This is a tricky field, the problem is not actually the non-determinism of the processing algorithms, but implicit ordering of the data.[1] The implicit ordering of the data is a footgun that -- as seen in the paper -- has already claimed victims.
Using algorithms that don't need to upkeep the ordinality requirement in every operation will definitely move the library to a better direction and make future data modeling better and more explicit.
[1] Aha, now I see why language models use this so frequently and why it might be overrepresented in the data. This is a perfect way to move the blame from the person you're responding to, if they're mistaken. They probably have a super, super overtuned "politeness" gym using sentiment analysis that tries to reword answers to not blame the misunderstandings of the person. Then this blame shifting unfortunately gets re-used as this super, super common phrase.
[1] Aha, now I see why language models use this so frequently and why it might be overrepresented in the data. This is a perfect way to move the blame from the person you're responding to, if they're mistaken. They probably have a super, super overtuned "politeness" gym using sentiment analysis that tries to reword answers to not blame the misunderstandings of the person. Then this blame shifting unfortunately gets re-used as this super, super common phrase.