By Austin Garrido
A biosphere composed on conscious, perceiving nodes mirrors the interactions of their respective components, non-trivially the components which give rise to consciousness in the highly complex and quantum neural architecture, resulting in a encompassing intelligence composed of any physical object interacting with the nodes.
In the basic design of the class “neural networks”, nodes of summation are connected to one another through weighted “synapses”, that dictates the amount of influence a given signal has on the next neuron. Information is encoded in spike trains that encode information about the source, duration, and kind of stimuli activating the neuron. In the biological brain, this is principally encoded by a method of a timing interval spike, as this is the most compact and concise way to give all the necessary information to the neurons using with an otherwise binary system of communication. The product of internal processing can and will be expressed externally, providing phenomenal input to other biological brains in othr, separate organisms.
Human language evolved as a way for us to communicate thoughts and concepts to one another. Thoughts and feelings are merely the result of the percolation of neuronal interaction of phenomenal stimulation- indeed, a mind with no stimulation will be exceedingly entropic. [1]
Human brains are equipped with censor information, choosing not to display and communicate certain thoughts and feelings to other organisms. This mirrors the threshold function that discriminates what information is sent along the axon in biological neural systems. Obviously, with a much more complicated system of conveying information, almost every aspect of a biological neuron is expanded and more complex, and increasingly subjected to entropy. The most important thing, however, is that every characteristic of a neural system is mirrored by biological organisms that interact with one another- in essence, any collection of dynamically processing beasts that can share information with one another assumes the form of a neural network, an therefore, intelligence on a massive scale.
Synapses are mirrored by human interactions. In the biological brain, a given neuron is principally connected to nearby neurons, but may also share information with neurons a much greater distance away. Given that human beings evolved from a tribal society, they have developed a number called “Dunbar’s Number”, and is the supposed cognitive limit to the number of individuals with whom any one person can maintain stable social relationships. This number is believed to be about 148, and is estimated to be the size of the largest hunter-gatherer societies. With the advent of the telephone and radio, humans began to enter the final stages of super-inclusive neural simulation. When networks such as the internet gave individuals the ability to convey specific information to other individuals, or groups of individuals, our biosphere completed the last necessary step in complexity to mirror it’s component parts, and emerge as a conscious system. An individual human being interacts principally with nearby humans with whom he/she has relationships with, but may also occasionally share information with somebody of considerable distance away, just as a neuron in a neural network would to its peers- if necessary, forming strong relationships with nodes that are physically distant.
One difference between a neural network as found in the human brain and a massive universal intelligence is the nature of input vs. output. In the human brain, there is some, trivial, level of input and output. Given a stimulus, the brain stores the stimulus as a some sort of memory, either sensory, short-term, or long-term.[2] The stimulus may then be discarded almost entirely, as happens to most of the information that enters out mind, with the neural effects still percolating introspectively. Effectively, the output of the “top” layer of neurons is fed back into the “bottom” causing the information to be to reprocessed, and reclassified.[3] In fact, to a neural structure, there is no difference between classifying new information from an external source and processing information that has already been partially classified. It is important to remember that this is the basic nature of a global intelligence; as an intelligent system grows larger and its basic constituent parts grow more complex and constitute a greater percentage of it’s own environment, the amount of closed-loop thinking is increased, and thus, the amount of classification is increased.
On an imaginary time line of humanity, with (for the sake of argument) definite points of discoveries about the world, one can easily see this closed-loop thinking in effect. Say at point “A” on this simplified timeline is the beginning of humanity. The entire world is one large chunk of information, with no distinguishing subclasses. Then, say at point “B”, humans discover something edible, the first input of information. News of this eventually passes through all nearby members of his specie. Now, humans have discovered the world is divided into at least two parts, “edible” and “non-edible.” This is reprocessed by the global intelligence, and at point “C”, man discovers that some edible items taste better and are more nutritious than others. Now, man’s world is divided into at least three groups: “good edible”, “bad edible”, and “non-edible.”
All of the data needed to classify the world up to the complexity we see today is in contained within the system, which included not only the humans, but the very foods and objects they were gathering information about. Unlike neurons, which are not complex enough to examine their own environment, humans possess the differentiation of language necessary to gather information about their environment. Having closed-loop processing occurring constantly throughout the earth’s biosphere’s existence has given us all of the technology and infrastructure we have today, through the reclassification and manipulation of old data about the earth.
[1] Some believe that through complex “emergence”, our own thought processes can be altered by will, or some quantum effect. It is fully within the full scope of this paper to encompass this, as any unknown processes that lead to consciousness would be encompassed in the super-inclusive consciousness (including possible linguistic or quantum effects. A super-inclusive system must be at least as entropic as it’s component parts, and in practice, usually much more so.)
[2] The appropriate analogue of this on the proposed global intelligence is the development of written language and the keeping of long-term records. They are an more permanent extensions of the neural network of their creators, who in turn had been affected by all previous physical neural stimulation.
[3] It similar to studying a cryptographer studying a complex cipher for a long enough period of time, until a pattern emerges and the cipher is solved. Even though no new information is given, the cryptographer has reprocessed the cipher long enough to classify it into “encoded” and “solved” (and all intermediary stages).
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