Machine Learning algorithms can exhibit a form of "amnesia"—called catastrophic forgetting—where they rapidly lose previously learned information upon learning new data. This challenges the notion that AI always builds upon past knowledge. Techniques like "elastic weight consolidation" help mitigate this by protecting important learned weights. Have you encountered other unique ML quirks or behaviors? Please share your insights or experiences!