The 2024 Nobel prize in physics has been awarded to John Hopfield and Geoffrey Hinton for their work on artificial neural networks and the fundamental algorithms that let machines learn, which are key to today鈥檚 large language models like ChatGPT.

鈥淚鈥檓 flabbergasted, I had no idea this would happen,鈥� Hinton told the Nobel committee upon hearing the prize announcement. 鈥淚鈥檓 very surprised.鈥� Hinton, who has been vocal about his fears around the development of artificial intelligence, also reiterated that he regretted the work he had done. 鈥淚n the same circumstances, I would do the same again, but I am worried that the overall consequences of this might be systems more intelligent than us that eventually take control,鈥� he said.

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While AI might not seem like an obvious contender for the physics Nobel, the discovery of neural networks that can learn and their applications are two areas that are intimately connected to physics, said Ellen Moons, chair of the Nobel Committee for Physics, during the announcement. 鈥淭hese artificial neural networks have been used to advance research across physics topics as diverse as particle physics, material science and astrophysics.鈥�

Many early approaches to artificial intelligence involved giving computer programs logical rules to follow to help solve problems, but this made it difficult for them to learn about new information or encounter situations they hadn鈥檛 seen before. In 1982, Hopfield, at Princeton University, created an architecture for a computer called a Hopfield network, which is a collection of nodes, or artificial neurons, that can change the strength of their connections with a learning algorithm that Hopfield invented.

That algorithm was inspired by work from physics that finds the energy of a magnetic system by describing it as collections of tiny magnets. The technique involves iteratively changing the strength of the connections between the magnets in an attempt to find a minimum value for the energy of the system.

In the same year, Hinton, at the University of Toronto, began developing Hopfield鈥檚 idea to help create a closely related machine learning structure called a Boltzmann machine. 鈥淚 remember going to a meeting in Rochester where John Hopfield talked and I first learned about neural networks. After that, Terry [Sejnowski] and I worked feverishly to work out how to generalise neural networks,鈥� he said.

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Hinton and his colleagues showed that, unlike previous machine learning architectures, Boltzmann machines could learn and extract patterns from large data sets. This principle, when combined with large amounts of data and computing power, has led to the success of many artificial intelligence systems today, such as image recognition and language translation tools.

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However, while the Boltzmann machine proved capable, it was also inefficient and slow, and it isn鈥檛 used in modern systems today. Instead, faster, modern machine learning architectures like transformer models, which power large language models like ChatGPT, are used.

At the Nobel award conference, Hinton was bullish on the impact that his and Hopfield鈥檚 discoveries would have. 鈥淚t will be comparable with the industrial revolution, but instead of exceeding people in physical strength, it鈥檚 going to exceed people in intellectual ability,鈥� he said. 鈥淲e have no experience of what it鈥檚 like to have things smarter than us. It鈥檚 going to be wonderful in many respects鈥� but we also have to worry about a number of bad consequences, particularly the threat of these things getting out of control.鈥�

Could AI soon write your favourite Hollywood film or streaming show? That concern is one of the issues driving a US film and television writers鈥� strike that has halted many productions nationwide.

The Writers Guild of America (WGA), a labour union representing writers who primarily work in film and television, began the work strike this month after reaching an impasse in negotiations with the Alliance of Motion Picture and Television Producers that represents the US entertainment industry. Part of the disagreement revolves around a to ban the industry from using AIs such as ChatGPT to generate story ideas or scripts for films and shows 鈥� the union wants to ensure that such technologies do not undermine writers鈥� compensation and writing credits.

鈥淭he fear is that AI could be used to produce first drafts of shows, and then a small number of writers would work off of those scripts,鈥� says at Cornell University in New York.

The WGA has also proposed that any scripts covered by the union鈥檚 collective bargaining agreement cannot be used to train AIs. There has already been broader resistance against tech companies scraping online content for free to train large language models and other generative AIs on text and images originally created by humans.

Hollywood studios on the other side of the negotiating table include companies such as Walt Disney Studios and Warner Bros. Studios, along with streaming services such as Netflix, Apple TV+ and Amazon Prime Video.聽The industry rejected the initial WGA proposal and countered with an offer to hold annual meetings to discuss new technological changes.

鈥淭his is a pretty weak commitment 鈥� the writers would have little power in those discussions to influence how the technologies are used,鈥� says Doellgast. 鈥淭he studios don鈥檛 want to negotiate hard limits on how they will use AI.鈥�

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The Alliance of Motion Picture and Television Producers on 4 May saying that 鈥淎I raises hard, important creative and legal questions for everyone鈥�. It also noted that the previous and now-expired agreement with the WGA already defined a writer as a 鈥減erson鈥� and would exclude AI from receiving a writing credit.

The writers鈥� strike comes at a time when the separate union representing actors and other performance artists is also looking to regulate possible uses of AI, including using or digitally edit filmed facial expressions and sync new audio to people鈥檚 lips.

鈥淭he WGA鈥檚 demands are a bellwether that workers don鈥檛 intend to stand for companies using AI to justify devaluation of their craft and expertise,鈥� says聽 at the AI Now Institute in New York. 鈥淭he WGA is pointing out an important question 鈥� who is benefiting from the development and use of these systems, and who is harmed by them?鈥�

Workers in other industries 鈥� such as accounting and IT support, customer service and software programming 鈥� are already seeing companies use AI to automate parts of their jobs and sometimes even to replace human workers. By comparison, writers 鈥渉ave a strong union backing them up and solidarity from other creative workers in their industry鈥�, along with higher individual bargaining power and in-demand skills, says Doellgast.

Beyond the AI issue, the writers鈥� strike is also focused on how the shift in viewing habits from TV broadcast networks to streaming services has impacted writers鈥� income and job security, says Doellgast. For example, writing jobs are now typically based on shorter seasons with fewer episodes for shows produced by platforms such as Netflix or Amazon Prime Video.

Companies have often won out in historical labour conflicts over technological automation of human work. But there have been cases where workers stood their ground: for example, in the 1960s unions representing US dock workers negotiated for employment security against tech-driven downsizing and for a pension fund for early worker retirement.

It may be difficult to stop the eventual use of AI in creative fields like TV and filmmaking. But in the case of the writers鈥� strike, an amicable agreement granting the WGA more control over how AI is used in scriptwriting could ensure that writers reap some benefits, even if part of their work gets automated, says at the Massachusetts Institute of Technology.

鈥淭he short-term key is who will control AI 鈥� labour or capital,鈥� says Johnson. 鈥淚f capital controls it, labour will lose big time and fast.鈥�