Demystifying Large Language Models ChatGPT, GPT 4, and the Future of AI Communication

The rapid advancements in artificial intelligence (AI) have given rise to a new era of large language models (LLMs) such as ChatGPT and GPT-4. These sophisticated AI systems are capable of understanding and generating human-like text, making them invaluable tools for communication and problem-solving. However, the complexity of these models often leaves the general public feeling overwhelmed and unsure of their implications. This talk aims to demystify LLMs, explaining their inner workings in an accessible manner, while highlighting their potential impact on our society.

The presentation will begin by offering an introduction to the concept of LLMs, touching on their history and development. We will explore the key principles behind these AI systems, such as neural networks and natural language processing, in a way that is easy to grasp for a non-technical audience. The primary focus will be on ChatGPT and GPT-4, two of the most advanced and widely-discussed models currently available.

Next, we will delve into the practical applications of these LLMs, demonstrating their versatility in tasks ranging from content creation to customer support. By showcasing real-world examples, attendees will gain a better understanding of how these AI models can transform various industries and streamline everyday tasks.

Finally, we will address some of the ethical and societal implications brought about by the increasing adoption of LLMs. Topics such as data privacy, algorithmic bias, and the potential for AI-generated misinformation will be discussed, providing a balanced perspective on the benefits and challenges of these revolutionary technologies.

By the end of this talk, attendees will have a clearer understanding of large language models and their impact on our lives. Join us for an enlightening journey into the world of AI communication, where we will explore the potential of ChatGPT, GPT-4, and other LLMs to shape our future interactions with technology.

Alex Olsen, Senior Research Associate, CARTE, University of Toronto
Somayeh Sadat, Assistant Director, CARTE, University of Toronto