Booth 21-25 | AI Data Management Zone | Tokyo Big Sight
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
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 made this feel almost like a law of physics — just add more and the model gets better. That era
