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ChatGPT and AI

Resources on ChatGPT and AI for Faculty

What is ChatGPT?

Chat GPT (Chat Generative Pre-trained Transformer) is an artificial intelligence tool that generates text based on given prompts.  The tool was created by OpenAI, an AI and research company and launched in November 2022. The way users interact with ChatGPT is to ask it a question, or give it a prompt and receive a quick answer. It can understand and produce natural language text. 

For a more in-depth introduction to ChatGPT Stephen Wophram's article,  "What is ChatGPT Doing... and Why Does it Work?"

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Algorithm:  a logical sequence of steps to accomplish a task such as solving a problem. (Mercatus Center/George Mason University: https://www.mercatus.org/ai-policy-guide/glossary

Artificial Hallucination: mistakes in AI generated text that are semantically or syntactically plausible but are in fact incorrect or nonsensical. (IEEE Spectrum/https://spectrum.ieee.org/ai-hallucination)

Artificial Intelligence:  the theory and development of computer systems able to perform tasks that normally require human intelligence, such as visual perception, speech recognition, decision-making, and translation between languages. (Lexico.com)

ChatGPT: a large language model tool that uses artificial intelligence (more specifically, natural language processing), to answer user-generated prompts. It was developed by OpenAI using the GPT 3.5 (Generative Pre-Trained Transformer) and is currently available for public use."  (McGill University Library LibGuide on AI).

Deep Learning:  a collection of algorithms used in machine learning, used to model high-level abstractions in data through the use of model architectures, which are composed of multiple nonlinear transformations.(Techopedia: https://www.techopedia.com/definition/30325/deep-learning)

Generative AI:  refers to deep-learning models that can generate high-quality text, images, and other content based on the data they were trained on. (IBM Topics: https://research.ibm.com/blog/what-is-generative-AI)

Large language models (LLMs): deep learning algorithms that can recognize, summarize, translate, predict, and generate content using very large datasets. (PC Magazine Encyclopedia: https://www.pcmag.com/encyclopedia/term/large-language-model)

Machine Learning:  a branch of artificial intelligence (AI) and computer science which focuses on the use of data and algorithms to imitate the way that humans learn, gradually improving its accuracy.  (IBM Topics: https://www.ibm.com/topics/machine-learning)

Neural networks:  subset of machine learning that uses a network of functions to understand and translate a data input of one form into a desired output, usually in another form. Their name and structure are inspired by the human brain, mimicking the way that biological neurons signal to one another. (IBM Topics: https://www.ibm.com/topics/neural-networks)