What is a key feature of AI models regarding data training?

A key feature of AI models regarding data training is that feedback helps in adapting and improving. This aspect is crucial because it allows AI systems to learn from their experiences and refine their outputs over time. When AI models are trained on existing datasets, they are capable of adjusting their algorithms based on the feedback they receive from their predictions or actions, whether that feedback comes from human evaluation or additional data inputs. This iterative learning process enables the models to become more accurate and effective in their tasks.

In contrast, the other options lack this foundational principle of adaptive learning. The idea that AI models require no prior data is misleading, as all AI systems need some form of initial data to learn from and build their models. Furthermore, stating that they depend solely on manual instructions fails to recognize that many modern AI systems utilize complex algorithms and data-driven insights to guide their operations. Lastly, claiming that AI is limited to algorithmic rules undermines the flexibility and adaptability that these systems can exhibit through learning and improving based on feedback and new data.