alt Hacker News>By my read of the (very sparse) data, we're getting linear improvements in capability for super-linear increases in costs. [1] Indicates that by 2027 models will cost $1 billon to train. Dario estimates that model runs will cost $10 billion in 2026 [2]. That to me indicates costs are potentially growing faster than capability. Maybe by quite a bit.
This is true and well established.
As long as you get any improvement whatsoever, it is worth spending to train since it pays off during.
Imagine training was not $1 billion but $100 billion but the performance improved by just 10%. This is still worth it because you can squeeze out the profits across years and years right? The improvement is ever lasting.
> The best data shows that LLM use might be destroying value [3].
This is basically a conspiracy theory and if you really believed this, you should not have led with "How is the capability advancement vs dollars paid for development?" because if there were no value, it doesn't really matter how much you invest.
>This is basically a conspiracy theory
I think this is pretty uncharitable, especially when I've provided you with a dataset you can evaluate yourself and an argument you can review for logical inconsistency.
I have worked quite hard to locate data that supports your thesis, I can't find it. I've at least gone to the effort of documenting that search. Before you throw around such strong convictions, I suggest you actually look for yourself.