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Two people I know bought M1 Macs to get into ML. I do think many confuse training performance with model execution performance.

I currently use a 2080tioc and wish for something faster to not wait for runs that long as they take you out of the zone.

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Google colab is a much better tool than a new computer for getting into ML. It's free, requires no dependency management, easy to share, and has tons of example notebooks you can reproduce as easily as duplicating a google doc.

Not to mention a Linux based workstation in the limit will have fewer headaches than mac these days. Package management doesn't require homebrew or dockerized everything, selinux is surprisingly easier to configure than the Mac security subsystems, etc.

I don’t know. As someone who recently built a Linux workstation but whose computing is generally done on a Mac, I had all sorts of trouble with surprising things. Like my mouse stopped working one day ... no idea what happened, tried googling, tried asking, but nothing I did fixed it. Ended up just reinstalling the OS.

Having had a similar experience, my new strategy is to set up a server and just ssh in to do ML development. That way I don't have to worry about mouse/display/wifi drivers.

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