The entire discussion in the software section is about simulating the brain.
> Creating superintelligence through imitating the functioning of the human brain requires two more things in addition to appropriate learning rules (and sufficiently powerful hardware): it requires having an adequate initial architecture and providing a rich flux of sensory input.
> The latter prerequisite is easily provided even with present technology. Using video cameras, microphones and tactile sensors, it is possible to ensure a steady flow of real-world information to the artificial neural network. An interactive element could be arranged by connecting the system to robot limbs and a speaker.
> Developing an adequate initial network structure is a more serious problem. It might turn out to be necessary to do a considerable amount of hand-coding in order to get the cortical architecture right. In biological organisms, the brain does not start out at birth as a homogenous tabula rasa; it has an initial structure that is coded genetically. Neuroscience cannot, at its present stage, say exactly what this structure is or how much of it needs to be preserved in a simulation that is eventually to match the cognitive competencies of a human adult. One way for it to be unexpectedly difficult to achieve human-level AI through the neural network approach would be if it turned out that the human brain relies on a colossal amount of genetic hardwiring, so that each cognitive function depends on a unique and hopelessly complicated inborn architecture, acquired over aeons in the evolutionary learning process of our species.