Scientific progress is like repeatedly shooting at the boundary with a scattergun, and if lucky, it will expand the boundary.
"The 2024 Nobel Prize in Physics was awarded to research on the foundational discoveries of artificial neural network machine learning.
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 propelled 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 brain neurons. 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 handle specific tasks. In the 1980s, John Hopfield proposed a simple feedback neural network model capable of representing memory and error correction functions, marking a significant milestone in the field of artificial neural networks. Hinton further developed the 'Boltzmann Machine,' a stochastic model aimed at simulating statistical patterns, 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 are gradually guiding us toward a sustainable future, for instance, by helping us discover new functional materials. Encouragingly, the future applications of these technologies will depend on how wisely humanity chooses to use this powerful tool."