{"data":{"slug":"scaling-laws-paper","etype":"paper","name":"Scaling Laws for Neural Language Models (2020)","cat":"Scaling","subtitle":"Kaplan et al.: loss falls as a power law in compute — the investment thesis, quantified.","summary":"This OpenAI paper measured smooth power-law relationships between model performance and parameters, data and compute — the curves that turned 'bigger is better' from folklore into planning tool, and ultimately into capex justification for everything on this site.","attrs":null,"kf":null,"aliases":["Kaplan scaling laws"],"ticker":null,"exchange":null,"hq":null,"founded":null,"website":null,"status":null,"region":null,"asof":"2026-01-15","sources":[{"url":"https://arxiv.org/abs/2001.08361","label":"arXiv 2001.08361"}]},"meta":{"found":true,"count":1,"served_from":"site cache (no live upstream calls)","as_of":"2026-10-14T06:07:16+00:00","disclaimer":"Research and information only — not investment advice. Structured records carry basis labels (vendor spec / reported / estimate); market quotes are delayed/indicative.","attribution":"Records compiled from vendor documentation, official filings and reputable public reporting; market quotes via financial data providers. See /data-sources."}}