NLP & Language · advanced · concept 145 of 311 · Updated Nov 4, 2026
LLM Scaling Laws
The empirical finding that LLM performance improves predictably with more data, compute, and parameters. Chinchilla scaling laws (2022) showed that most models were undertrained relative to their size.
Top AI contributors on this
- Dario AmodeiAnthropic
- Sam AltmanOpenAI
- Jeff DeanDiscovery Loop
- Noam ShazeerOpenAI
- Alec RadfordIndependent / Thinking Machines Lab (adviser)
- Oriol VinyalsDiscovery Loop
Key terms
ChinchillaCompute-optimalEmergent abilitiesPower law
Learn these first
Videos
▶ Lec 20. Scaling Laws ↗
MIT OpenCourseWare · YouTube
▶ Stanford CS336 Language Modeling from Scratch | Spring 2026 | Lecture 9: Scaling Laws ↗
Stanford Online · YouTube
Guides and articles
The Scaling Hypothesis ↗
Gwern Branwen
2026-06-24-scaling-laws ↗
Lil'Log (OpenAI researcher)
Courses, papers, and more
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