» The 2024 Nobel Prize in Physics was awarded to John J. Hopfield and Geoffrey Hinton for “foundational discoveries and inventions that enable machine learning with artificial neural networks”. Awarding the physics prize to work that has traditionally been considered a part of computer science was an unprecedented move by the Nobel committee, and unjustified in the eyes of some experts who believed the AI hype had finally penetrated the hallowed chambers of the Nobel prize committee. Others however welcomed the announcement with open arms, seeing it as a smart move by physicists to claim the successes of machine learning as their own.
Whatever the reactions, it is a fact that machine learning has proved to be a revolutionary technology in a wide range of domains and deserved to be recognized. In this talk, we will discuss the seminal work of Hopfield and Hinton that laid the foundation of modern machine learning, the connections between physics and AI that they leveraged to make their discoveries and the applications of machine learning in physics. We aim to make our discussion understandable to a general audience who may not have any special background in computer science or physics.
● About the Speakers:
» Rashid Saleem is an Associate Professor in English Language and Literature at a Federal College in F-10/4, Islamabad. His interests range from Philosophy, Literature, Education to Linguistics, Psychology, Neurology, Physics, Electronics, Maths and Computer Science.
» Shahryar Khan is a graduate of physics from Quaid-i-Azam University, Islamabad. His research interests range from cosmology to condensed matter physics to chaos theory. He is also deeply interested in pure mathematics, philosophy and artificial intelligence.
