Slime Mold

Physarum polycephalum challenges categories. Individual cells function independently, foraging through soil. When resources deplete, cells aggregate into a multicellular slug—a coordinated entity that moves toward light to find better conditions. The slug can navigate mazes, find shortest paths between food sources, and even recreate efficient network designs like Tokyo's rail system. No cell contains the solution; solutions emerge from collective behavior.

The transition from individual to collective is reversible. When the slug finds favorable conditions, it differentiates into fruiting body and spores—returning to individual cells that disperse and start the cycle again. The organism shifts between individual and collective modes based on environmental conditions. Individuality when resources are abundant and dispersal beneficial; collectivity when resources are scarce and coordination valuable.

Slime mold decision-making has been extensively studied. The organism demonstrates memory (avoiding previously explored areas), learning (improving maze navigation over trials), and optimization (finding efficient network configurations). These capabilities emerge from simple cell behaviors aggregated across millions of units. The business parallel reveals that distributed intelligence can solve problems no individual unit understands. Slime molds don't know they're solving problems; they follow simple rules that produce intelligent-seeming behavior. Organizations can achieve similar emergent intelligence—market efficiency from individual trades, scientific progress from individual research, innovation ecosystems from individual experiments. The question is designing interaction rules that aggregate individual behavior into collective intelligence.