Universe works like a cosmological neural network, argues new paper

Controversial physics theory says reality around us behaves like a computer neural network.

Universe works like a cosmological neural network, argues new paper

Synapses in space.

Credit: sakkmesterke
  • Physicist proposes that the universe behaves like an artificial neural network.
  • The scientist's new paper seeks to reconcile classical physics and quantum mechanics.
  • The theory claims that natural selection produces both atoms and "observers".

Does the reality around us work like a neural network, a Matrix-like computer system that operates similar to a human brain? A new physics paper argues that looking at the universe that way can provide the elusive "theory of everything".

This controversial proposal is the brainchild of the University of Minnesota Duluth physics professor Vitaly Vanchurin. In an interview with Futurism, Vanchurin conceded that "the idea is definitely crazy, but if it is crazy enough to be true?"

The scientist developed the theory while exploring the workings of machine learning using statistical mechanics. He found that mechanisms involved in the computer learning were similar in some instances to the dynamics of quantum mechanics.

A computer neural network works via nodes, which mimic biological neurons, processing and passing on signals. As the network learns new information, it changes, giving certain nodes more priority, allowing it to connect bits of information in such a way that next time in will know, for example, what are they key traits of a "zebra".

"We are not just saying that the artificial neural networks can be useful for analyzing physical systems or for discovering physical laws, we are saying that this is how the world around us actually works," writes Vanchurin in the paper. "With this respect it could be considered as a proposal for the theory of everything, and as such it should be easy to prove it wrong."

How do you prove his theory wrong? Vanchurin proposes a way. All you have to do is "find a phenomenon which cannot be modeled with a neural network." That, of course, isn't actually so easy to pull off, as Vanchurin himself points out. We don't fully understand how neural network and machine learning work and need to grasp those processes first.

Vanchurin interview:

Vanchurin thinks his idea can accomplish another purpose that has been the goal of modern physics – to reconcile classical physics, which describes how the universe works on a large scale, and quantum mechanics, the study of the atomic and subatomic level of existence. The physicist thinks that if you view the universe as working essentially as a neural network, its behavior under certain conditions can be explained by both the quirky equations of quantum mechanics and the laws of classical physics like the theory of general relativity devised by Albert Einstein.

"The learning dynamics of a neural network can indeed exhibit approximate behaviors described by both quantum mechanics and general relativity," writes Vanchurin in his study.

Diving deeper into his theory, Vanchurin thinks it supports such apparent mechanisms of our world as natural selection. He suggests that in a neural network, particles and atoms, but even us, the "observers" would emerge from a natural-selection-like process. On the microscopic level of the network, some structures would become more stable while some would be less so. The stable ones would survive the evolutionary process, while the less stable ones would not.

'On the smallest scales I expect that the natural selection should produce some very low complexity structures such as chains of neurons, but on larger scales the structures would be more complicated," he shared with Futurism.

He sees little reason why this kind of process would only work on just the small scale, writing in the paper:

"If correct, then what we now call atoms and particles might actually be the outcomes of a long evolution starting from some very low complexity structures and what we now call macroscopic observers and biological cells might be the outcome of an even longer evolution."

While he posits the neural network explanation, Vanchurin doesn't necessarily mean we all live in a computer simulation, like proposed by philosopher Nick Bostrom, adding the caveat that even if we did, "we might never know the difference."

Vanchurin's idea has so far been received with skepticism by other physicists but he is undeterred. You can check out his paper for yourself on ArXiv.

Vanchurin on “Hidden Phenomena”:

Vitaly Vanchurin speaking at the 6th International FQXi Conference, "Mind Matters: Intelligence and Agency in the Physical World." The Foundational Questions...

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CRISPR therapy cures first genetic disorder inside the body

It marks a breakthrough in using gene editing to treat diseases.

Credit: National Cancer Institute via Unsplash
Technology & Innovation

This article was originally published by our sister site, Freethink.

For the first time, researchers appear to have effectively treated a genetic disorder by directly injecting a CRISPR therapy into patients' bloodstreams — overcoming one of the biggest hurdles to curing diseases with the gene editing technology.

The therapy appears to be astonishingly effective, editing nearly every cell in the liver to stop a disease-causing mutation.

The challenge: CRISPR gives us the ability to correct genetic mutations, and given that such mutations are responsible for more than 6,000 human diseases, the tech has the potential to dramatically improve human health.

One way to use CRISPR to treat diseases is to remove affected cells from a patient, edit out the mutation in the lab, and place the cells back in the body to replicate — that's how one team functionally cured people with the blood disorder sickle cell anemia, editing and then infusing bone marrow cells.

Bone marrow is a special case, though, and many mutations cause disease in organs that are harder to fix.

Another option is to insert the CRISPR system itself into the body so that it can make edits directly in the affected organs (that's only been attempted once, in an ongoing study in which people had a CRISPR therapy injected into their eyes to treat a rare vision disorder).

Injecting a CRISPR therapy right into the bloodstream has been a problem, though, because the therapy has to find the right cells to edit. An inherited mutation will be in the DNA of every cell of your body, but if it only causes disease in the liver, you don't want your therapy being used up in the pancreas or kidneys.

A new CRISPR therapy: Now, researchers from Intellia Therapeutics and Regeneron Pharmaceuticals have demonstrated for the first time that a CRISPR therapy delivered into the bloodstream can travel to desired tissues to make edits.

We can overcome one of the biggest challenges with applying CRISPR clinically.

—JENNIFER DOUDNA

"This is a major milestone for patients," Jennifer Doudna, co-developer of CRISPR, who wasn't involved in the trial, told NPR.

"While these are early data, they show us that we can overcome one of the biggest challenges with applying CRISPR clinically so far, which is being able to deliver it systemically and get it to the right place," she continued.

What they did: During a phase 1 clinical trial, Intellia researchers injected a CRISPR therapy dubbed NTLA-2001 into the bloodstreams of six people with a rare, potentially fatal genetic disorder called transthyretin amyloidosis.

The livers of people with transthyretin amyloidosis produce a destructive protein, and the CRISPR therapy was designed to target the gene that makes the protein and halt its production. After just one injection of NTLA-2001, the three patients given a higher dose saw their levels of the protein drop by 80% to 96%.

A better option: The CRISPR therapy produced only mild adverse effects and did lower the protein levels, but we don't know yet if the effect will be permanent. It'll also be a few months before we know if the therapy can alleviate the symptoms of transthyretin amyloidosis.

This is a wonderful day for the future of gene-editing as a medicine.

—FYODOR URNOV

If everything goes as hoped, though, NTLA-2001 could one day offer a better treatment option for transthyretin amyloidosis than a currently approved medication, patisiran, which only reduces toxic protein levels by 81% and must be injected regularly.

Looking ahead: Even more exciting than NTLA-2001's potential impact on transthyretin amyloidosis, though, is the knowledge that we may be able to use CRISPR injections to treat other genetic disorders that are difficult to target directly, such as heart or brain diseases.

"This is a wonderful day for the future of gene-editing as a medicine," Fyodor Urnov, a UC Berkeley professor of genetics, who wasn't involved in the trial, told NPR. "We as a species are watching this remarkable new show called: our gene-edited future."

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