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These occur when an AI model generates erroneous or misleading outputs, posing credibility issues for companies relying on AI for content generation, decision-making, or other critical functions. To mitigate these risks, continuous improvements in AI model architectures and robust testing mechanisms are crucial. Copyright issues further compound the difficulties faced by the generative AI market. As these AI models are trained on large datasets that may include copyrighted material, there's a constant battle over ownership and rights. Content creators and copyright holders are expressing apprehension about their works being used without consent, raising ethical and legal questions that the industry must tackle to avoid potential litigation and conflicts.
