alt Hacker NewsAnd while we’re at it, let’s move away from Python altogether. In the long run it doesn’t make sense just because it’s the language ML engineers are familiar with.
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It makes plenty of sense. Python handles strings well, has a great package ecosystem, and is easy to write/learn for non-programmers. It can be easily embedded into a notebook (which is huge for academics) and is technically a "write once run anywhere" platform in theory. It's great.
If you think Python is a bad language for AI integrations, try writing one in a compiled language.
Most of that is already happening under the hood. A lot of performance-sensitive code is already written in C or cython. For example numpy, scikit learn, pandas. Lots of torch code is either C or CUDA.
ML researchers aren’t using python because they are dumb. They use it because what takes 8 lines in Java can be done with 2 or 3 (including import json) in python for example.
No! This is not good.
Iteration speed trumps all in research, most of what Python does is launch GPU operations, if you're having slowdowns from Pythonland then you're doing something terribly wrong.
Python is an excellent (and yes, fast!) language for orchestrating and calling ML stuff. If C++ code is needed, call it as a module.