AWS Certified AI Practitioner Practice Exam

What is the simplest solution for modifying a generative AI model's response style based on user age?

1. Fine-tune the model with representative training data for different age ranges

2. Add a role description to the prompt context indicating user age

3. Use chain-of-thought reasoning for appropriate response style

4. Summarize response texts based on user age

The correct answer is: Add a role description to the prompt context indicating user age

The most straightforward approach for modifying a generative AI model's response style based on user age is to add a role description to the prompt context that indicates the user's age. This method leverages the model's existing framework without the need for extensive alterations or retraining. By explicitly stating the user's age in the prompt, the model can adapt its responses to be more suitable for the specified age group, whether that involves simplifying language for younger audiences or incorporating more complex ideas for older users. This method is efficient because it requires minimal changes to the model itself and allows for immediate adjustments in response style depending on the context provided in the prompt. It harnesses the model's capacity to interpret context effectively, making it quick to implement compared to retraining with new data. In contrast, fine-tuning the model with representative training data for different age ranges involves significant effort in collecting, processing, and re-training the model, which may not be necessary for simpler style modifications. Chain-of-thought reasoning, while beneficial in generating complex answers, does not directly address the prompt's requirement for specific age-based response styles. Summarizing response texts based on user age can alter content but does not inherently modify the communication style to suit different age groups as effectively as providing a role