Evolution of Generative AI: From Theory to Revolution

Meet the instructor, Prof. Jesse Spencer-Smith, and find out about how we'll learn the history of AI and gain insight into the future. This introductory module sets the foundation for understanding the historical development and future implications of generative AI.

This module explores the evolution of AI over the past 60 years, from early discussions about machine intelligence to modern chat assistants. It covers key players, breakthrough moments, and obstacles in AI development, examining how goals and approaches have shifted over time. The module also delves into the deep learning foundations that enabled generative AI.

This module examines why generative AI represents a significant leap forward in artificial intelligence. It explores key advancements including new learning algorithms, self-supervised learning, and model scaling. The module explains how these developments have enabled AI systems to generate human-like text, create art, and write code, representing a fundamental shift in AI capabilities.

This final module explores cutting-edge generative AI and its future prospects. It examines decoder transformer architecture, instruction fine-tuning, AI agents, and trends toward smaller, efficient models. The module discusses business implications, opportunity liability, and the democratization of technical skills, providing insights into generative AI's trajectory and future developments.