Besides claimed efficiency improvements, posits are claimed to have advantages for implementing numerical algorithms correctly compared to IEEE floats. A big part of Gustafson's book The End of Error is devoted to that, claiming to show that a range of numerical algorithms are implemented better with posits vs IEEE floats (better meaning some mix of clearer, easier to produce stability, better error bounds, etc.). It's something of a competitor to interval arithmetic in that respect [1].

A 'softposit' implementation can at least let people experiment with writing posit algorithms to investigate the claimed algorithm-design benefits, even if it's not going to beat hardware floats in speed.

[1] The interval arithmetic people don't seem very happy with his comparisons though: http://frederic.goualard.net/publications/MR3329180.pdf

Yes, those implementation are slow compared to classical floating points. The goal, as I understand it, is to let people experiment with Posits in order to prove that they bring something to the table.

As far as I read https://posithub.org/docs/Posits4.pdf there are FPGA implementations. Also in systems where floating point arithmetic isn't supported in hardware (i.e. Arduino Uno) you rely on soft fp.