School of Computer Science
Technical Workshop Series
Exploring Large Language Models: An Introduction to ChatGPT and Beyond (2 Offerings)
Presenter: Shaghayegh Sadeghi
Date: Tuesday, July 18th, 1:00 pm -2:00 pm
Location: 4th Floor (Workshop space) at 300 Ouellette Avenue (School of Computer Science Advanced Computing Hub)
LATECOMERS WILL NOT BE ADMITTED once the presentation has begun.
Abstract:
The workshop on Introduction of Large Language Models and ChatGPT provides a comprehensive overview of state-of-the-art language models, focusing on ChatGPT as an example. Participants will learn about the architecture, training methodologies, and applications of large language models. Hands-on exercises and demonstrations will enable attendees to interact with ChatGPT and explore its capabilities in generating conversational responses, assisting with various tasks and OpenAI API. Ethical considerations and best practices for responsible use will also be discussed. By the end of the workshop, participants will have a solid understanding of large language models and be equipped to leverage ChatGPT and similar models in their work effectively.
Workshop Outline:
I. Introduction
A. Overview of language models
B. Importance and applications of large language models
C. Introduction to ChatGPT as a prominent example
II. Applications of ChatGPT
A. Generating conversational responses
B. Information retrieval and assistance
C. Creative writing and content generation
III. Hands-on Exercises
A. Interacting with ChatGPT
B. Experimenting with conversational prompts
C. Exploring model outputs and evaluating responses
D. Exploring OpenAI API
IV. Best Practices and Future Directions
A. Guidelines for using large language models
B. Recent advancements and research directions
C. Leveraging language models in real-world applications
Prerequisites:
Everyone is welcome to join this workshop regardless of their background. However, participants with a basic understanding of natural language processing (NLP) concepts, familiarity with programming (preferably Python), some knowledge of machine learning principles, and prior exposure to language models (such as RNNs and transformers) will be able to derive greater benefit from the workshop.
Biography:
Shaghayegh Sadeghi is a PhD candidate at the University of Windsor, specializing in the application of Artificial Intelligence (AI) in the pharmaceutical field. With a strong interest in graph analysis and text embedding, Shaghayegh's research focuses on leveraging AI techniques to extract valuable insights from pharmaceutical data for drug development and patient care improvement.