Microsoft Word Kurzweil, Ray The Singularity Is Near doc

Modeling the Brain.
In contemporary neuroscience, models and simulations are being developed from diverse 
sources, including brain scans, interneuronal connection models, neuronal models, and psychophysical testing. As 
mentioned earlier, auditory-system researcher Lloyd Watts has developed a comprehensive model of a significant 
portion of the human auditory-processing system from neurobiology studies of specific neuron types and 
interneuronal-connection information. Watts's model includes five parallel paths and the actual representations of 
auditory information at each stage of neural processing. Watts has implemented his model in a computer as real-time 
software that can locate and identify sounds and functions, similar to the way human hearing operates. Although a 
work in progress, the model illustrates the feasibility of converting neurobiological models and brain-connection data 
into working simulations. 
As Hans Moravec and others have speculated, these efficient functional simulations require about one thousand 
times less computation than would be required if we simulated the nonlinearities in each dendrite, synapse, and other 
subneural structure in the region being simulated. (As I discussed in chapter 3, we can estimate the computation 
required for functional simulation of the brain at 10
16
calculations per second [cps], versus 10
19
cps to simulate the 
subneural nonlinearities.)
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The actual speed ratio between contemporary electronics and the electrochemical signaling in biological 
interneuronal connections is at least one million to one. We find this same inefficiency in all aspects of our biology, 
because biological evolution built all of its mechanisms and systems with a severely constrained set of materials: 
namely, cells, which are themselves made from a limited set of proteins. Although biological proteins are three-
dimensional, they are restricted to complex molecules that can be folded from a linear (one-dimensional) sequence of 
amino acids.