This Year’s (2024) Noble Prize for Physics has been announced for John Hopfield, a US scientist and Geoffrey Hinton, British- Canadian scientist. These two join the league of past winners including superstars of science — Albert Einstein, Neils Bohr and Enrico Fermi.

Geofrey Hinton (76) has been widely credited as one of the godfathers of Artificial Intelligence. He is a professor emeritus at the University of Toronto. He invented a method that can find properties in data and carry out tasks such as identifying specific elements in pictures. He quit Google in 2023 to speak about the risks of the technology he had pioneered. He is a PhD from the University of Edinburgh, UK.

Hopfield (91), a professor emeritus at Princeton University created associative memory that can store and reconstruct images and other types of patterns in data. He is a PhD from Cornell University.

Machine Learning (ML) and Artificial Intelligence (AI) can bring enormous benefits, it may get smarter than human beings, and hence we have the responsibility for using this technology in a safe and ethical way for the greatest benefit of mankind.

Hopfield and Hinton have been developing computer algorithms that mimic the functioning of human brain in performing common tasks. Though AI has become common parlance now, the term was coined in the mid-1950s when scientists spoke of computers as intelligent machines. However, most tasks the computers accomplished were calculation-based.

Computers imitated the human brain after Hopefield’s revolutionary work in the 1980s. He built an artificial neural network, resembling the nerve cells of human brain. It enables computers to ‘remember’ and ‘learn’. Earlier Donald Hebb, a Canadian psychologist had worked on human learning (1949), and Hopfield’s artificial neural network could accomplish something similar. It was a big breakthrough. His network processed information using entire network structure and not its individual constituents as in traditional computing. His network captured an image or song pattern in one go. The network is able to recall, identify or regenerate that image or song. It enabled pattern recognition in computers.

Hinton took forward the work of Hopfield and developed AI networks that could perform much more complex tasks. Hinton introduced training to enhance the computer’s capability. He developed a method of backpropagation to enable AI networks to learn from previous mistakes and improve themselves.

The process of continuous learning and improvement by training on large datasets led to the development of deep neural networks. These had multiple layers. Deep networks learnt more complex features and patterns in large datasets.

Deep learning is the core of modern speech and image recognition, translation, voice assistance and autonomous cars.

Hinton and his students developed AlexNet that recognized images. It was a seminal moment in the development of AI.

Hinton was awarded the Turing prize in 2018. Hinton’s body of work is in computer science. Hopfield has made contribution to physics, neuroscience and biology. Hopfield’s 1982 work was borrowed from some earlier breakthroughs in physics.

This time the Nobel Committee has picked up a computer science breakthrough for Nobel. In past, it has also awarded a Nobel for work related to data storage devices such as hard drives (2007).