To evaluate generic model is hard. For example, for image synthesis in GAN, the widely used Inception score balances between authenticity of the generate sampl

To evaluate generic model is hard. For example, for image synthesis in GAN, the widely used Inception score balances between authenticity of the generate samples vs the variety as well, to make sure the model is not copy-pasting. In this particular case, apparently the same event has been reported multiple times by different news agency. Even if the exact one are excluded, still it is suspicious how much less the model is being protected from knowing the subject itself. An analogy would exam in real world. Often, some of the questions aren't leaked as is, but paraphrased yet stay close enough to the source. In this particular case though, I disagree it is reaching human level generation. They can tested the model with an unseen events, which happen after the model is trained to test how well it generalize.