In the early stages of a seed AI, such improvements might occur mainly through trial and error, information acquisition, or assistance from the programmers. At its later stages, however, a seed AI should be able to understand its own workings sufficiently to engineer new algorithms and computational structures to bootstrap its cognitive performance. This needed understanding could result from the seed AI reaching a sufficient level of general intelligence across many domains, or from crossing some threshold in a particularly relevant domain such as computer science or mathematics.
