[sumnuyungi]

This is just patently false. Most of the folks I know that have an M1 are students that were saving up to upgrade from a much older computer and got the M1 Air. I can assure you that they don't have a decent amount of money.

Tensorflow has a branch that's optimized for metal with impressive performance. [1] It's fast enough to do transfer learning quickly on a large resnet, which is a common use-case for photo/video editing apps that have ML-powered workflows. It's best for everyone to do this locally: maintains privacy for the user and eliminates cloud costs for the developer.

Also, not everyone has an imagenet sized dataset. A lot of applied ML uses small networks where prototyping is doable on a local machine.

[1] https://blog.tensorflow.org/2020/11/accelerating-tensorflow-...