And the Apple Silicon chips even include specialized cores that allow LLMs to run locally on both iPhones and MacBooks. (See the "Foundation Models Framework".)
Which was a day late and a dollar short, even at release. Those ANEs are only really good at inference, and even then you get faster results using your Apple Silicon GPU. They're slow, incomplete, not integrated into the GPU architecture (like Nvidia's) therefore killing any chance of Apple Silicon seeing serious AI server usage.
If you want to brag about Apple's AI hardware prowess, talk about MLX. The ANE was a pretty obvious mistake compared to Nvidia's approach and hundreds of businesses had their own, even before Apple made theirs.
The cores and architecture was designed for smartphones, it got put in desktops and rackmount servers anyways. I can judge it for whatever the product is, it's not a untold mystery why Apple Silicon servers aren't flying off the shelves in the AI boom.
If you want to brag about Apple's AI hardware prowess, talk about MLX. The ANE was a pretty obvious mistake compared to Nvidia's approach and hundreds of businesses had their own, even before Apple made theirs.