On the Origin of Circuits

In a unique laboratory in Sussex, England, a computer carefully scrutinized every member of large and diverse set of candidates. Each was evaluated dispassionately, and assigned a numeric score according to a strict set of criteria. This machine's task was to single out the best possible pairings from the group, then force the selected couples to mate so that it might extract the resulting offspring and repeat the process with the following generation. As predicted, with each breeding cycle the offspring evolved slightly, nudging the population incrementally closer to the computer's pre-programmed definition of the perfect individual.

The candidates in question were not the stuff of blood, guts, and chromosomes that are normally associated with evolution, rather they were clumps of ones and zeros residing within a specialized computer chip. As these primitive bodies of data bumped together in their silicon logic cells, Adrian Thompson– the machine's master– observed with curiosity and enthusiasm.

Dr. Adrian Thompson is a researcher operating from the Department of Informatics at the University of Sussex, and his experimentation in the mid-1990s represented some of science's first practical attempts to penetrate the virgin domain of hardware evolution. The concept is roughly analogous to Charles Darwin's elegant principle of natural selection, which describes how individuals with the most advantageous traits are more likely to survive and reproduce. This process tends to preserve favorable characteristics by passing them to the survivors' descendants, while simultaneously suppressing the spread of less-useful traits.

Dr. Thompson dabbled with computer circuits in order to determine whether survival-of-the-fittest principles might provide hints for improved microchip designs. As a test bed, he procured a special type of chip called a Field-Programmable Gate Array (FPGA) whose internal logic can be completely rewritten as opposed to the fixed design of normal chips. This flexibility results in a circuit whose operation is hot and slow compared to conventional counterparts, but it allows a single chip to become a modem, a voice-recognition unit, an audio processor, or just about any other computer component. All one must do is load the appropriate configuration.

The informatics researcher began his experiment by selecting a straightforward task for the chip to complete: he decided that it must reliably differentiate between two particular audio tones. A traditional sound processor with its hundreds of thousands of pre-programmed logic blocks would have no trouble filling such a request, but Thompson wanted to ensure that his hardware evolved a novel solution. To that end, he employed a chip only ten cells wide and ten cells across– a mere 100 logic gates. He also strayed from convention by omitting the system clock, thereby stripping the chip of its ability to synchronize its digital resources in the traditional way.

He cooked up a batch of primordial data-soup by generating fifty random blobs of ones and zeros. One by one his computer loaded these digital genomes into the FPGA chip, played the two distinct audio tones, and rated each genome's fitness according to how closely its output satisfied pre-set criteria. Unsurprisingly, none of the initial randomized configuration programs came anywhere close. Even the top performers were so profoundly inadequate that the computer had to choose its favorites based on tiny nuances. The genetic algorithm eliminated the worst of the bunch, and the best were allowed to mingle their virtual DNA by swapping fragments of source code with their partners. Occasional mutations were introduced into the fruit of their digital loins when the control program randomly changed a one or a zero here and there.

For the first hundred generations or so,


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