As long as Apple and Google put reasonable AI capabilities on device, then software engineers will use those capabilities when it makes sense (the article gives lots of good examples of capabilities that make sense to run locally). As the author notes, it's cheaper and more reliable to run these things locally.

That also doesn't preclude LLM services from being massively successful, they'll just have to justify the pricing and complexity that comes with their adoption, just like any other product.

> ...it also directly opposes the idea that LLMs are going to replace entire workers rather than enhance the abilities of individual workers.

Which also, as I feel the need to remind everyone every time it comes up, has not yet once been actually shown to be a workable strategy. For any worker in any industry.

And to be clear, I'm talking about a worker, sitting in a chair, replaced with an agent, sitting in... a server, I guess, where nothing else about the org has to be changed. That's what's being advertised and sold, and it has never to my knowledge actually happened.

mainframe industry vs personal computers.

If their product is "access to a big model running on a really big computer" (if we can count 'multiple data-centers' as a single enormous distributed computer), then the product "small, accessible device that everyone has" risks killing their cash cow.

Ironically enough, the first company to really focus on "an LLM in every phone" will have a good shot at actually being the ones that "changed everythingTM", in the way Microsoft changed the world from IBM mainframes to PCs, or Apple made smartphones a thing.