Emergent Behavior

Capabilities or behaviors that appear in an AI model that were not explicitly trained for and were not predicted in advance, typically arising as a result of scale. The concept draws on complexity theory: quantitative changes produce qualitative shifts. In large language models, abilities like multi-step reasoning have appeared abruptly at certain scales, performing near-randomly in smaller models before jumping sharply above random in larger ones. Whether this constitutes genuine emergence or an artifact of how performance is measured remains actively debated.
See also: scaling law, large language model, Phase Transition.