Booth 21-25 | AI Data Management Zone | Tokyo Big Sight
For most of the last six years, the most capable LLMs were locked behind APIs. You could call them, you could build on them, but you couldn’t look inside, customize
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
