From Magnets to Machines: How a Simple Physics Model Helped Shape the Future of AI
What does a hundred-year old theory about magnetism have to do with the cutting edge of Artificial Intelligence? A lot more than you might think.
This talk will explain how a simple physics model called the Ising model, originally used to understand magnetism, has influenced modern artificial intelligence (AI).
Professor Damien Foster will discuss how this model became important in AI, particularly in associative memory and deep learning, impacting the work of John Hopfield and Geoffrey Hinton, who received the Nobel Prize for their contributions.
The lecture will show how this basic model has shaped machine learning and continues to help us understand complex systems, with effects reaching beyond theoretical physics.
This lecture is available to join in person or online.
