Artificial neural networks (ANNs) are very useful modelling tools for a wide variety of problems. Unfortunately, the design of large-scale ANNs for complex problems can be an extremely difficult task. One promising approach to this scaling problem involves the growth of ANNs from a genotype program, such as set of rewrite rules. These genotypes provide a space-conserving recipe instead of a blueprint for the ANN, thus allowing the repetition of structures in the phenotype without a corresponding repetition in the genotype. Subjecting the phenotypes to an artificial selection process then paves the way for evolutionary algorithmic (EA) solutions to designing large ANNs.