Maybe community-owned datacenters will, who knows.

I kinda agree with his points that:

Currently, using local models on average consumer hardware is not really feasible. The math of building your own powerful lab to run these models just doesn’t work out no matter what way you look at it… just look at PC component prices, factor in the electricity and so on…

People will generally go for the new shiny, powerful thing (that’s what drives our economic system, after all).

Data center inference will always be more efficient.

I would also add that people are not tech savvy enough and or lazy to go through the hassle of setting up a local model.

So I do think running a model locally will continue being a niche unless some serious advances will be made in them.

It’s important to note that even though running a local model might not make sense today, that doesn’t mean we have to be stuck with large, proprietary USA models. Through something like Cortecs you can use small, open-weight models like GPT 20B, Gemma 4 26B, Qwen 9B and so on … They’re dirt cheap, some providers have environmentally clean data centers, strict privacy policy, etc.

Guy working at github (microsoft) doing ai stuff is telling you to just use the cloud because it is soooo cheap and the cloud provider will definitively NOT stab you in the back with price increases