This assumes that current neural networks topologies can "solve" intelligence. "Gains" could be a problem of missing subsystems, rather than missing data. For

This assumes that current neural networks topologies can "solve" intelligence. "Gains" could be a problem of missing subsystems, rather than missing data. For a squishy example of a known conscious system, if you scoop out certain small, relatively fixed, regions of our brains, you can make consciousness, memory, and learning mostly cease. This suggests it's partly due to special subsystems, rather than total connection count.