Deep Learning Scaling is Predictable, Empirically

This is a seminal research paper (Hestness et al., 2017) that helped establish the field of scaling laws. While it was a breakthrough at the time, as an open-source project, it functions as a static reference implementation. Frontier labs like OpenAI and Anthropic have since developed significantly more advanced and proprietary scaling laws (e.g., Kaplan et al., Chinchilla), making this specific implementation obsolete for production use but historically critical.