John Hopfield and Geoffrey Hinton have won the Nobel Prize in Physics for their seminal work on artificial intelligence that has contributed to scientific progress, the Financial Times reports.
Hinton, who left Google last year, was âblown awayâ by the honorary title. He noted AIâs advances in healthcare and productivity, but also called for concern about a range of potential negative consequences, especially if neural networks get out of control.
Hopfield and Hinton received the 11 million Swiss crown ($1.06 million) prize for their "fundamental discoveries and inventions" in the field of machine learning since the 1980s.
Their work helped develop so-called artificial neural networks, which mimic the human brain's biological circuitry for processing information.
"It will have a huge impact, comparable to the Industrial Revolution. But instead of surpassing humans in physical strength, it [AI] will surpass them in intellectual ability. We have no experience of what it is like to have things smarter than us," Hinton said.
American physicist Hopfield developed an artificial neural network to store and recreate patterns. Hinton, considered one of the "godfathers" of AI in tech circles, used Hopfield's work to create a network known as a Boltzmann machine.
The Nobel Prize organisers noted that both scientists helped "initiate the current explosive development of machine learning".
âIn short, machines are helping us understand ourselves, which in turn opens up new possibilities for technological advances. None of this would be possible without the seminal work of Hopfield and Hinton,â said Rhodri Cusack, a cognitive neuroscientist at Trinity College Dublin.
Royal Society President Adrian Smith noted Hinton's research, which compares brain damage in humans with loss of function in neural networks.
"He found striking similarities to human impairments, such as name recognition and loss of categorization. This could be the beginning of the creation of autonomous intelligent brain-like machines," Smith added.
Nobel Physics Committee Chair Ellen Moons emphasized that machine learning has become part of our everyday lives, mentioning facial recognition, language translation and medical diagnostics.
"While machine learning brings enormous benefits, its rapid advancement raises concerns about our future. Humans have a collective responsibility to use new technology safely and ethically for the greatest good of humanity," she said.
Let us recall that Nobel Prize winner in economics Daniel Kahneman believes that machine intelligence will surpass human intelligence, but it is still far from this.
