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
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 world does. This is concept drift — when the relationship between the inputs a model was trained on and the
