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Nobel Prize 2024 in Physics: John Hopfield and Geoffrey Hinton win Nobel Prize in Physics

By Sandy Verma

Nobel Prize 2024 in Physics: The Royal Swedish Academy of Sciences awarded the John J. It has been decided to award the 2024 Nobel Prize in Physics to John J. Hopfield and Geoffrey E. Hinton. Both scientists are being given the award “for their fundamental discoveries and inventions that enable machine learning with artificial neural networks.” The Nobel Prize has given this information on Tuesday through social media platform X.

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According to The Nobel Prize, the 2024 Nobel Prize winners in Physics used the tools of physics to create methods that helped lay the foundation for today's powerful machine learning. John Hopfield created a structure that could store and reconstruct information. Geoffrey Hinton invented a method that can independently discover properties in data and which has become important for the large artificial neural networks now in use.

Although computers cannot think, machines can now mimic tasks such as memory and learning. This year's physics laureates have helped make it possible. Using fundamental concepts and methods of physics, he has developed technologies that use structures in networks to process information.

This year's Physics Nobel Prize winner John Hopfield has created an associative memory that can store and reconstruct images and other types of patterns in data. Hopfield networks can store patterns and have a method for recreating them. When the network is given incomplete or slightly distorted patterns, the method can find the stored pattern that is most similar.

2024 Physics Laureate Geoffrey Hinton uses a network developed by his co-laureate John Hopfield as the foundation of a new network: the Boltzmann machine. It can learn to recognize specific elements in a given type of data. A Boltzmann machine can be used to classify images or create new examples of the type of pattern on which it was trained. Hinton has carried this work forward, helping to launch the current explosive growth of machine learning.

The successes of this year's Physics Prize winners stand at the foundation of physics. They have shown us a completely new way of using computers to aid and guide us in dealing with many of the problems and challenges our society faces. Thanks to their work humanity now has a new item in the toolbox that we can choose to use for good purposes. Machine learning based on artificial neural networks is currently revolutionizing science, engineering and daily life.

The field is already on the way to enabling breakthroughs toward building a sustainable society, such as identifying new functional materials. How deep learning will be used by artificial neural networks in the future depends on how we humans choose to use these incredibly powerful tools, which are already present in many aspects of our lives.

Did you know that an artificial neural network is designed to mimic the brain? Inspired by biological neurons in the brain, artificial neural networks are large collections of “neurons” or nodes, connected by “synapses” or weighted couplings, that are trained to perform certain tasks. An artificial neural network processes information using its entire network structure. The initial inspiration came from a desire to understand how the brain works.

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