Booth 21-25 | AI Data Management Zone | Tokyo Big Sight
Here’s a problem that doesn’t always make it into model deployment conversations: AI models degrade over time, even when you don’t touch them. Not because the model changes. Because the
Before you reach for RLHF, before you design a reward model, before you start thinking about reinforcement learning from verifiable rewards — there’s a more fundamental question worth asking: has this model been properly fine-tuned on examples of the behavior you want? Supervised Fine-Tuning (SFT) sits between pre-training and the
