Blue Whale News, October 8 (Reporter Zhu Junxi) On October 8, local time, the Royal Swedish Academy of Sciences announced that it will award the 2024 Nobel Prize in Physics to John and recognize their pioneering efforts in using artificial neural networks to achieve machine learning. Sexual discovery.

The Nobel Prize Committee said on social media X, “This year’s Nobel Prize winners’ breakthroughs are built on the basis of physical science. They show us a completely new way to leverage computers to help and Guide us to deal with the many challenges facing society.”

The committee further explained that the artificial intelligence that people frequently mention now refers to machine learning using artificial neural networks. Since the 1980s, two winners have begun to conduct important research on artificial neural networks. They developed methods using physics tools to lay the foundation for today's powerful machine learning. Benefiting from these efforts, humans now have new tools, and machine learning based on artificial neural networks is revolutionizing science, engineering, and everyday life.

Born in 1933, John is currently a professor at Princeton University in the United States. He is famous for his contributions to physics and neural networks. In 1982, John proposed the Hopfield Network, which had a profound impact on the development of artificial intelligence and neural networks. This network mimics human memory mechanisms, similar to synaptic connections between neurons in the brain, and can store and restore images and other data patterns by adjusting connections between nodes in the network.

The Nobel Prize Committee introduced that the Hopfield Network has used the concept of spin systems in physics. When a distorted or incomplete image is input, the Hopfield network will process the nodes in an orderly manner and update their values, gradually finding the closest complete image.

Another Nobel Prize winner in physics is also widely known as the "father of neural networks" and the "godfather of AI". He is one of the leading figures in the fields of artificial intelligence and deep learning. His students and descendants are spread throughout the AI ​​academic community. and industry. Born in the UK in 1947, he is currently a professor at the University of Toronto, Canada. He has worked at Google for nearly 10 years, serving as vice president and engineering researcher, helping Google make significant progress in the fields of artificial intelligence such as image recognition and voice recognition.

In 2018, for his pioneering contributions in the field of deep learning, Yann LeCun won the Turing Award, which is also the highest honor in the computer science community.

In the introduction, the Nobel Prize Committee pointed out that based on the Hopfield network, a new neural network "Bolzmann Machine" has been developed. With statistical physics tools, Boltzmann machines are able to analyze large amounts of example data to learn and identify specific data features. Further research on this basis has promoted the explosive development of machine learning.

After learning about the award, he told the committee on the phone that he was "shocked" and "had never expected this to happen." He told the media that artificial intelligence would be comparable to the industrial revolution and would bring productivity. Great improvement. AI will surpass humans intellectually rather than physically, "we have never experienced what something smarter than us are."

It also warned to be careful about the adverse consequences of artificial intelligence, "especially the threat of out-of-control events" and worried that systems smarter than humans would take control. The main reason for resigning from Google in 2023 is the hope of being more free to discuss AI-related risks. On its social media X, the latest post is linked to a call for the passage of the controversial California AI Act SB 1047. The bill requires security testing of powerful cutting-edge AI models to protect the public's interests from harm. On September 30, local time, California Governor Gavin formally rejected the bill, believing that the bill may be too broad and will put a burden on AI companies.

In past Nobel Prizes, some of the award-winning research has been closely related to artificial intelligence or machine learning. Taking the Nobel Prize in Economics as an example, Simon, the winner in 1978, was considered one of the founders of the field of artificial intelligence. He proposed pioneering concepts such as "finite rationality" in decision theory, which later directly affected the design of AI systems. .

Research related to AI has also appeared on the shortlist of the Nobel Prize in Physiology or Medicine this year. Although the end of the game has fallen into other countries, the highly-watched candidates include David Baker, a biochemist who introduced deep learning technology into protein structure prediction. And scientists Demis and John of Google's company, who developed AI systems and made revolutionary breakthroughs in the field of protein structure prediction.