How much more exposition do you want from a casual blog post? There's a link to the academic paper if you want full details (you can follow up on the numerous references to other papers, which explain applications.)
The academic paper is confusing, because it defines the problem as it would have been a singular event, the sender chooses a real number, then sends 1 bit to the receiver and the receiver miraculously guesses the real number.
You have to waste time by carefully studying the paper to see that the statistical methods used are meaningless for a singular event, so in fact a large number of transmissions of a single bit are assumed and the accuracy (i.e. the variance) of the estimation of the real number is computed over that very large but unspecified number of transmitted bits.
In any real application, the main quality of an estimation algorithm would be determined by how many single bits must be transmitted and received to guarantee a certain accuracy (variance) of the estimation, i.e. a certain number of recovered bits of the real number, but I have lost patience when reading the paper before discovering whether the authors even mention this somewhere.
What should be clear for everyone, is that recovering N bits of a real number, i.e. reducing the variance of the estimation to that level, always requires transmitting many more single bits than N.
Nevertheless, even if more bits are sent, there are many cases when this is useful, e.g. because losing some single bits or receiving them with errors has little effect, but there may also be other reasons.