A known limitation of current AI technologies is their reliance on data quality and quantity. AI models require substantial, high-quality datasets for training to perform effectively. If the dataset is biased or lacks diversity, the AI's outputs will reflect these limitations, potentially leading to inaccuracies or ethical concerns. Moreover, AI technologies often struggle in contexts that necessitate complex reasoning, understanding of nuance, or emotional intelligence, showcasing the challenges in replicating human-like cognitive abilities. These limitations pose hurdles in achieving fully autonomous and reliable AI systems.