abu_ameena

I think we started going down this slippery-slope since we decided that LLMs are permitted to use human languages.

Yes, but you don’t always want the power/expense of these models for the task at hand. A hammer is good enough to push a nail inside a wall. Save the nail gun for when you are building a house.

I see it as a long-term tradeoff on user freedom. You pay upfront for a capable hardware, you get your services running locally (you don’t pay subscriptions). Or you buy cheap hardware, you still need the same services “running in some cloud” for $X monthly. X goes up depending on the corporate bottom-line

On-device models are the future. Users prefer them. No privacy issues. No dealing with connectivity, tokens, or changes to vendors implementations. I have an app using Foundation Model, and it works great. I only wish I could backport it to pre macOS 26 versions.

If that’s the dystopia we would live in, I’d imagine an alternate healthcare/legal system would emerge. Also, personally I’m far more forgiving of the human-error than that of the machine

If we are talking about jobs (quantity) maybe to some extent. But if want to be honest, it’s qualitative (human-judgment) question. And even if a job seems totally AI-ready on paper, it might have invisible side effects.

(Thought experiment: do I want an AI robot to perform a surgery on me, if it only has 2% chance of hallucinating? My answer is no, bring the surgeon)

Any job where human-judgment is not required and there’s clear rules on the tasks required.