Do AI researchers train models using scaling laws?

Scaling laws have been proposed as ways to gather information about how to train large machine learning models efficiently (Kaplan et al., 2020), and this has been done in practice for training LLMs like Chinchilla (Hoffmann et al., 2022). But how broadly have scaling laws been used by AI researchers in general, and has there been a delay in the uptake of such an approach?