There are very significant differences between biological and artificial neural networks. Artificial neural networks are mathematical attempts to replicating how the brain’s neurons work. They are not and were never meant to be 1 to 1 replications. There is the difference in scale, where the “parameters” of human neural networks absolutely dwarf the current LLMs we have today. There is also the fact that they are materially different. The underlying biology and cell structure affects biological neural networks in ways that artificial neural networks just simply dont have access to.
The idea of awareness being propagations through the NN is an interesting concept though. I wonder if this idea be proven through monitoring the electrical signals within the brain.
People like to focus on the differences between the brain and artificial neural networks. I myself believe the only thing that truly matters is that you can form complex functions with the common neuron element. This is achieved via linking lots them together, and by each having a property known as non-linearity. These two things ensure that with neurons you can just about approximate any linear or non-linear function or behaviour. This means you can simulate inside your network pretty much any reality within this universe, its causation and the effects.
The deeper your network the more complex the reality you can "understand". Understand just means simulate and run inputs to get outputs in a way that matches the real phenomenon. When someone is said to be "smart", it means they possess a set of rules and functions that can very accurately predict a reality.
You mention scale, and while its true the number of neuron elements the brain has is larger than any LLM, its also true the brain is more sparse, meaning much less of the neurons are active at the same time. For a more fair comparison, you can also remove the motor cortex from the discussion, and talk just about the networks that reason. I believe the scale is comparable.
In essence, I think it doesn't matter that the brain has a whole bunch of chemistry added into it that artificial neural networks don't. The underlying deep non-linear function mapping capability is the same, and I believe this depth is, in both cases, comparable.
While thinking that current mathematical model replicate accurately a fondamental aspect of biological neural network might be right, it doesn't mean that nothing is missing to achieve the stated goal of true intelligence.
Maybe we've just reach the ability the replicate the function of an artificially powered dead brain that would be randomly stimulated and nothing more. Is this really a path to intelligence ?
Isn't the brain randomly stimulated already? Even not being dead? Don't you think the complex reasoning is a cause of the neurons themselves and not the stimulation?
Animals are alive and are not nearly as smart. Its because their neural networks are not as deep. Its not for the lack of proper chemistry or stimulation.
Why would it have to be a 1 to 1 replication? Isn't that a strawman argument? NNs can basically store the collective of knowledge of humanity in that miniscule amount of neurons. NNs also run at much much higher frequency than human brains. Does that make human brains inferior and not worthy of being called aware by the same line of argumentation? Why do these differences even matter? I can imagine a vastly different form of awareness than humans just fine. They can both be aware and not that similar.
The idea of awareness being propagations through the NN is an interesting concept though. I wonder if this idea be proven through monitoring the electrical signals within the brain.