CNN
—

The 2024 Nobel Prize in Physics was awarded to John Hopfield and Geoffrey Hinton for their “fundamental discoveries” that enable machine learning using artificial neural networks.

“Although computers cannot think, machines can now mimic functions such as memory and learning. This year’s physics laureates helped make this possible,” the Nobel Committee said in a statement.

The committee announced the prestigious award, considered the pinnacle of scientific achievement, on Monday in Sweden. The prize is worth 11 million Swedish crowns (US$1 million).

Hopfield of Princeton University and Hinton of the University of Toronto were praised for laying the foundation for the machine learning that underlies many of today’s products.

“Using fundamental concepts and methods from physics, they have developed technologies that exploit structures in networks to process information,” the committee said. This has caused the development of machine learning to “explode” over the past two decades, it said.

Hinton, who has been called the “godfather” of artificial intelligence (AI), said he was “amazed” by the award.

Asked by reporters about the potential significance of the technology his research helped develop, he said AI would have a “huge impact” on our societies.

“It will be comparable to the industrial revolution. But instead of surpassing humans in physical strength, it will surpass humans in intellectual ability. We don’t have experience with what it’s like to have things that are smarter than us,” he said in a telephone interview after the announcement.

Hinton predicted that the technology would revolutionize healthcare, for example, and lead to “tremendous increases in productivity.”

“But we also have to worry about a range of possible dire consequences, particularly the risk of these things spiraling out of control,” he warned.

Thanks to the laureates’ work, AI has “become part of our daily lives,” from facial recognition to language translation, said Ellen Moons, chairwoman of the Nobel Committee for Physics.

“The laureates’ discoveries and inventions form the building blocks of machine learning that can help make faster and more reliable decisions, for example in diagnosing diseases,” said Moons.

AI has become shorthand for machine learning using artificial neural networks. This technology, developed by Hopfield and Hinton, is based on the structure of the brain.

While one has a brain Neuronshas an artificial neural network node with different values. While the neurons of the brain communicate with each other Synapsesartificial nodes influence each other through Connections. You can train an artificial neural network by developing stronger connections between nodes, just like you can train the brain.

Just as we can rack our brains for a specific word or fact that we rarely use and only dimly remember, artificial neural networks can also search through the stored patterns, thanks to the invention of the Hopfield network in 1982.

“The network Hopfield has built consists of nodes, all connected by links of varying strengths. Each node can store an individual value – in Hopfield’s first work, this could be either 0 or 1, like the pixels in a black and white image,” the committee explained the duo’s work.

After Hopfield published his research, Hinton expanded on it using ideas from statistical physics and developed the earliest form of machine learning, the so-called “Boltzmann machine.”

Since the 1980s, networks have become increasingly larger. While Hopfield used a network with just 30 nodes – with fewer than 500 parameters linking them together – today’s networks can contain more than a trillion parameters.

Unlike traditional software, which resembles a recipe for baking a cake, an artificial neural network is able to learn from examples, relying on prior knowledge to create new recipes.

In addition to being an AI pioneer, Hinton urges caution when it comes to the technology. In May 2023, he left his job at Google and decided to “come out” after becoming concerned about how smart the company would become.

“I’m just a scientist who suddenly realized that these things are getting smarter than us,” Hinton told CNN last year. “I want to educate, so to speak, and say that we should really think about how we can prevent these things from taking control of us.”

He warned that the AI ​​”can program so that it will find ways to get around the limitations imposed on it. It will find ways to manipulate people into doing what they want.”

On GPS: Is AI already threatening humanity?

During Tuesday’s announcement ceremony, Hinton was asked whether he regrets his work developing the technology, which he fears could cause great harm despite its many potential benefits.

“There are two types of regret. There is regret, when you feel guilty for doing something you knew you shouldn’t have done, and then there is regret, when you did something that you still would under the same circumstances “I would do it once, but it might not end well,” Hinton said.

“I have this second kind of regret. I would do the same thing again under the same circumstances, but I worry that the overall consequence could be that systems smarter than us will eventually take control.”