Unraveling Genius: How a Nobel Breakthrough Unleashed a Double-Edged Revolution in Artificial Intelligence

Unraveling Genius: How a Nobel Breakthrough Unleashed a Double-Edged Revolution in Artificial Intelligence

There are various debates about whether and how artificial intelligence will change the world. This week’s list of winners of the Nobel Prize in Physics and Chemistry emphasizes that this technology has changed science itself behind the scenes, helping to solve difficult problems and analyze large amounts of scientific data, but it is not All researchers are pleased with the results.

On Tuesday, AI godfather Geoffrey Hinton and molecular biology professor John Hopfield won this year’s Nobel Prize in Physics for their work on machine learning in the 1970s and 1980s. They each used physics concepts to invent artificial neural networks, causing and promoting artificial intelligence. develop.

On Wednesday, Google DeepMind CEO Demis Hassabis, DeepMind director John Jumper, and University of Washington biochemistry professor David Baker jointly received the Nobel Prize in Chemistry. The AlphaFold 2 artificial intelligence system developed by DeepMind effectively solves one of the most difficult problems in biology for half a century: predicting the complex structure of proteins; David Baker developed another protein prediction tool driven by artificial intelligence, RoseTTAFold, and also designed a new protein.

Generally speaking, the Nobel Prize is usually awarded to research completed decades ago, so that there is time to clearly evaluate whether the research content is in the best interest of mankind.

However, Google’s DeepMind company first launched the AlphaFold 2 system 4 years ago. The Nobel Prize Committee believes that the system has now been used by scientists around the world to solve a series of scientific problems, including exploring antibiotic resistance, drug design, crop resilience, etc. , the DeepMind team is also continuing to improve the system version.

Should AI be given its own category?

Despite this, social media was in an uproar shortly after the Nobel Prize in Physics was announced. Several physicists believed that the machine learning research conducted by Geoffrey Hinton and John Hopfield was not based on traditional physics.

Sabine Hossenfelder, a physicist at the Center for Mathematical Philosophy in Munich, Germany, said that the research of Geoffrey Hinton and John Hopfield belongs to the “field of computer science” rather than physics. The annual Nobel Prize in Physics should allow the public to get to know a person who has been involved in basic scientific research for many years. physicist, but not this year.

Noah Giansiracusa, associate professor of mathematics at Bentley University in the United States, said that even with inspiration from physics, Geoffrey Hinton and John Hopfield did not develop new physics theories or solve long-standing problems in physics.

However, some physicists approve of this year’s winners. They believe that Geoffrey Hinton and John Hopfield’s research is interdisciplinary and combines physics, mathematics, computer science, and neuroscience. California science writer Anil Ananthaswamy pointed out that the Nobel Committee cited Although the research is not the purest form of theoretical physics, it is certainly rooted in physics techniques and concepts.

With the rise of artificial intelligence, we will definitely see more researchers using artificial intelligence tools win Nobel medals in the future. Perhaps the world is progressing, and the boundaries of physics, chemistry, and medical scientific methods recognized by the Nobel Prize are gradually blurring. Perhaps Artificial intelligence needs its own Nobel Prize category.

(Source of first picture:pixabay

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