// curated_library

Seminal papers, key talks, and essential videos from the people shaping AI — filtered for signal, not noise.

paper

Scaling Laws for Neural Language Models

Kaplan et al. (OpenAI) — 2020

The empirical laws governing how model performance scales with compute, data, and parameters. The theoretical backbone behind the scaling hypothesis that has driven frontier AI for five years.

scaling laws language models compute empirical ML
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