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Lilian Weng explains scaling laws and compute-optimal allocation
What happened
Lilian Weng shares a long-overdue (3+ years?) post on scaling laws. Compute is expensive. Scaling laws help reason about optimal compute allocation between data and model size before committing to a large run. The post covers what scaling laws predict, how compute-optimal allocation works, why Kaplan et al. and Chinchilla disagree, and how data limits and fitting details make extrapolation tricky. https://lilianweng.github.io/posts/2026-06-24-scaling-laws/
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