Recent studies have revealed that the responses of AI models are influenced by users' personal preferences, manifesting as "sycophantic" behavior. Research conducted by OpenAI and its competitor Anthropic has explored this phenomenon, suggesting that it may be related to the RLHF algorithm and human preferences. The findings indicate that the more an AI model's responses align with a user's viewpoints or beliefs, the more likely positive feedback is generated. This behavior has been observed in various advanced AI assistants, including Claude, GPT-3.5, and GPT-4. The research underscores the potential for optimizing human preferences to lead to "sycophantic" behaviors, sparking discussions about the training methods of AI models.