LEGEND : John Hopfield, 91 (left), and Geoffrey Hinton, 76, were honoured for their vital contribution to the development of AI. DR/ADOBE
John Hopfield and Geoffrey Hinton were awarded the prestigious Nobel Prize in Physics on Tuesday. Their work on artificial neural networks and machine learning has been instrumental in developing AI features such as voice and facial recognition, object detection in images, etc.
Forty years of work and research in physics applied to AI finally rewarded ! The 2024 Nobel Prize in Physics was awarded this Tuesday by the Royal Swedish Academy of Sciences to two emblematic figures in the field of artificial intelligence (AI): British Canadian Geoffrey Hinton And the American John Hopfield.
The two researchers were recognized for their pioneering work in the field of machine learning, a discipline central to the development of modern AI technologies. Their discoveries, particularly on artificial neural networks, have radically transformed the scientific and technological landscape, bringing major advances in sectors as diverse as facial and object recognition, machine translation, and many others.
" They used fundamental concepts from statistical physics to design artificial neural networks that function like associative memories and find patterns in large data sets." said Ellen Moons, chair of the Nobel Committee for Physics, as she announced the names of the winners of the prestigious award..
John Hopfield or the contribution of associative memory
John Hopfield, now 91 and a professor at Princeton University, is the originator of the " Hopfield network", a model of associative memory. This network allows to analyze, store and reconstruct images or other types of data, thus simulating memory mechanisms of the human brainThis innovation marked a turning point in the development of data and image processing systems, providing a framework for manipulating large amounts of information in an associative manner, a principle that is found in many modern applications of AI.
Geoffrey Hinton; Physical Statistics to Identify Data in Images
Geoffrey Hinton, 76, often considered one of the founding fathers of artificial intelligence, also played a key role in the development of neural networks. Building on Hopfield's work, he developed a new approach called " Boltzmann machine". This model uses concepts from statistical physics to autonomously identify important features in complex data sets. It is thanks to this approach that algorithms capable of recognizing objects in images or performing automatic translations have emerged..
These advances, which are now omnipresent in the technological landscape, were made possible by the tools developed by Hinton and Hopfield… in the 1980s.
A major revolution for artificial intelligence
The work of the two laureates is based on fundamental principles of physics – in particular statistical physics – applied to artificial neural networks. These networks, inspired by the functioning of neurons in the human brain, enable machines to learn from data, identify patterns and make decisions. This is this machine learning capability which paved the way for concrete applications in fields as diverse as particle physics, astrophysics, and materials science. Today, these technologies have become an integral part of our daily lives, with systems such as the voice and facial recognition, THE recommendation engines on digital platforms, or even virtual personal assistants.
Machine learning: promise and risks
Nobel Committee Chair Ellen Moons used the award ceremony to point out that the models developed by the laureates "are now at the heart of many aspects of our daily lives," while stressing that their potential extends far beyond current applications. She also warned that machine learning, while bringing immense benefits, also raises concerns about the future of humanity which now has a powerful new tool that it must " choose to use for good purposes.”
Ethical issues
Awarded since 1901, the Nobel Prizes recognize people who have worked for "the benefit of humanity", in accordance with the wish of their creator, the Swedish inventor Alfred Nobel, to whom we owe in particular the stick of dynamite, the initial use of which was diverted to make a weapon.
It is undoubtedly this original spirit that takes precedence over virtue and this story of the diversion of progress that pushed the jury to choose the duo of researchers. Because the intrusion of AI into our daily lives, its potential but also its risks require that the debate be opened publicly. "Machine learning has enormous advantages" admitted the president of the Nobel jury before adding " Its rapid development has also raised concerns about our future" she added.
The risk of an AI “takeover”
Geoffrey Hinton, while enthusiastic about the progress made in the field of artificial intelligence, has already expressed his concerns about the long-term consequences of this technology. When he announced his departure from Google in May 2023, Hinton notably warned of the risks of uncontrolled development of AI, fearing that systems more intelligent than humans could end up "taking control". Despite this, he remains convinced of the importance of his research and its positive impact, acknowledging that he is an avid user of AI, and particularly of ChatGPT, but while remaining vigilant about their repercussions. Creator of ChatGPT, doesn't OpenAI also aim to create a new stage in the development of AI, that of a superhuman AI ?…
Call for collective responsibility
Raising these concerns at an event like the Nobel highlights the ethical dilemmas society faces as AI tools become increasingly powerful. The Nobel Committee has emphasized this collective responsibility, stressing that how the newly Nobel-winning work is used in the future will depend on “ of how we humans will choose to use these incredibly powerful tools"It will also depend on the decisions taken - or not - to regulate its use.
For now, let's bet that the work of Hinton and Hopfield is fully in line with this virtuous tradition of the Nobel Prize. Thanks to them, artificial intelligence has become not only an essential field of study, but also, let's not forget, a tool for innovation and progress.
