I (dumb) thought anaconda would automatically choose the proper version for the type of chip, turns out I have been using the intel-based python all this time instead of the native version.
/Users/x/opt/anaconda3/envs/ml/bin/python: Mach-O 64-bit executable x86_64
It should say:
... Mach-O 64-bit executable arm64
Now, it is normal to use the intel based version if not already updated to native silicon? I guess I’m just missing out on M1 performance?
From my understanding, the only way to download the native Python 3.9X versions is through homebrew / miniforge: TLDR. Is it worth updating, especially considering I’m starting to use TensorFlow, etc. for ML? Also, what happens to all my current envs and packages I have in (the current, intel based ) anaconda if I switch to Miniforge? Do they all translate, or what happens to the packages not optimised for arm64?
Or is the performance not life changing at all and I should save myself headaches and keep using TensorFlow 2.0.0 on the intel-based anaconda / python 3.6?