained on extensive text data, capable of comprehending and generating human-like text for various applications.
NEURAL NETWORKS: Computational models inspired by the human brain, used in AI to process and analyze data.
PREDICTIVE AI: subset of artificial intelligence that uses historical data and machine learning techniques to make informed forecasts and predictions about future events or outcomes, helping businesses and systems make proactive decisions.
While advice may vary, citing the use of generative AI tools in your research output is important, and a way to acknowledge the sources of generated content that helped guide your process. The very nature of genAI tools makes it difficult to provide complete transparency or reproducibility so it is encouraged that you create and save any chat transcripts.
Visit the below website for specific instruction on how to cite genAI tools:
Curious about the buzz around ChatGPT and AI's role in research? Eager to harness generative AI's power in a responsible manner that builds on your existing research skills? The resources and workshop on this page are intended to introduce you to the world of genAI, while equipping you with the vital know-how to seamlessly integrate generative AI into your current research toolkit.
The following generative AI tools can be used to assist you in your research process. However, we urge you to use genAI tools thoughtfully and with caution, ensuring that you understand the ethical implications and potential consequences of the content they generate. Students should always consult with their instructors or advisors on the use of genAI in any assignments or course work. Refer to Artificial Intelligence at the University of Manitoba for more information and advice on use of genAI in academic settings.
Keys to building good prompts:
No model is perfect, and there will always be times when the response might not meet your expectations. Using the above strategies can, however, greatly improve the chances of getting the desired outcome.
*OpenAI. (2023). ChatGPT4 (Oct 17 version) [Large language model]. https://chat.openai.com/chat
Video explaining GenAI
Video explaining Large Language Models
List of sources to help you understand and stay on top of artificial intelligence and how it is employed.