LOL, you can get 5x - 10x computational power (including AI if needed) for the same price from other vendors.
Unless they overshot production and have stock of unsold M2s they're willing to sell at 90% discount.
Unless they overshot production and have stock of unsold M2s they're willing to sell at 90% discount.
I expect it's about control and Apple's philosophy that they have to do everything themselves.
Your comment doesn't make much sense to me.
If you're releasing a bunch of new ML-powered features that are setup to run on-device, you have to have a cutoff for what generation of device is required. Apple has indicated with recent OpenELM model releases that they're targeting different levels of device capability. But you can only go so far.
For older devices, you can offload those tasks to the cloud, but then you have to maintain 2 different software stacks and there are potential compatibility issues.
If you have a bunch of M2Us in the cloud though, you have the exact same hardware that you're developing on-device for. If you package up the core software components as frameworks, you can run on device or in the cloud, and it MAYBE simplifies keeping the results and output in sync between the two.
Otherwise, it makes no sense from a pure performance perspective vs. just deploying racks of H100s...