“It is important to note that the design of an entire brain region is simpler than the design of a single neuron. As discussed earlier, models often get simpler at a higher level—consider an analogy with a computer. We do need to understand the detailed
physics ofsemiconductors to model a transistor, and the equations underlying a single real transistor are complex. A digital circuit that multiples two numbers requires hundreds of them. Yet we can model this multiplication circuit very simply with one or
two formulas. An entire computer with billions of transistors can be modeled through its instruction set and register description, which can be described on a handful of written pages of text and formulas. The software programs for an operating system,
language compilers, and assemblers are reasonably complex, but modeling a particular program—for example, a speech recognition programbased on hierarchical hidden Markov modeling—may likewise be described in only a few pages of
equations. Nowhere in such a description would be found the details ofsemiconductor physics or even of computer architecture. A similar observation holds true for the brain. A particular neocortical pattern recognizer that detects a particular invariant
visualfeature (such as a face) or that performs a bandpass filtering (restricting input to a specific frequency range) on sound or that evaluates the temporal proximity of two events can be described with far fewer specific details than the actual physics and
chemicalrelations controlling the neurotransmitters, ion channels, and other synaptic and dendritic variables involved in the neural processes. Although all of this complexity needs to be carefully considered before advancing to the next higher conceptual level,
much of it can be simplified as the operating principles of the brain are revealed.”
―
Ray Kurzweil,
How to Create a Mind: The Secret of Human Thought Revealed
