Good article, but I feel that it misses an important property of diffusion models that they model the score function (derivative of log prob) [1] and that diffusion sampling is akin to Langevin dynamics [2]. IMO these explain why it's easier to train these models than GANs, because of an easier modeling objective.
[1] https://yang-song.net/blog/2021/score/
[2] https://lilianweng.github.io/posts/2021-07-11-diffusion-mode...