We have seen how evolution, when manipulating a real physical electronic medium, can exploit it with orders of magnitude more efficiency than conventional design. This is possible because evolution can utilise the emergent behaviour of a collection of components without having to be able to predict or analyse it: the simplifying constraints of traditional methods can be removed, releasing the full capabilities of the physical hardware.
Evolvable hardware provides the first opportunity for the evolution of synthetic physical `nervous systems.' The components of a physical system -- whether it be biological or electronic -- have a size, shape, and location, and these are important. Robustness cannot be taken for granted. These issues need to be faced in order to reap the full engineering benefits of unconstrained hardware evolution: the potentially small, low-power, fault-tolerant circuits produced have obvious applications in Evolutionary Robotics and elsewhere. Unconstrained direct hardware evolution may thus also be a useful route to greater realism in ER models aiming to address questions in biology or wishing to take inspiration from it.