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Answer :
Generative AI models face challenges in maintaining consistency due to unpredictability, bias, and difficulty in interpreting training feedback.
One of the key challenges faced by generative AI models in terms of consistency is ensuring reliable performance across different contexts and applications. AI models, especially those using complex algorithms, often struggle with unpredictability and bias, leading to inconsistent results in diverse environments. According to research like Maity (2019), interpreting training feedback, linking it to performance, and standardizing processes in the face of a diverse user base add to the complexity of maintaining consistency. Moreover, as AI systems become more sophisticated, their goals may diverge from human intentions, posing further challenges for consistency and alignment with desired objectives.
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