AI 360: From Theory to Transformation

This talk charts the evolution of Artificial Intelligence through the dual lenses of data and models, tracing AI’s journey from early symbolic systems to today’s advanced data-driven techniques. Attendees will learn how the interplay of ever-growing datasets and increasingly sophisticated model architectures has powered major breakthroughs, transforming AI from theoretical curiosity to a global catalyst for innovation.

General curiosity in AI

We will begin by examining AI’s early days, when handcrafted rules and symbolic reasoning took center stage despite limited data and computational resources. Next, the spotlight shifts to the rise of machine learning and neural networks, as larger datasets and improved computing power enabled more flexible, adaptive models. Along the way, we will highlight pivotal milestones—such as the resurgence of deep learning—that propelled AI forward at an accelerated pace. By focusing on how evolving data availability and model complexity shaped each phase of AI, this session provides a comprehensive historical perspective and offers insights into how AI’s trajectory continues to unfold in today’s data-rich world.