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Given the expected limit to Moore’s law and the evidence of such an event becoming apparent, many companies and entrepreneurs have invested in abstract supplements for the possibly ending market of modern day computers. This specific idea replicates the unfortunate adversity of the human brain’s communication design. The reasoning the professor uses is that efficiency (as in power) is more important than accuracy (amount of misfires). This is because accuracy can be ameliorated using advanced algorithms, although possibly not to the point of modern day computers which err less than once every trillion times, while the heat is a limiting factor given the amount of energy needed for these momentous computers to achieve such high accuracy.

Replicated around the fashion in which the human brain functions, this microprocessor made from silicon atoms and would be (hypothetically given estimations prevail) far smaller than an equally powerful modern day computer due to its simplicity and being unbounded by manufactured transistors which take up far more space. The transistors require enormous amounts of energy (relative to the radical opposite) to maintain this incredibly high accuracy (remember < 1 - 1,000,000,000,000), neurons have evolved over millions of years and have chosen an incredibly low power consumption rate, however as a consequence many neurons can sporadically and lead to often mistakes (3-9 - 10). The reliability of each is directly related to the amount of power consumption. Ideally, a transistor will only open or close when it is needed, and a neuron will only fire when it is told. The transistor malfunction is likely caused by manufacturing defects in addition to conditioning, but the all more prevalent malfunction of a neuron is due to the accidental release of a protein.