There has been some effort to quantify "AI scaling laws": ie how much performance increases as we scale up the resources involved. See section 1.2 of https://arxiv.org/pdf/2001.08361.pdf

My main takeaway from that paper is that a 2x increase in training cost improves performance by 5% (100x by 42%). I only skimmed the paper though.

To me this says that model scaling will not get us very much farther: we can probably do one more 100x but not two.

I talked to someone working on model scaling and they see the same numbers and draw a very different conclusion: my interpretation of their argument is that they view scaling money as easy versus finding new fundamental technical advances.