Retrieval-Augmented Generation
(Lewis, Patrick et al. “Retrieval-Augmented Generation for Knowledge-Intensive NLP Tasks.” arXiv.org (2021): n. pag. Print.): A general-purpose fine-tuning recipe for retrieval-augmented generation (RAG) -- models which combine pre-trained parametric and non-parametric memory for language generation.
Artificial General Intelligence
(Bubeck, Sébastien et al. “Sparks of Artificial General Intelligence: Early Experiments with GPT-4.” arXiv.org (2023): n. pag. Print.): an early version of GPT-4 which can solve some novel and difficult tasks that span mathematics, coding, vision, medicine, law, psychology and more, without needing any special prompting.
ChatGPT refers to a specific use-case or version of OpenAI's Generative Pre-trained Transformer (GPT) models designed for conversational interactions.
>> ChatGPT official updates on model versions: https://openai.com/chatgpt
>> UFIT Tutorial on The role of ChatGPT in Assessment of Students Learning (April 11, 2023) -- Click to access the slides
>> How UF regulates the way of using ChatGPT?
>> From UF IRM (Integrated Risk Management) :
Any data classified as sensitive or restricted should not be used. This includes, but is not limited to the following data types:
>> The GPT models! - ChatGPT is a powerful tool but "lies" sometimes.
>> How come can something be unreliable and powerful at the same time?
>> Depending on what and how we use it.
Leslie Mojeiko and educational technologist Chris Sharp offers generative AI “recipes” to enhance course design and teaching.
>> What about ChatGPT is helpful for librarians?
>> Share your thoughts with us! A piece of thought from me: ChatGPT, an Opportunity to Understand More About Language Models
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