The kinds of things being discussed here (compute heavy algorithms) are typically already accelerated by using high performance native libraries. Think BLAS or OpenCL or CUDA and the Python bindings in Numpy etc.
FPGAs aren't usually going to be much use in business-logic heavy algorithms (which of course are often written in interpreted languages). The performance limits of these are usually set by IO, and in some circumstances FPGAs may help with parts of that (eg, the aforementioned database indexing).
Realistically, increasing use of the new M.2 interface with fast SSDs will make more real-life difference though.
you can do that today going from ruby/js to c