Abstract: 

Statements such as """"Large Language Models (LLMs) are a type of generative Artificial Intelligence (AI) that is specifically focused on generating natural language text."""" and """"Current large language models (LLMs) like ChatGPT …” have become commonplace. Such statements conflate LLMs with generative models. However, strictly speaking this is not correct, because not all LLMs are generative. In this talk, I will explain what a LLM is, the range of architectures that can be used, and when an LLM is in fact a generative model. At the end of this session, you will have a more precise understanding of different types of language models, what's going on """"under the hood"""" of these models, and the kinds of natural language processing problems that each type is designed for.

Learning Objectives:
* Understand the key characteristics of Large Language Model architectures
* Understand different training objectives for LLMs
* Understand what types of tasks are suited to different LLM architectures

Bio: 

Professor Karin Verspoor is Dean of the School of Computing Technologies at RMIT University. She was previously a Professor in the School of Computing and Information Systems and Deputy Director of the Health and Biomedical Informatics Centre at the University of Melbourne.

Trained as a computational linguist, Karin’s research primarily focuses on extracting information from clinical texts and the biomedical literature using machine learning methods to enable biological discovery and clinical decision support. Karin held previous posts as the Scientific Director of Health and Life Sciences at NICTA Victoria Research Laboratory, at the University of Colorado School of Medicine, and Los Alamos National Laboratory. She also spent 5 years in start-ups during the US Tech bubble, where she helped design an early artificial intelligence system.