A customer service company is exploring ways to improve its AI-powered chatbot, seeking to balance automation with human input to ensure high-quality responses. The company is considering two approaches: Reinforcement Learning from Human Feedback (RLHF) and Amazon Augmented AI (A2I). However, the company needs to understand the primary differences between these two approaches, as it will help the company choose the right approach to enhance the chatbot's accuracy and reliability. What would you recommend to the company?