Optimistic answer: each sub-network can specialize in a certain skill or element of knowledge, and then as a group, the networks can contribute to a larger deci

Optimistic answer: each sub-network can specialize in a certain skill or element of knowledge, and then as a group, the networks can contribute to a larger decision. Such specialization allows skills to be highly developed but used only when they are applicable, instead of trying to force-fit a certain skill onto an inappropriate problem domain. The human brain is believed to work in a similar way with multiple regions processing input in parallel and "voting" for the appropriate response, with other parts of the brain coalescing and merging their output into the final response. Cynical answer: Neural net machine learning has reached its peak, and there's far more computing power than the researchers know what to do with. Add additional layers of processing and if the numbers change, that's a paper.