MONITORING (SW) – The 2024 Nobel Prize in Physics has been awarded to scientists John Hopfield and Geoffrey Hinton “for foundational discoveries and inventions that enable machine learning with artificial neural networks”.
Inspired by ideas from physics and biology, Hopfield and Hinton developed computer systems that can memorize and learn from patterns in data. Despite never directly collaborating, they built on each other’s work to develop the foundations of the current boom in machine learning and artificial intelligence (AI), reported the Conversation.
Artificial neural networks are behind much of the AI technology we use today.
In the same way your brain has neuronal cells linked by synapses, artificial neural networks have digital neurons connected in various configurations. Each individual neuron doesn’t do much. Instead, the magic lies in the pattern and strength of the connections between them.
Neurons in an artificial neural network are “activated” by input signals. These activations cascade from one neuron to the next in ways that can transform and process the input information. As a result, the network can carry out computational tasks such as classification, prediction and making decisions.
John Hopfield (born 1933) is a US theoretical physicist who made important contributions over his career in the field of biological physics. However, the Nobel Physics prize was for his work developing Hopfield networks in 1982.
Geoff Hinton (born 1947), sometimes called one of the “godfathers of AI”, is a British-Canadian computer scientist who has made a number of important contributions to the field. In 2018, along with Yoshua Bengio and Yann LeCun, he was awarded the Turing Award (the highest honour in computer science) for his efforts to advance machine learning generally, and specifically a branch of it called deep learning.
While recent rapid progress in AI – familiar to most of us from generative AI systems such as ChatGPT – might seem like vindication for the early proponents of neural networks, Hinton at least has expressed concern. In 2023, after quitting a decade-long stint at Google’s AI branch, he said he was scared by the rate of development and joined the growing throng of voices calling for more proactive AI regulation.
After receiving the Nobel prize, Hinton said AI will be “like the Industrial Revolution but instead of our physical capabilities, it’s going to exceed our intellectual capabilities”. He also said he still worries that the consequences of his work might be “systems that are more intelligent than us that might eventually take control”.
