Estimating cognitive evolution’s complexity boundary in humans

As touched upon earlier genetic evolution is complexity bound. To be exact to about 25 megabytes because roughly speaking, genetic evolution isn’t going to support more than 10^8 meaningful bases with 1 bit of selection pressure and a 10^-8 error rate.

Reflecting on this complexity boundary in genetic evolution I was wondering what cognitive evolution’s complexity boundary might be in humans. As basis I will assume that:

1) cognitive evolution in humans is taking place on the level of beliefs (a brief summary can be found in my paper on friendly AI theory)

2) beliefs are stored in the neural structure of the brain

3) the informational complexity of the neural structure of the brain that stores beliefs is equal to cognitive evolution’s complexity boundary in humans

Being a friend of Google I quickly came across this interesting estimate of the informational storage capacity of the human brain:

“The human brain contains about 50 billion to 200 billion neurons (nobody knows how many for sure), each of which interfaces with 1,000 to 100,000 other neurons through 100 trillion (10 14) to 10 quadrillion (10 16) synaptic junctions. Each synapse possesses a variable firing threshold which is reduced as the neuron is repeatedly activated. If we assume that the firing threshold at each synapse can assume 256 distinguishable levels, and if we suppose that there are 20,000 shared synapses per neuron (10,000 per neuron), then the total information storage capacity of the synapses in the cortex would be of the order of 500 to 1,000 terabytes.”

Staying on the safe side I will assume that this estimate is off by two orders of magnitude and that only one percent of the human brain is actually involved in storing beliefs. As a result I estimate that human cognitive evolution on the level of beliefs is bound by a complexity of no less than 100 gigabytes or at least 4’096 times higher than that of genetic evolution.

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