Alex Galvagni, CEO of Age of Learning and a former artificial intelligence researcher with NASA, says advances in AI now make it possible to deliver to children "a personalized and supportive" experience in education. Two pioneers of artificial intelligence -- John Hopfield and Geoffrey Hinton -- won the Nobel Prize in physics Tuesday for helping create the building blocks of machine learning that is revolutionizing the way we work and live but also creates new threats for humanity. Hinton, who is known as the godfather of artificial intelligence, is a citizen of Canada and Britain who works at the University of Toronto, and Hopfield is an American working at Princeton. "These two gentlemen were really the pioneers," said Nobel physics committee member Mark Pearce. "They ... did the fundamental work, based on physical understanding which has led to the revolution we see today in machine learning and artificial intelligence."

Geoffrey Hinton, one of the so-called'Godfathers of AI' has won a Nobel Prize for pioneering the very same technology he fears could result in the "end of people." Hinton and fellow AI researcher John J. Hopfield were awarded the Nobel Prize in Physics on Tuesday for their crucial early work on artificial neural networks, which have since formed the foundation for powerful AI models developed by Google, OpenAI, and others. The pair's work, which draws on inspiration from the human brain's architecture, paved the way for advancements in machine learning used in everything from fraud detection to driverless vehicles. In Hinton's view, the tech he helped pioneer may also pose a profound risk to human safety. Hopfield and Hinton are credited with advancing the study of neural networks in the 1970s and '80s during a time when it was still unclear that the field would mature into the behemoth it is today.

Two scientists have been awarded the Nobel Prize in Physics "for foundational discoveries and inventions that enable machine learning with artificial neural networks." John Hopfield, an emeritus professor of Princeton University, devised an associative memory that's able to store and reconstruct images and other types of patterns in data. Geoffrey Hinton, who has been dubbed the "Godfather of AI," pioneered a way to autonomously find properties in data, leading to the ability to identify certain elements in pictures. "This year's physics laureates' breakthroughs stand on the foundations of physical science. They have showed a completely new way for us to use computers to aid and to guide us to tackle many of the challenges our society face," the committee wrote on X. "Thanks to their work humanity now has a new item in its toolbox, which we can choose to use for good purposes. Machine learning based on artificial neural networks is currently revolutionizing science, engineering and daily life."

Large language models can do jaw-dropping things. But nobody knows exactly why. Two years ago, Yuri Burda and Harri Edwards, researchers at OpenAI, were trying to find out what it would take to get a large language model to do basic arithmetic. The models memorized the sums they saw but failed to solve new ones. By accident, Burda and Edwards left some of their experiments running for days rather than hours.

Hinton shares the award with fellow computer scientist John Hopfield, who invented a type of pattern-matching neural network that could store and reconstruct data. Hinton built on this technology, known as a Hopfield network, to develop backpropagation, an algorithm that lets neural networks learn. Hopfield and Hinton borrowed methods from physics, especially statistical techniques, to develop their approaches. In the words of the Nobel Prize committee, the pair are recognized "for foundational discoveries and inventions that enable machine learning with artificial neural networks." But since May 2023, when MIT Technology Review helped break the news that Hinton was now scared of the technology that he had helped bring about, the 76-year-old scientist has become much better known as a figurehead for doomerism--the idea that there's a very real risk that near-future AI could precipitate catastrophic events, up to and including human extinction.

The 2024 Nobel Prize in Physics has been awarded to two scientists for developing the methods which lay the foundations for today's powerful AI. John Hopfield and Geoffrey Hinton received the prestigious award for'foundational discoveries and inventions that enable machine learning with artificial neural networks.' John Hopfield, of Princeton University, invented the first methods which allowed machine learning systems to save and recreate patterns. Geoffrey Hinton, of the University of Toronto, gave these networks the ability to find specific properties, allowing them to complete tasks like recognising elements in pictures. These scientists' discoveries paved the way for the artificial neural networks which power modern chatbots such as ChatGPT.

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's large language models like ChatGPT. How this moment for AI will change society forever (and how it won't) There is no doubt that the latest advances in artificial intelligence from OpenAI, Google, Baidu and others are more impressive than what came before, but are we in just another bubble of AI hype? "I'm flabbergasted, I had no idea this would happen," Hinton told the Nobel committee upon hearing the prize announcement. Hinton, who has been vocal about his fears around the development of artificial intelligence, also reiterated that he regretted the work he had done. "In 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," he said.

John Hopfield and Geoffrey Hinton have won the Nobel Prize in physics 2024 for their pioneering work in the field of machine learning. The Royal Swedish Academy of Sciences said on Tuesday the scientists were honoured "for foundational discoveries and inventions that enable machine learning with artificial neural networks". Hopfield, whose research is carried out at Princeton University in the United States, was recognised for creating an associative memory that can store and reconstruct images and other types of patterns in data. Hinton, who works at the University of Toronto, invented a method that can autonomously find properties in data, allowing it to perform tasks such as identifying specific elements in pictures. "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," says Ellen Moons, chair of the Nobel Committee for Physics.

A pair of AI scientists won the Nobel Prize in physics on Tuesday for foundational discoveries and inventions that enable machine learning with artificial neural networks. John J. Hopfield, a professor at Princeton University, and Geoffrey E. Hinton, a professor at the University of Toronto, used tools from physics to develop methods that became the foundation of today's powerful machine learning, the Nobel Foundation said. "When we talk about artificial intelligence, we often mean machine learning using artificial neural networks. This technology was originally inspired by the structure of the brain," the foundation said. "This year's laureates have conducted important work with artificial neural networks from the 1980s onward."

When Prof Hinton resigned from Google last year, he told the BBC some of the dangers of AI chatbots were "quite scary". He also said at the time that his age had played into his decision to leave the tech giant. Earlier this year, in an interview with BBC Newsnight, he said the UK government will have to establish a universal basic income to deal with the impact of AI on inequality, as he was "very worried about AI taking lots of mundane jobs". He added that while AI would increase productivity and wealth, the money would go to the rich "and not the people whose jobs get lost and that's going to be very bad for society". In the same interview, he said developments over the last year showed governments were unwilling to rein in military use of AI while the competition to develop products rapidly meant there was a risk tech companies wouldn't "put enough effort into safety".