Neuromorphic computers do not aim to replace conventional computers. They instead wish to supplement them in a way that makes sense. The current computer architectures have a major problem in recognizing patterns and grasping complexity. Neuromorphic computers can sift through vast mountain of data, provided by services like Google, combined with smartphones and cars, looking for patterns and predict a traffic jam before the first car even comes to a halt.
That is a highly complex endeavor in which conventional computer architectures have immense difficulty, because any calculation steps are required. On the other hand, it is an ideal application area for neuromorphic computing, for reservoir computers and for artificial intelligence, because the novel technologies are not only small, but also incredibly energy-efficient, they could work directly on the sensors.
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