One of the greatest challenges in the real estate market is identifying who will likely list their home for sale in the near future. Listings are sporadic events often separated by several years of inactivity. Therefore, any method or algorithm that could reliably predict these events has the potential to generate immense value. For this reason, GIANT AI has recently concluded a series of test analyses of real estate activity. The purpose of these tests was to determine whether new analytic technologies could identify subtle predictive elements among the thousands of data elements related to any given dwelling unit.

The technology used to explore this massive volume of data is artificial swarm intelligence, an analog of the natural collective intelligence observed in flocks of birds, schools of fish, swarms of bees, etc. In artificial swarm intelligence, thousands of intelligent agents simultaneously search a data landscape for patterns and communicate their findings to each other. When applied to predictive analytics, the swarm of intelligent agents subdivides a problem into homogeneous segments, creates a solution for each segment, and finally reunites the solutions into an ultimate equation that is greater than the sum of its parts.