I think it’s because getting to a point where your error bound is that small with nature is incredibly difficult. GANs are a breakthrough but there are still lo

I think it’s because getting to a point where your error bound is that small with nature is incredibly difficult. GANs are a breakthrough but there are still lots of drawbacks and “tells” that allow you to identify a fake distribution. I actually don’t think we’ll get there for a really long time, and for all we know it might actually be impossible to replicate a natural distribution without gathering some untenable amount of data. Even if you gather that amount of data you often have no idea how correct your model actually is because you don’t have access to the natural distribution. You have to have a prior and picking that prior is a research area in and of itself. That’s why people say that. Your premise is really hard. EDIT: just thought of something else, for videos and pictures increasing the resolution dramatically will make it harder to generate deep fakes, it might be interesting to see how much better cameras get and I’m sure that the amount of compute to fake a higher resolution image will be drastically higher. There are a lot of factors at play.