AI pioneers Geoffrey Hinton and John Hopfield win the Nobel Prize in Physics

Geoffrey Hinton and John Hopfield were honored Tuesday with the Nobel Prize in Physics for their work on artificial neural networks over the past four decades. They will share the 11 million Swedish krona ($1.06 million) prize associated with the prize.

Hinton, 76, is by far the better known of the two. Hinton is sometimes referred to as one of the “Godfathers of AI,” along with Yoshua Bengio and Yann LeCun. Last year he dramatically quit Google, publicly warning about the short- and long-term risks of the technology he helped develop. He said he regrets his life's work because AI is too easily abused; He believes this could increase inequality and perhaps even lead to the subjugation of humanity.

Now he has received the ultimate award for this work – one even more prestigious than the Turing Award shared by Hinton, Bengio and LeCun in 2019.

Neither Hopfield nor Hinton were the first people to develop artificial neural networks or suspect that they could provide a way to develop artificial intelligence.

But Hopfield, 91, helped lay the foundation for today's AI with a 1982 paper describing a brain-inspired network that could store and recall patterns and had the ability to best match even partial inputs .

A few years later, Hinton and two other researchers (David Ackley and Terry Sejnowski) used the Hopfield network as the basis for their invention of the so-called Boltzmann machine – another network model architecture that can classify images and iterate on their training material. However, the Boltzmann machine turned out to be nowhere near as scalable as today's machine learning systems.

However, Hinton is perhaps better known today for his work with David Rumelhart and Ronald Williams on “gradient descent,” a method that allows large, multilayer neural networks to learn efficiently.

There is no Nobel Prize category that can be clearly attributed to the emerging AI sector – or even to computer science.

Some have previously suggested that an AI scientist could win a Nobel Prize by applying their technology in a more established field such as chemistry or physics. But in this case, the Royal Swedish Academy of Sciences chose to highlight both the physical origins and applications of Hinton and Hopfield's work.

“The work of the award winners has already been of great benefit. In physics, we use artificial neural networks in a variety of areas, such as developing new materials with specific properties,” said Ellen Moons, Chair of the Nobel Physics Committee.

It is certainly true that Hopfield and Hinton's work also drew on the field of statistical physics, alongside other areas such as neurobiology and cognitive psychology. Hopfield was awarded the Boltzmann Medal for Statistical Physics just two years ago.

Still, some in the physics community are upset that their Nobel Prize goes to machine learning pioneers who did not explicitly work on fundamental physics research.

“I don't want to downplay their successes, but the connection to physics is (tenuous) at best,” reads the most upvoted comment about the development in the physics subreddit. “There is already too much real physics that still needs to be rewarded.”