Sep 11, 2020 11:25 PM
(This post was last modified: Sep 11, 2020 11:26 PM by C C.)
https://futurism.com/physicist-entire-un...al-network
[excerpts] ... FUTURISM: Your paper argues that the universe might fundamentally be a neural network. How would you explain your reasoning to someone who didn’t know very much about neural networks or physics?
VITALY VANCHURIN: There are two ways to answer your question.
The first way is to start with a precise model of neural networks and then to study the behavior of the network in the limit of a large number of neurons. What I have shown is that equations of quantum mechanics describe pretty well the behavior of the system near equilibrium and equations of classical mechanics describes pretty well how the system further away from the equilibrium. Coincidence? May be, but as far as we know quantum and classical mechanics is exactly how the physical world works.
The second way is to start from physics. We know that quantum mechanics works pretty well on small scales and general relativity works pretty well on large scales, but so far we were not able to reconcile the two theories in a unified framework. This is known as the problem of quantum gravity. Clearly, we are missing something big, but to make matters worse we do not even know how to handle observers. This is known as the measurement problem in context of quantum mechanics and the measure problem in context of cosmology.
Then one might argue that there are not two, but three phenomena that need to be unified: quantum mechanics, general relativity and observers. 99% of physicists would tell you that quantum mechanics is the main one and everything else should somehow emerge from it, but nobody knows exactly how that can be done. In this paper I consider another possibility that a microscopic neural network is the fundamental structure and everything else, i.e. quantum mechanics, general relativity and macroscopic observers, emerges from it. So far things look rather promising.
[...] How does your research relate to quantum mechanics, and does it address the observer effect?
There are two main lines of thought the Everett’s (or many-world’s) interpretation of quantum mechanics and Bohm’s (or hidden variables) interpretation. I have nothing new to say about the many-worlds interpretation, but I think I can contribute something to the hidden variables theories. In the emergent quantum mechanics which I considered, the hidden variables are the states of the individual neurons and the trainable variables (such as bias vector and weight matrix) are quantum variables. Note that the hidden variables can be very non-local and so the Bell’s inequalities are violated. An approximated space-time locality is expected to emerge, but strictly speaking every neuron can be connected to every other neuron and so the system need not be local.
[...] Do you mind expanding on the way this theory relates to natural selection? How does natural selection factor into the evolution of complex structures/biological cells?
What I am saying is very simple. There are structures (or subnetworks) of the microscopic neural network which are more stable and there are other structures which are less stable. The more stable structures would survive the evolution, and the less stable structure would be exterminated. 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. I see no reason why this process should be confined to a particular length scale and so the claim is that everything that we see around us (e.g. particles, atoms, cells, observers, etc.) is the outcome of natural selection... (MORE - details)
[excerpts] ... FUTURISM: Your paper argues that the universe might fundamentally be a neural network. How would you explain your reasoning to someone who didn’t know very much about neural networks or physics?
VITALY VANCHURIN: There are two ways to answer your question.
The first way is to start with a precise model of neural networks and then to study the behavior of the network in the limit of a large number of neurons. What I have shown is that equations of quantum mechanics describe pretty well the behavior of the system near equilibrium and equations of classical mechanics describes pretty well how the system further away from the equilibrium. Coincidence? May be, but as far as we know quantum and classical mechanics is exactly how the physical world works.
The second way is to start from physics. We know that quantum mechanics works pretty well on small scales and general relativity works pretty well on large scales, but so far we were not able to reconcile the two theories in a unified framework. This is known as the problem of quantum gravity. Clearly, we are missing something big, but to make matters worse we do not even know how to handle observers. This is known as the measurement problem in context of quantum mechanics and the measure problem in context of cosmology.
Then one might argue that there are not two, but three phenomena that need to be unified: quantum mechanics, general relativity and observers. 99% of physicists would tell you that quantum mechanics is the main one and everything else should somehow emerge from it, but nobody knows exactly how that can be done. In this paper I consider another possibility that a microscopic neural network is the fundamental structure and everything else, i.e. quantum mechanics, general relativity and macroscopic observers, emerges from it. So far things look rather promising.
[...] How does your research relate to quantum mechanics, and does it address the observer effect?
There are two main lines of thought the Everett’s (or many-world’s) interpretation of quantum mechanics and Bohm’s (or hidden variables) interpretation. I have nothing new to say about the many-worlds interpretation, but I think I can contribute something to the hidden variables theories. In the emergent quantum mechanics which I considered, the hidden variables are the states of the individual neurons and the trainable variables (such as bias vector and weight matrix) are quantum variables. Note that the hidden variables can be very non-local and so the Bell’s inequalities are violated. An approximated space-time locality is expected to emerge, but strictly speaking every neuron can be connected to every other neuron and so the system need not be local.
[...] Do you mind expanding on the way this theory relates to natural selection? How does natural selection factor into the evolution of complex structures/biological cells?
What I am saying is very simple. There are structures (or subnetworks) of the microscopic neural network which are more stable and there are other structures which are less stable. The more stable structures would survive the evolution, and the less stable structure would be exterminated. 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. I see no reason why this process should be confined to a particular length scale and so the claim is that everything that we see around us (e.g. particles, atoms, cells, observers, etc.) is the outcome of natural selection... (MORE - details)
