El progreso científico, al igual que disparar una shotgun repetidamente contra los límites, expandirá los límites si la suerte está de tu lado.
"2024 Nobel Prize in Physics awarded to research on the foundations of machine learning based on artificial neural networks"
The 2024 Nobel Prize in Physics was jointly awarded to John Hopfield and Geoffrey Hinton, recognizing their pioneering contributions to advancing machine learning based on artificial neural networks (ANN). Their research promoted the development of artificial neural networks, enabling machine learning to excel in various applications.
The development of artificial neural networks can be traced back to the 1940s, inspired by simulations of biological neural networks. Artificial neural networks consist of a series of "neurons" or nodes connected through "synapses" or weighted connections. These nodes are not rigidly executing predefined instructions but are trained to process specific tasks. In the 1980s, John Hopfield proposed a simple feedback neural network model that could represent memory and error correction functions, becoming a significant milestone in the field of artificial neural networks. Hinton further developed the "Boltzmann Machine" (Boltzmann Machine), a stochastic model aimed at simulating statistical patterns and becoming an essential tool in deep learning.
These foundational discoveries laid the groundwork for today's deep learning technologies. Machine learning and artificial neural networks are now widely applied across various aspects of science, engineering, and daily life, such as image recognition, language generation, and medical decision support. Advancements in these technologies gradually lead us toward a sustainable future, such as helping us discover new functional materials. Encouragingly, the future applications of these technologies depend on how wisely humanity chooses to use this powerful tool.