The post is just full of half-baked conjectures masquerading as facts... combined with "things they read" by unspecified authors and sources... the author seems to prefer engaging in AI doomerism as opposing to actually understanding.
> Diseconomies of Scale. Every new technology I can think of thrived, in part, due to economies of scale, where the larger the industry grew, the more efficient it got. AI is going in the opposite direction, where every new AI model consumes more resources than its predecessors. This may turn out to be the fatal flaw – the bigger the industry gets, the more its operating costs increase.
[Agreed] Newer gens of models are more power-efficient per task, not less.
It's possible that the demands on the model are growing faster than it gets efficient though. A lot of the improvement in output quality/metrics come from more churning and passes.
You could argue that a RTX5090 needs less power than a 1996 3Dfx Voodoo 1 to render GLQuake at 320x200/60fps, but it's rarely being used for that.
> Diseconomies of Scale. Every new technology I can think of thrived, in part, due to economies of scale, where the larger the industry grew, the more efficient it got. AI is going in the opposite direction, where every new AI model consumes more resources than its predecessors. This may turn out to be the fatal flaw – the bigger the industry gets, the more its operating costs increase.
[Agreed] Newer gens of models are more power-efficient per task, not less.
This is a low quality post full of basic errors.