The study of evolution has entered a revolutionary new era, where quantitative and predictive methods are transforming the traditionally qualitative and retrospective approaches of the past. Genomic sequencing and modern computational techniques are permitting quantitative comparisons between variation in the natural world and predictions rooted in neo-Darwinian theory, revealing the shortcomings of current evolutionary theory, particularly with regard to large-scale phenomena like macroevolution. Current research spanning and uniting diverse fields and exploring the physical and chemical nature of organisms across temporal, spatial, and organizational scales is replacing the model of evolution as a passive filter selecting for random changes at the nucleotide level with a paradigm in which evolution is a dynamic process both constrained and driven by the informational architecture of organisms across scales, from DNA and chromatin regulation to interactions within and between species and the environment.