New Theory Suggests That The Universe Could Be A Self Learning Computer

A problem has proven impossible to the brightest minds in physics. A new theory suggests that the universe could be a self-learning computer

Albert Einstein and Stephen Hawking, the most famous physicists of the 20th century, spent decades trying to find a unique law that could explain how the world works on the scale of the atom and on the scale of galaxies. In short, the Standard Model describes the physics of the very small. General relativity describes the physics of the very large. The problem? The two theories tell different stories about the fundamental nature of reality.

Now Stephon Alexander, a professor of physics at Brown University, has taken the challenge into his own hands. In a preliminary study that has not yet been peer-reviewed, Alexander and several collaborators, including technologist Jaron Lanier and physicist Lee Smolin, put a slightly different spin on the problem.

Instead of focusing on what the laws of physics are, they wonder why the physical world is governed by certain laws and not others. They write that while physicists have not “finished that task” of discovering the laws of physics, “we seem to know enough to take some steps to answer a deeper question.”

The Universe Is A Self Learning Continuously Improving Computer

His idea is that the physical world as we know it today is not the only true reality, it is the result of many iterations of the universe trying an arrangement of laws that did not work. According to Alexander’s account, our universe has probably taken on the characteristics of many possible universes. Eventually it “found itself in a configuration that was stable” and allowed it to “build itself consistently.”

Compare this process of trying, failing, and trying again to playing an arcade game with a large bag of nickels. “If you have infinite [lives], you play, you die, you play, you keep playing, you die, but you can keep playing, right? I think it’s kind of like the idea, ”he said.

A Self Learning Computer

The universe can always “keep trying.” In this sense, the universe is “learning” what works and what doesn’t as it evolves. Since the universe does not have a teacher but is learning its lessons as it goes, researchers call it “self-taught.”

A Primordial “Meta-Law”

How can this be possible? Alexander’s answer is elegant: a “meta-law” that existed long before the laws of physics that we know as the standard model and general relativity. It is this meta-law that contains the ability to try things and learn. Confusingly, the meta-law is the universe itself, at least in some respects.

“The strange thing here is that the hardware is the software and the software is the hardware,” explains Alexander. General relativity and the standard model emerged later, once the universe found the stability it was looking for. Compare the idea to Darwin’s theory of evolution.

A Self Learning Computer
Stephon Alexander. 
Credit: Dartmouth University.

“In biology, there used to be a ‘Why these species?’ Problem: why do cats and dogs exist while unicorns and werewolves don’t?” The researchers wrote in the study. There they explain that Darwin introduced a handful of principles that govern life in general that make it possible to understand how a specific species arose. 

For example, the idea that species arise because individuals that adapt well to their environment are more likely to pass on valuable traits to their descendants. Finding that first glimpse of those underlying principles was a gigantic achievement, but it wasn’t the end of the story. Researchers have spent 160 years filling in details and they are not done yet.

Alexander and his colleagues do not claim to have discovered the physical equivalent of evolution. Rather, they describe their contribution as “baby steps” toward a complete theory. For Alexander, it was important to propose a formal version of the theory to see if it stands up to the scrutiny of other theoretical physicists and the empirical work of experimentalists.

“We have to commit to something to be able to play and we can try to do some calculations and explore ideas that go beyond traditional borders,” he concluded.

Source: IE

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