Booth 21-25 | AI Data Management Zone | Tokyo Big Sight
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
Most improvements to AI systems happen before deployment: better training data, better fine-tuning, better RLHF. Once the model is out in the world, you generally get the performance you trained for and nothing better. A paper from early 2026 takes a different approach. Instead of trying to bake everything into
