General Artificial Intelligence is a term used to describe the kind of artificial intelligence we are expecting to be human like in intelligence. We cannot even come up with a perfect definition for intelligence, yet we are already on our way to build several of them.
To put it up in regular terms, you could communicate to that system like you do with a person and the system would interact with you like a person. The problem is people have limited knowledge or memory. Sometimes we cannot remember some names. We know that we know the name of the other guy, but we just cannot get it on time. We will remember it somehow, but later at some other instance. This is not called parallel computing in the coding world, but it is something similar to that. Our brain function is not fully understood but our neuron functions are mostly understood. This is equivalent to say that we don’t understand computers but we understand transistors; because transistors are the building blocks of all computer memory and function.
When a human can parallel process information, we call it memory. While talking about something, we remember something else. We say “by the way, I forgot to tell you” and then we continue on a different subject. Now imagine the power of computing system. They never forget something at all. This is the most important part. As much as their processing capacity grows, the better their information processing would be. We are not like that. It seems that the human brain has a limited capacity for processing; in average.
The rest of the brain is information storage. Some people have traded off the skills to be the other way around. You might have met people that are very bad with remembering something but are very good at doing math just with their head. These people have actually allocated parts of their brain that is regularly allocated for memory into processing. This enables them to process better, but they lose the memory part.
Human brain has an average size and therefore there is a limited amount of neurons. It is estimated that there are around 100 billion neurons in an average human brain. That is at minimum 100 billion connections. I will get to maximum number of connections at a later point on this article. So, if we wanted to have approximately 100 billion connections with transistors, we will need something like 33.333 billion transistors. That is because each transistor can contribute to 3 connections.
Now you can understand how complicated the actual human neuron should be. The problem is we haven’t been able to build an artificial neuron at a hardware level. We have built transistors and then have incorporated software to manage them. Neither a transistor nor an artificial neuron could manage itself; but an actual neuron can. So the computing capacity of a biological brain starts at the neuron level but the artificial intelligence starts at much higher levels after at least several thousand basic units or transistors.
The advantageous side for the artificial intelligence is that it is not limited within a skull where it has a space limitation. If you figured out how to connect 100 trillion neurosynaptic cores and had big enough facilities, then you can build a supercomputer with that. You can’t do that with your brain; your brain is limited to the number of neurons. According to Moore’s law, computers will at some point take over the limited connections that a human brain has. That is the critical point of time when the information singularity will be reached and computers become essentially more intelligent than humans. This is the general thought on it. I think it is wrong and I will explain why I think so.