Synthetic data requires a discriminator that can select the highest quality results to feed back into training. Training a discriminator is easier than a full blown LLM, but it still suffers from a lack of high quality training data in the case of 1M context windows. How do you train a discriminator to select good 2,000 page synthetic books if the only ones you have to train it with are Proust and concatenated Harry Potter/Game of Thrones/etc.