How would you reduce hallucinations in a customer-facing AI assistant?

Focus on identifying specific strategies to minimize inaccuracies in AI responses, known as hallucinations. Discuss the importance of improving the training data quality and ensuring it is diverse and representative of real-world scenarios. Consider the implementation of feedback loops where users can report inaccuracies, and how this data can be used to refine the model. Additionally, explore the role of transparency in AI responses, such as providing confidence scores or disclaimers when the assistant is uncertain. Finally, think about user experience implications and how to maintain trust while addressing these challenges.