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Most AI today is generally some form of machine learning / deep learning. When it comes to deep learning, python is by far the most popular language (libraries

Most AI today is generally some form of machine learning / deep learning. When it comes to deep learning, python is by far the most popular language (libraries like PyTorch and tensorflow have a thriving ecosystem)

DontchaKnowit 4y ago
Always wondered why this was the case : python is painfully slow and machine learning benefits greatly from speed.
- pizza 4y ago
  The Python ecosystem imo tries to get you from 0 to 1 a bit faster than the more performant alternatives with large userbases I’m really thinking of the C/C++ ecosystem here - os portability, compiler differences, cmake, xeus-cling vs ipython, etc. Interestingly it seems nowadays the trend is to siphon the good parts of the faster languages into Python (xla/numba/tvm) for cheap, rather than making it easier to get the good parts of Python into the faster languages (although certainly eg pybind11 is nice in that regard).
- rsfern 4y ago
  It’s nice and flexible to work with, and for large models all the heavy lifting is calling out to CUDA and C++. often the overhead of the python interpreter is completely negligible
dusted 4y ago
it's my understanding that python is more used as a user interface to the actual AI programs, which are mostly written in some GPU-friendly language, so Python is more for menial work that can be slow because it's just doing minor tranformations to data that's being passed to and from the actual programs.. But yeah, python is painfully slow, write a naive "count the lines in a textfile" program in C and Python, you're in for a bad time waiting for python to finish.. even with small files of 100 gigabytes..
- jstx1 4y ago
  No, Python is much more than an interface - the model architercture and definition happens in Python. If you're writing an ML algorithm, you're writing it in Python, it's just that the lower level operations are implemented in something like C++.

DontchaKnowit 4y ago

Always wondered why this was the case : python is painfully slow and machine learning benefits greatly from speed.

pizza 4y ago
The Python ecosystem imo tries to get you from 0 to 1 a bit faster than the more performant alternatives with large userbases I’m really thinking of the C/C++ ecosystem here - os portability, compiler differences, cmake, xeus-cling vs ipython, etc. Interestingly it seems nowadays the trend is to siphon the good parts of the faster languages into Python (xla/numba/tvm) for cheap, rather than making it easier to get the good parts of Python into the faster languages (although certainly eg pybind11 is nice in that regard).
rsfern 4y ago
It’s nice and flexible to work with, and for large models all the heavy lifting is calling out to CUDA and C++. often the overhead of the python interpreter is completely negligible

dusted 4y ago

it's my understanding that python is more used as a user interface to the actual AI programs, which are mostly written in some GPU-friendly language, so Python is more for menial work that can be slow because it's just doing minor tranformations to data that's being passed to and from the actual programs.. But yeah, python is painfully slow, write a naive "count the lines in a textfile" program in C and Python, you're in for a bad time waiting for python to finish.. even with small files of 100 gigabytes..

jstx1 4y ago
No, Python is much more than an interface - the model architercture and definition happens in Python. If you're writing an ML algorithm, you're writing it in Python, it's just that the lower level operations are implemented in something like C++.