1: that could be something for the future, but at the moment this is just meant as a way to quickly try out and evaluate various algorithms and libraries without having to learn the syntax for them (we call those backends).
2: we adopted the same methodology as ann-benchmarks for our evaluation, so technically the benchmarks there are valid for the backends we support. However it's a good suggestion to add those explicitly to the repo, I'll add a todo for that.
3: mainly because a: it's the language we are most the comfortable with developing in, b: it's the most widely used and adopted language for ML and c: (almost) all the algorithms we support are written in C/C++/Cython already.
2: we adopted the same methodology as ann-benchmarks for our evaluation, so technically the benchmarks there are valid for the backends we support. However it's a good suggestion to add those explicitly to the repo, I'll add a todo for that.
3: mainly because a: it's the language we are most the comfortable with developing in, b: it's the most widely used and adopted language for ML and c: (almost) all the algorithms we support are written in C/C++/Cython already.