Why do bigger neural networks do things better?

Before we go to think about what the large neural system can mean. We should determine what a neural network can mean?

The neural network can be physical or it can be virtual. The virtual neural network can be a group of databases that involves some actions.

A large neural network can mean three things. And all of them can make something for the system.

1) A large number of servers can make neural networks powerful. Human brains are a good example of how effective neural networks can be if there are hundreds of billions of data handling units. In human brains, neurons are the data-handling tools.

In some futuristic visions, a nano-size microprocessor can be put at the layer of neurons. And then that system can interact with neurons. Nanotechnology can make it possible to make hybrid systems where organic brains are interconnected with nanotechnical computers. The computer can get the orders from the EEG of those neurons.

2) Large area where the network can collect data can make it effective. That kind of system can use to collect data from radio- and optical telescopes.

And machine learning makes it possible to search exoplanets from other solar systems. But the similar systems can use to observe satellites and give warnings about missile strikes and other kinds of things.

3) Large physical and geological areas where the servers are located provide effective protection against electricity distribution errors and nuclear attacks. Neural networks in large areas are the penultimate thing that determines the neural networks of a large area.

4) The final thing that might determine large neural networks is the skills. A large database number can use as the determinator for a large neural network. The problem with large neural networks is how to determine neural networks?

Neural networks are not necessarily learning systems. They might be systems that can collect data from sensors. And if some parameters are filled they can select an action from the library. The learning AI can observe the brightness of some stars and if there are changes the system can report possible planets around that star.

The fact is that the larger neural networks have a bigger data handling capacity than smaller neural networks. There are more data handling units in larger neural networks. And a large number of data handling units allow large data handling capacity.

The thing is the large geological area of the physical neural network. Allows those systems can collect data from a larger area. If the neural network operates in a large geological area that minimizes the effect of errors in the power supply.

Also, the large geological area is used in the missile warning networks. The missile warning systems are collecting data from large areas. And they are operating in large areas. That structure eliminates the effect of things like EMP pulses and nuclear strikes against the network and application servers.

https://www.quantamagazine.org/computer-scientists-prove-why-bigger-neural-networks-do-better-20220210/

Image) https://www.quantamagazine.org/computer-scientists-prove-why-bigger-neural-networks-do-better-20220210/

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