Genetic Algorithms, "are a way of solving problems by mimicking the same processes mother nature uses. They use the same combination of selection, recombination and mutation to evolve a solution to a problem." They've often been used in software but have largely not been applied to hardware. Enter Dr. Adrian Thompson and some 100 cell FPGAs. He created an experiment where a computer would analyze the evolution of an FPGA configuration over time until it could reliably differentiate between two tones (and later two voice commands). After nearly 4000 evolutions, Dr. Thompson's creation demonstrated a peculiar quirk of the process - unexplainable hardware nuances themselves became part of the design. For instance, the final candidate included some logical loops that were never actually part of the circuit - but removing them results in the chip's failure. More so, putting the same configuration onto another chip resulted in failure. The algorithm literally adapted to magnetic flux, a "gray area" between transistor ON/OFF states, and other performance quirks of its native FPGA host in order to fulfill its task.