> We trained a generative model on CIFAR-10, which we then used to generate ~6 million images. The scale of the dataset was chosen to ensure that it is “virtually infinite” from the model’s perspective, so that the model never resamples the same data.
I don't think so, Tim. They observe identical performance between cifar-10 and cifar-5m, because the generative model for cifar-5m learned to replicate the distribution that cifar-10 was sampled from. It's the same dataset.
I don't think so, Tim. They observe identical performance between cifar-10 and cifar-5m, because the generative model for cifar-5m learned to replicate the distribution that cifar-10 was sampled from. It's the same dataset.