ai-practitioner video for a company developing AI-powered customer service chatbots is exploring ways to improve the quality and accuracy of responses using
A company developing AI-powered customer service chatbots is exploring ways to improve the quality and accuracy of responses using Reinforcement Learning from Human Feedback (RLHF). The data science team is considering using Amazon SageMaker Ground Truth to assist with gathering and processing human feedback during model training. To ensure this solution aligns with their needs, they want to understand how SageMaker Ground Truth supports the key capabilities required for implementing RLHF, such as collecting, labeling, and managing human input effectively. What do you suggest?