Some Thoughts on AI and Unsolved Puzzles of Physics

Recently a lot of attention has focused on Artificial Intelligence (AI) to help the human mind to attack all kinds of problems. A natural question is whether AI can help us solve some of the outstanding puzzles facing physics today. In a recent post in this website (December 2023) we discussed a personal view of the most important discoveries in physics (I must emphasize the words “personal view” as different people could have much different choices). For example, as we already mentioned in that article, Dmitri Mendeleev of the Periodic Table and some of the major discoveries regarding the origin and development of the universe are not on that list. The 12 items that appeared in the list are the following:

  1. Mechanical Laws of Motion
  2. Law of Gravitation
  3. Thermodynamics
  4. Electrodynamics (or Theory of Electricity and Magnetism)
  5. Theory of Relativity (both Special Theory and General Theory)
  6. Theory of the Nucleus and the Atoms
  7. Quantum Physics
  8. Quantum Electrodynamics (QED)
  9. Discovery of the Weak Force and Formulation of the Electroweak Force
  10. Modern Building Blocks of Matter
  11. Standard Model of Particle Physics
  12. Bell’s Theorem and Experimental Confirmation of Quantum Physics

However, as pointed out in that Dec. 2023 article, we also wrote ”that in spite of all the discoveries in the last half century, there are still several major mysteries”:

  • Dark matter: Dark matter is matter in our universe which cannot be seen, because they don’t interact electromagnetically, and they don’t interact through the strong force and maybe also through the weak force, but they interact through the gravitational force. Ordinary matter make up only about 5% of the universe, but dark matter consist of about 27%.
  • Dark energy: Dark energy is a theoretical repulsive force that counteracts gravity and causes the universe to expand at an accelerating rate, and it makes up 68% of our universe.
  • Matter-antimatter asymmetry: Almost all of the matter we see in the universe is made up of matter, but matter and antimatter should have been created in equal amounts when the original universe is made up of energy.

Therefore, major discoveries are waiting to be discovered to answer these questions. Perhaps, this means that the greatest discoveries may still be waiting to be discovered.
We have no illusion that these discoveries will be easy to be discovered. Furthermore, even with the support of AI, it may not be discovered without creative thinkers and deep knowledge of what transpired in the minds of the great physicists during the last several hundreds of years. Nevertheless, we believe that AI could help us in solving some of the mysteries facing us, perhaps even in the three mysteries just mentioned.

We believe that this faith is not just based on wishful thinking, but it is based on what went on with respect to some of the things that happened related to some of the great discoveries in the last 75 years. This was pointed out in the earlier article “Some Thoughts on AI and Frontiers of Science” (posted in the June 2023 issue of this website), which we will repeat here to serve as lead ins to the current discusssion of AI and unsolved puzzles of physics.

Examples of Possible Leads as Input to AI-Enabled Computers: We probably can discuss for hours on the definition of creativity and wouldn’t be able to come to agreement on its definition and whether computers can exhibit that. However, let’s not talk in abstract, and actually look at some of the discoveries in the last 50-100 years that were considered to be major discoveries. In particular, consider the field of high energy physics (or elementary particle physics). In my opinion, some of those discoveries could have come from computers with suitable questions or inputs from a knowledgeable researcher or a team of knowledgeable researchers, then with the help of AI-capable computer(s), some leads suggested to the computer could enable the computer and/or researcher(s) to make the new discovery. Here are a few examples:

  • For the asymptotic freedom theory (leading to Quantum Chromodynamics or QCD, the current theory of strong interactions of quarks and gluons) of Yang-Mills gauge theory from the work of Politzer, and Gross and Wilczek in 1972-1973 that resulted in their 2004 Nobel Prize in Physics, it turned out that two-three years earlier Anthony Zee investigated several theories for this asymptotic freedom property. Unfortunately for him, one of the few theories that he didn’t investigate was Yang-Mills gauge theory. If he did, he probably would have discovered it. So if someone in 1970-1971 had fed this information to an AI-enabled computer and asked the computer the question what other theories they could have investigated for this property, the computer might have suggested Yang-Mills gauge theory for investigation and then the researcher would have discovered it.
  • Even parity violation of Lee and Yang for their 1956 work with respect to weak interactions. If someone had fed the information to a smart computer that there were strong experimental data to support conservation of parity in strong and electromagnetic interactions, and had asked a smart computer to search for evidence of conservation of parity in weak interactions, the computer would have answered that there was not much evidence, and they could have proposed non-conservation of parity in weak interactions before Lee and Yang, which was what Lee and Yang did.
  • Even on the question of the expansion of the universe originally discovered by Hubble in the 1920s (Hubble didn’t get the Nobel Prize in Physics because at that time astronomy was not considered part of physics) and the more recent accelerated expansion discovery of the universe by Perlmutter/Schmidt/Riess (Nobel Prize in Physics in 2011), a computer with the right inputs and the right questions could have discovered or led to discover that.
  • Three-degree cosmic background radiation that got Penzias and Wilson of Bell Labs their 1978 Nobel Prize in Physics for their work in the mid-1960s could have been discovered by a smart computer with the right questions and inputs, instead of the accidental discovery of Penzias and Wilson (at first, they were uncertain what they discovered), even though at that time a group at Princeton was looking for that kind of astrological evidence). But they didn’t have smart computers with AI in the early-mid 1960s. If there were, more groups might have looked into this area of research around the time of discovery of Penzias and Wilson.

This is not taking away any credit from the people who achieved these past achievements, because they deserve all the credits that they received.

I think if we work on it, we could come up with many other new ideas or discoveries not only in physics, but also in other fields, that could have been made or led researchers to by computers with AI, as long as appropriate questions and relevant data are input to the AI-enabled computers. Of course, this may be an iterative process, meaning there could be going back and forth with the AI-enabled computers before a meaningful new idea or discovery will emerge, or before a new idea that could lead to a new discovery will emerge.

We have actually tried this approach with the basic version of ChatGPT ( by asking the question why there is so much matter over anti-matter in our current observed universe. However, the current responses are not much meaningful and far from leading us to more worthwhile research areas to pursue further research.

We welcome comments from our readers. Perhaps we are too naive to believe that such a simple approach could lead to fruitful research. Perhaps we need to feed the AI-enabled computers with more meaningful questions to probe so that the AI-enabled computers can come up with more meaningful ideas that can lead us to do more meaningful research and lead to new discoveries.

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