Nobel Prize in Physics 2024: The Royal Swedish Academy of Sciences announced on Tuesday that the 2024 Nobel Prize in Physics will be awarded to John J. Hopfield of Princeton University, USA, and Geoffrey E. Hinton of the University of Toronto, Canada, for their “foundational discoveries and inventions that enable machine learning with artificial neural networks.”
Hopfield and Hinton applied principles of physics to train artificial neural networks, laying the groundwork for modern machine learning techniques. According to the Nobel Foundation, the laureates used “tools from physics to develop methods that are the foundation of today’s powerful machine learning.”
John Hopfield developed a model of associative memory capable of storing and reconstructing images and data patterns, while Geoffrey Hinton introduced a method that allows machines to autonomously discover data properties, facilitating tasks such as identifying specific elements within images.
John J. Hopfield, born in 1933, attended Cornell University in Ithaca, New York, and currently teaches at Princeton University. Geoffrey E. Hinton, born in London 77 years ago, earned his PhD from The University of Edinburgh, UK, and is now a professor at the University of Toronto, Canada.
The Nobel Prize in Physics comes with a prize of 11 million Swedish kronor, which will be shared equally between the two laureates.
Hopfield and Hinton’s Nobel-Winning Work
The Nobel Committee highlighted John Hopfield’s development of an associative memory system, capable of storing and reconstructing images and other data patterns. Geoffrey Hinton, on the other hand, pioneered a method that can autonomously detect features within data, enabling tasks such as recognizing specific elements in images.
When we talk about artificial intelligence (AI), we are often referring to machine learning, which relies on artificial neural networks modeled after the brain. In these networks, “neurons” are represented by nodes that influence one another, similar to brain cell interactions. The connections between these nodes can strengthen or weaken as the network learns from data. Since the 1980s, this year’s Nobel laureates have made significant contributions in this area.
John Hopfield created a network that can store and retrieve patterns, such as recognizing images. In this system, the nodes function like pixels, and the network operates like a puzzle: when given an incomplete or distorted image, it adjusts values to recreate the closest match to the original.
Building on Hopfield’s work, Geoffrey Hinton introduced the Boltzmann machine, a model that learns to identify common features within data, such as recognizing specific objects in pictures. His work has been instrumental in advancing modern machine learning and has paved the way for many of today’s AI breakthroughs.
Ellen Moons, Chair of the Nobel Committee for Physics, emphasized the broader impact of these discoveries, noting that AI advancements are also being used to develop new materials with unique properties.
Meanwhile, the Nobel Prize in Physiology or Medicine for 2024 was awarded to Victor Ambros and Gary Ruvkun for their discovery of microRNA, as announced on Monday.
In 2023, the Nobel Prize in Physics was awarded jointly to Pierre Agostini (Ohio State University, USA), Ferenc Krausz (Max Planck Institute of Quantum Optics, Germany), and Anne L’Huillier (Lund University, Sweden) “for experimental methods that generate attosecond pulses of light for the study of electron dynamics in matter.”
Since its inception in 1901, a total of 117 Nobel Prizes in Physics have been awarded.
Source: Abp live
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