Emergent abilities are behaviors or properties of ML models that "emerge" unpredictably, specially as models grow in size/capacity. These abilities are said to emerge because they are somewhat unrelated to the original task the models were designed for. For example: large language models trained to predict the next token in a sequence of tokens have shown various emergent abilities in the context of few-shot prompting (when a few input-output samples are given and the model is asked to generate the output to a previously unseen input).