Booth 21-25 | AI Data Management Zone | Tokyo Big Sight
There was a point, not long ago, when the dominant strategy for improving large language models was simple: feed them more. More tokens, more compute, more parameters. The scaling laws
Most AI text detectors look good in testing. They’re trained and evaluated on specific models, specific prompt styles, specific domains — and they perform well within that distribution. Then they get deployed into the real world, which has different models, different prompting patterns, different domains, and the performance drops. This
