There is no distributed execution of a single LLM across multiple GPUs using tensor parallelism here. Instead, it relies on task-level parallelism-breaking down a large workload into independent subtasks that run across separate machines. For example, generating embeddings for a million documents.

Maybe their chip team is already on the work, or already made, a server chip for AI purposes used internally, and doesn't have to talk about it yet.

Swift's main reason to go open source and have good Linux support was naturally for app developers to be able to use it on server side, which naturally wasn't going to be macOS.

I macOS wasn't required for developing iDevices apps, they would surely sell even less desktops.