I am saying as long as two brains have the same structures, the g factor varies in the production part, instead of the learning part. By learning I mean possib

I am saying as long as two brains have the same structures, the g factor varies in the production part, instead of the learning part. By learning I mean possible learning. The connections between each brain are different and how you store the information and link it to other memories are different between humans, but you can teach any human Calculus if you can find the right method to teach them. The same for teaching any human language. Only if their brain was neurodegenerated, those structures don't exist properly. Where it gets interesting is when the structures are different. You could still teach GPT-6 Calculus, and it could reason it. But how it learned Calculus required massive training data, to be able to understand language and then the Calculus text. With humans, we need little training data because the rest of the brain does the reasoning part and language part. So, AGI does not need to replicate the human brain or the structures within it, but an AGI will need to become more efficient at calculations. So, eventually, GPT-9 could reason language with a much smaller dataset, because it has a similar reasoning portion of its code like how our brain has a specific region to process language. Instead of data, it has been optimized in its code structure itself. So it needs only less data to do the same computation. To put it simply: No. You do not need to replicate the structures that exist in the human brain. But, yes, the AGI will have structures that are segmented to process those same inputs and outputs a brain region also does. An AGI will have an optimized language structure, and optimized optical structure, an optimized reasoning structure, and as much sub structures as it needs. It won't look like our brain, but it won't look like a mess either. Otherwise, we would be using more compute than necessary or possible in the near future to create something that could be done with less compute.