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Data annotation is the process of labeling or tagging data (such as images, text, audio, or video) so that machine learning models can learn from it. It helps AI systems understand and recognize patterns by providing clear examples of what different data elements represent.
App and AI testing involves using applications or AI systems and providing structured feedback on their performance, usability, and accuracy. This includes identifying bugs, evaluating responses, and reporting issues to help improve the overall quality and reliability of the system.