Azure AI Foundry has introduced significant enhancements in model fine-tuning with Reinforcement Fine-Tuning (RFT) for the upcoming o4-mini model and Supervised Fine-Tuning (SFT) for the GPT-4.1-nano model. RFT, geared for complex decision-making environments, allows models to adaptively respond to nuanced business logic through feedback mechanisms, enhancing their contextual understanding and reasoning capabilities. This method has already benefitted legal tech startup DraftWise, improving contract generation accuracy by 30%.
Simultaneously, SFT for GPT-4.1-nano enables organizations to align model outputs with specific terminologies and workflows, particularly beneficial for high-volume scenarios like customer support. Additionally, Llama 4 Scout fine-tuning has been made available, offering a robust model infrastructure with advanced customization options. These upgrades reflect Azure AI Foundry’s commitment to providing tools for developing tailored, efficient AI systems that meet diverse organizational needs.
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