The Nobel Committee in Physics has awarded this year’s prize to John Hopfield y Geoffrey E. Hinton for using tools from physics to develop methods that are the basis of today’s powerful machine learning. Specifically, Hopfield created an associative memory that can store and reconstruct images and other types of patterns in data, while Hinton invented a method that can autonomously find properties in data and therefore perform tasks such as identifying elements specific in images.
“The work of the winners has already been very useful. In physics, we use artificial neural networks in a wide range of areas, such as in the development of new materials with specific properties,” says Ellen Moons, chair of the Nobel Committee for Physics.
John Hopfield created a structure that can 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 in use today. They both used physics to find patterns in information.
The networks that “think”
Although computers cannot think, machines can imitate functions such as memory and learning. This year’s laureates in physics have helped make this possible. Using fundamental concepts and methods from physics, they have developed technologies that use network structures to process information.
Machine learning differs from traditional software, which works as a kind of recipe. The software receives data, processes it according to a clear description and produces the results, similar to when someone collects ingredients and processes them according to a recipe to produce a cake. Instead, in machine learning, the computer learns by example, allowing it to tackle problems that are too vague and complicated to be handled with step-by-step instructions.
At the press conference to present the award, Hinton acknowledged that he uses the ChatGPT tool and finds it “very useful,” although he does not trust its answers one hundred percent because he may have “hallucinations.” The chair of the committee finds it difficult to imagine that tools like ChatGPT could have been developed if it had not been for the pioneering work of the awardees.
Source: www.eldiario.es
