ML-based indexing ("The Case for Learned Index Structures", a paper from Google)

Very interesting read: https://arxiv.org/abs/1712.01208

HN discussion: https://news.ycombinator.com/item?id=15894896

Some of the comments (from Twitter
https://twitter.com/schrockn/status/940037656494317568): "Jeff Dean and co
at GOOG just released a paper showing how machine-learned indexes can
replace B-Trees, Hash Indexes, and Bloom Filters. Execute 3x faster than
B-Trees, 10-100x less space. Executes on GPU, which are getting faster
unlike CPU. Amazing."

Can those ideas be applied to Postgres in its current state? Or it's not
really down-to-earth?