The 2024 Nobel Prize in Physics was awarded to Geoffrey Hinton and John Hopfield for their groundbreaking work on artificial neural networks. Hinton, often called the "godfather of artificial intelligence," suggests that AI will soon surpass human intelligence. What does this mean for healthcare?
The trick of mimicking the human brain
John Hopfield, professor emeritus at Princeton University (US), and Geoffrey Hinton, professor emeritus at the University of Toronto (Canada), were awarded for “foundational discoveries and inventions that enable machine learning with artificial neural networks.” The scientists’ early work became the backbone of generative AI systems like ChatGPT or Gemini. Notably, Sam Altman, the CEO of OpenAI, was one of Hinton’s students.
Their journey with AI began in the 1980s. Both scientists contributed to developing computer systems that mimic how neurons in the human brain exchange information. Their work paved the way for modern machine learning, an approach that allowed the creation of precise face recognition and language translation systems, with many more AI systems being created later.
Hopfield developed a network that stores and recreates patterns using principles from physics, specifically atomic spin systems, to minimize energy and recognize images. The network adjusts node values to reduce energy and identify saved images, even from incomplete inputs. Hinton extended this idea to create the “Boltzmann machine,” which learns to recognize characteristic features in data by employing concepts from statistical physics.
In medicine, trained on the vast amount of data, machine learning applications can, for example, detect cancerous lesions—without the need to program the system. It’s because as soon as AI gets the data, it starts to learn to recognize patterns autonomously, much like humans, by exchanging information between artificial neurons.
Why a Nobel prize in physics for breakthrough discoveries in AI?
The decision to award the Nobel Prize in Physics for AI work might seem unusual. However, as the committee noted, artificial neural networks have played a significant role in fields like particle physics and astrophysics.
“The laureates’ work has already been of the greatest benefit. In physics, we use artificial neural networks in a vast range of areas, such as developing new materials with specific properties,” according to Ellen Moons, Chair of the Nobel Committee for Physics.
Today, machine learning systems are part of everyday life, from text translation on Google or DeepL to interactions with AI tools like ChatGPT and Perplexity. As there is no dedicated Nobel category for AI, the Physics Prize became the most fitting recognition.
Hinton’s missed predictions for healthcare
Geoffrey Hinton hit the headlines not only for his innovations but also for his warnings about AI’s potential risks. After leaving Google, Hinton warned that AI could displace jobs, including those in healthcare. In 2016, he famously predicted that AI would replace radiologists within five years—a claim that has not yet come to pass. Eight years later, radiologists remain indispensable, and AI has only a limited role in their work.
When asked about AI’s future after receiving the Nobel Prize, Hinton likened AI’s impact to the Industrial Revolution. While machines have surpassed humans in terms of physical strength, he believes AI will soon surpass us intellectually. He predicts that we will see breakthroughs in medicine, especially in drug development and the rise of digital assistants, including digital doctors. Yet, he also warned that AI systems that are more intelligent than humans could become dangerous someday.
“I’m hoping AI will lead to tremendous benefits, to tremendous increases in productivity and to a better life for everybody. I’m convinced that it will do that in healthcare,” commented Hinton shortly after receiving the information that he won the 2024 Nobel Prize.
Medicine will benefit the most
Despite the inaccurate prediction about radiologists, Hinton remains cautiously optimistic about AI’s future in healthcare. In a 2023 interview with digital health expert Eric Topol, he suggested that within 10 to 15 years, AI systems will be regularly used to provide second opinions and could surpass doctors in specific aspects of clinical decision-making.
Hinton believes that large-scale language models (LLMs) truly “understand” tasks beyond mere statistical analysis, signaling that general artificial intelligence could be on the horizon. Although some remain skeptical about machines outperforming doctors, the rapid progress in AI makes this outcome increasingly difficult to dismiss. The challenge now lies in regulating AI’s use and addressing its ethical implications.
AI promises to bring personalized treatment into routine practice. With access to patient data, AI—especially LLMs—will help doctors make accurate diagnoses and treatment decisions. It will also provide patients with a second opinion, improving their understanding of medical conditions. A new wave of well-being AI advisors will offer insights into health risks and guide us through daily decisions so they are tailored to our health goals.
When an AI pioneer like Hinton raises concerns about its potential dangers, it’s understandable to feel uneasy. However, Hinton remains hopeful about AI’s future. He envisions a scenario where AI, becoming smarter than humans, could act as a “kind parent” for humanity, addressing global crises such as environmental, economic, and social challenges.
