亚马逊Nova的强化微调：通过反馈教会AI

Reinforcement fine-tuning (RFT) is a powerful customization technique for Amazon Nova models that learns through evaluation rather than imitation. The post details how RFT works, when to use it compared to supervised fine-tuning, and real-world applications ranging from code generation to customer service. Implementation options are discussed, including fully managed Amazon Bedrock and multi-turn agentic workflows with Nova Forge. Practical guidance on data preparation, reward function design, and best practices for achieving optimal results is also provided.