Gemini's Over-Reliance on Analogies Raises Concerns About User Experience and Customization

The user's experience highlights a potential flaw in Gemini's output generation, where the model persistently uses analogies despite explicit instructions to avoid them. This suggests a weakness in the model's ability to adhere to user-defined constraints and raises questions about the effectiveness of customization features. The issue could stem from a prioritization of certain training data or a fundamental limitation in the model's architecture.

• •Gemini 3.0 Pro exhibits a tendency to use analogies even when instructed not to.
• •Users are experiencing difficulty in customizing Gemini's output to avoid unwanted content types.
• •The issue is present across different Gemini interfaces, including AI Studio and AG.