>>12697296The neural net model is clearly wrong from immediate experience with brains.
Neuroscientists by and large do not agree, and many of them believe that neurons strictly do a net computation still, although this opinion is likely changing, because it is obviously false.
The first observation is that the memory capacity of the brain is extraordinarily limited, in both time and memory. For example, if I glance at a street, and I see a car, it takes about 1/10th of a second for the visual processing to complete, and for me to identify the car. In that process, there are only 100 cycles of neural activity possible, in other words, the neurons can only fire 100 times. Each neuron holding a bit, even with the most efficient computation you can imagine, there is absolutely no way that you will identify the car and recall properties of cars, like "driving, there is a wheel, on the road, right side up" and all the innumerable little dormant things, from a trillion bits in 100 steps of a millisecond.
What you can do in this time is produce a unique pattern of firing that serves to uniquely identify the observation of a car, and bin the firing into the appropriate bin. This then can be used by something else to do the rest of the computation in thinking.
This is the problem of too-low computational capacity of neural nets. It cannot be improved by making brains bigger, because it is a problem of depth, not of breadth.
