The Nobel Prizes in Physics and Chemistry

(Source: Unifying Quantum and Relativistic Theories)

The last few blogs have alternated between descriptions of AI—with its environmental impacts—and the upcoming elections. On a more abstract level, both issues represent key features of our reality: the elections are part of the short term and AI is longer term. My intention in this blog was to focus on the elections, with an emphasis on the frequent polling that all of us are bombarded with. But, as often happens, reality has its own priorities. This week was the announcement of the Nobel Prizes. The second and third Prizes, announced in the beginning of the week (October 8^th and 9^th) were for Physics and Chemistry. Below are the two citations:

Physics:

They used physics to find patterns in information

This year’s laureates used tools from physics to construct methods that helped lay the foundation for today’s powerful machine learning. John Hopfield created a structure that can store and reconstruct information. Geoffrey Hinton invented a method that can independently discover properties in data and which has become important for the large artificial neural networks now in use.

Chemistry:

They cracked the code for proteins’ amazing structures

The Nobel Prize in Chemistry 2024 is about proteins, life’s ingenious chemical tools. David Baker has succeeded with the almost impossible feat of building entirely new kinds of proteins. Demis Hassabis and John Jumper have developed an AI model to solve a 50-year-old problem: predicting proteins’ complex structures. These discoveries hold enormous potential.

AI is mentioned in both Prizes. The surprise, to me and others, was that AI is not currently directly associated with Physics and certainly not with Chemistry, but the awards were given to scientists with backgrounds in the disciplines that allowed them to make key contributions to machine learning (Physics) and the use of AI in protein chemistry. The technique itself is associated with Computer Science. However, there is no Nobel in Computer Science (according to Wikipedia, “The top computer science award is the ACM Turing Award, generally regarded as the Nobel Prize equivalent for Computer Science.”)

The criteria to receive the Nobel Prizes in Physics and Chemistry are given below:

Who can receive the Prize?

According to Alfred Nobel’s will, the Nobel Prize in Physics is awarded to the person who made the most important discovery or invention in the field of physics and the Nobel Prize in Chemistry to the person who made the most important chemical discovery or improvement.

AI (through Google) tried to clarify the meaning of “most important discovery in the field” in the following way:

According to Alfred Nobel’s will, the key criteria for awarding a Nobel Prize is to recognize the person who has made “the most important discovery” within their field, which must have “conferred the greatest benefit to humankind,” meaning the discovery should be of significant impact and have a positive influence on society at large.

“Conferred the greatest benefit to humankind” might refer to having contributed to changing reality for the betterment of humankind. In an earlier blog titled “The Physics of Reality” (February 2, 2021), I used the Encyclopedia Britannica to define reality in the following way:

Physics, science that deals with the structure of matter and the interactions between the fundamental constituents of the observable universe. In the broadest sense, physics (from the Greek physikos) is concerned with all aspects of nature on both the macroscopic and submicroscopic levels. Its scope of study encompasses not only the behaviour of objects under the action of given forces but also the nature and origin of gravitational, electromagnetic, and nuclear force fields. Its ultimate objective is the formulation of a few comprehensive principles that bring together and explain all such disparate phenomena.

I was not the only skeptic asking whether, in its present form, AI qualifies ():

You might think that the Nobel Prize for Physics would go to a physicist. Not this, year though. As usual, the Prize was shared earlier this week, but both of the winners were computer scientists. It’s as if the Olympic gold for the 100-metre dash had gone to a cyclist.

It should be said that the two laureates, Geoffrey Hinton and John Hopfield, are highly distinguished in their field. However, that field is artificial intelligence (AI), which is not usually regarded as a branch of physics.

So quite a slap in the face for the physicists. But, then, the very next day, came a second slap —  this time for the chemists. The Nobel Prize for Chemistry was another shock win for computer science. One of the three winners, David Baker, has a background in biochemistry, but the other two — John Michael Jumper and Demis Hassabis — are leading AI experts.

The skepticism focused on the present concentration of the technology in the for-profit industry. Below are a few highlights from the NYT on the topic:

Google, thanks to the tens of billions of dollars it makes every year from its online search business, has long pursued giant research projects that could one day change the world.

On Wednesday, the Nobel Prize committee conferred considerable prestige to Google’s pursuit of big ideas. Demis Hassabis, the chief executive of Google’s primary artificial intelligence lab, and John Jumper, one of the lab’s scientists, were among a trio of researchers who received the Nobel Prize in Chemistry for their efforts to better understand the human body and fight disease through A.I.

The two Google scientists won their Nobels a day after Geoffrey Hinton, a former Google vice president and researcher, was one of two winners of the Nobel Prize in Physics for his pioneering work on artificial intelligence.

The Nobel wins were a demonstration of the growing role artificial intelligence is playing in areas far beyond the traditional world of the high-tech industry, and were a reminder of Silicon Valley’s influence in nearly every corner of science and the economy.

But the triumphant moment for Google was tempered by concerns that the commercial success that has allowed the company to pursue these long-term projects is under threat by antitrust regulators. The Nobel awards were also a reminder of worries that the tech industry isn’t paying enough attention to the implications of its open-throttled pursuit of building more powerful A.I. systems.

Dr. Hinton left Google, using his retirement as an opportunity to speak freely about his worry that the race toward A.I. could one day be catastrophic. He said on Tuesday that he hoped “having the Nobel Prize could mean that people will take me more seriously.”

Leading researchers such as Dr. Hassabis often describe artificial intelligence as a way to cure disease, battle climate change and solve other scientific mysteries that have long bedeviled the world’s researchers. The work that won a Nobel was a significant step in that direction.

Out-of-discipline Nobel Prizes are somewhat rare but they do happen. The recent one that comes to mind is the 2002 Prize in Economics, which went to Daniel Kahneman for his contributions to Behavioral Economics. I wrote three earlier blogs on the topics (November 21 – December 5, 2017) with “irrationality” as the common word in the three titles. We will continue to follow AI progress to see if it fits.