SM2 has less parameters, but there is not a systematic way to tweak them correctly. With the optimizer, it's easy to make FSRS adaptive to any learners. There is only one lever for user to tweak in FSRS: the desired retention.
Math Academy provided a self-service learning system with a novel spaced repetition algorithm which could take the hierarchical body of math into account.
Yes, we can improve FSRS in that way. But it requires to collect a lot of review data with cards' content, which breaks Anki's privacy policy. And FSRS is my side project which has squeezed all my free time... I'm not very motivated to improve it now.
You don't need to beat FSRS with 700 millions of reviews. You can collect thousands of reviews for months and compare the ad-hoc algorithm with FSRS on those reviews.