Just how “Deep” is your Deep Learning?
Most Deep Learning (DL) systems are functionally no more complicated than a child’s collection of legos, or in some cases a marble track, where one piece connects to another that needs to be the right size. Consequently, the actual value these systems offer is bottlenecked by the diversity of perspectives applied to their design. That diversity has a very low glass ceiling because current systems have one big gaping flaw.