To ensure high-confidence responses during live chat, what combination of settings might a customer experience team adjust in their generative AI model?

Enabling safety settings and configuring top-p sampling is a strategic approach to enhance the reliability and appropriateness of responses generated by a generative AI model during live chat interactions.

Safety settings are vital as they help ensure that the model avoids generating harmful or inappropriate content, which is particularly important in customer-facing applications where user trust is paramount. By configuring top-p sampling, also known as nucleus sampling, the model can choose from a more controlled set of probable responses. This method allows the model to focus on a subset of all possible outputs that carry a high cumulative probability, effectively guiding it toward higher-quality and more relevant responses.

Together, these adjustments create a balance between creativity and safety, ensuring that the AI model provides confident, accurate, and contextually appropriate responses in real time. This combination ultimately fosters a better user experience and enhances the overall efficiency of the customer experience team.

While other options like adjusting frequency penalties or utilizing fallback responses may have their merits, they do not inherently offer the same level of confidence and relevance as the chosen combination of safety settings and top-p sampling.