> One big downside is that is has a margin of error which is very often unacceptable. You should look at the paper they mention The Case for Learned Index Stru

> One big downside is that is has a margin of error which is very often unacceptable. You should look at the paper they mention The Case for Learned Index Structures[0]. It covers B-Tree-Index and how to use Hybrid Indexes to bound the errors so that "bad" answers from the model perform no worse than the standard data structure. For a lighter read this paper was also covered by Adrian Colyer in an issue of the morning paper[1]. [0] https://arxiv.org/abs/1712.01208 https://arxiv.org/abs/1712.01208 [1] https://blog.acolyer.org/2018/01/08/the-case-for-learned-index-structures-part-i/ https://blog.acolyer.org/2018/01/08/the-case-for-learned-ind... [edit: formatting]