I haven't read this whole thread in detail, but the matlab/octave thing has also been something of a concern of mine since I will probably be doing a master's in machine learning next year. However, I was just planning to spend a few weeks writing a embedded domain specific language wrapper in Haskell for matlab/octave. Maybe that's harder than I'd imagined it would be - but the problem with writing a Haskell matrix library from scratch is that not only do you lose a lot of the functionality which has already been implemented in these programs, but you also lose all the work which has gone into tuning them for speed. They support a wide variety of optimized internal matrix representations which are transparent to the user, special fast linear algebra operations on those matrices, etc. And for the kind of applications that people use matlab and octave for, speed and scalability tend to be important. So an arrangement where you keep the optimized matlab kernel as a backend and just send it commands would seem to be preferable. Plus, with an EDSL you could improve the type system, index matrices over arbitrary Enum-like types (which are translated to and from integers), graft rudimentary tensor support into Octave, etc. Maybe there would also be uses for a native Haskell matrix library but my intuition is that something like what I described above would be more useful to more people. Am I wrong? Frederik -- http://ofb.net/~frederik/