Large Language Models (LLMs) such as ChatGPT have transformed the way we interact with technology, enabling natural conversations, creative assistance, and advanced problem-solving. But what really happens under the hood? At its core, ChatGPT performs a surprisingly simple task: predicting the next word in a sequence. This session demystifies how LLMs work, starting with tokens and probabilities and moving through neural networks and transformer architecture. We’ll explore how attention mechanisms help models understand context, how randomness and temperature settings influence creativity, and why training on massive datasets is essential. The discussion will also cover how these models generate coherent text one token at a time, their limitations, and what those mean for real-world applications. Attendees will gain a clear understanding of why LLMs are powerful, where they fall short, and the emerging trends shaping the future of AI. Whether you’re a developer, researcher, or tech enthusiast, this session provides the foundation to appreciate and leverage these cutting-edge systems.

You will learn:

• How LLMs like ChatGPT predict text one token at a time.
• The role of transformers, attention, and randomness in generating responses.
• How to identify key limitations and future trends in AI language models.