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Fine-Tuning is Dead, Long Live Reinforcement Fine-Tuning

‘This is not standard fine-tuning... it leverages reinforcement learning algorithms that took us from advanced high school level to expert PhD level’
OpenAI has shattered the boundaries of AI customisation with the debut of reinforcement fine-tuning (RFT) for its o1 models on the second day of its ‘12 Days of OpenAI’ livestream series. This new breakthrough marks the end of traditional fine-tuning as we know it. With RFT, models don’t just replicate—they reason.  By employing reinforcement learning, OpenAI looks to empower organisations to build expert-level AI for complex tasks in law, healthcare, finance, and beyond. This new approach enables organisations to train models using reinforcement learning to handle domain-specific tasks with minimal data, sometimes as few as 12 examples.  By using reference answers to evaluate and refine model outputs, RFT improves reasoning and accuracy in expert-level tasks. OpenA
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Siddharth Jindal
Siddharth is a media graduate who loves to explore tech through journalism and putting forward ideas worth pondering about in the era of artificial intelligence.
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