Tag: AI Anomalies

AI Anomalies refer to unexpected or unusual behaviors exhibited by artificial intelligence systems that deviate from normal operation or expected outcomes. These anomalies can arise during the development, training, or deployment of AI models and may manifest as errors, biases, or unforeseen decision-making patterns. Identifying and understanding AI anomalies is crucial for ensuring the reliability, safety, and ethical considerations of AI systems. By analyzing these anomalies, developers and researchers can improve models, rectify potential issues, and enhance the overall performance and accountability of AI technologies.