AI scaling laws
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Publication dates and source age
Sources counted: 2
Newest dated source: 2022-03-29
Assessed at this edition's evidence cutoff: 2026-09-15. 18-month boundary: 2025-03-15.
Publication age does not tell us whether a claim is still valid. Reading an old source again does not make its publication date newer. An update date does not establish that the passage we used was updated.
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In plain language
Measured patterns linking model size, training data and computing resources to performance. Each pattern concerns a particular measurement and training setup. [1] [2]
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Limits & distinctions
Larger is not the only choice. Hoffmann and coauthors found better results by balancing model size with more training data. Extrapolating a measured trend to untested scales adds an assumption. [1] [2]
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A fuller explanation
Researchers train different-sized models and fit equations to the results. In language-model research, a common measure is prediction loss: how poorly the model predicts the next text piece. [1] [2]
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How it relates to the map
Map context: these studies inform expectations about capability growth and resource use. [1] [2]
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Sources and what we read
1. Scaling Laws for Neural Language Models
Source is over 18 months old.
Publication dates and source age
Sources counted: 1
Newest dated source: 2020-01-23
Assessed at this edition's evidence cutoff: 2026-09-15. 18-month boundary: 2025-03-15.
Publication age does not tell us whether a claim is still valid. Reading an old source again does not make its publication date newer. An update date does not establish that the passage we used was updated.
Read abstract and submission record. Empirical relationships concern language-model prediction loss and training resources, not an AGI date.
2. Training Compute-Optimal Large Language Models
Source is over 18 months old.
Publication dates and source age
Sources counted: 1
Newest dated source: 2022-03-29
Assessed at this edition's evidence cutoff: 2026-09-15. 18-month boundary: 2025-03-15.
Publication age does not tell us whether a claim is still valid. Reading an old source again does not make its publication date newer. An update date does not establish that the passage we used was updated.
Read abstract and submission record. Tests balance parameter count and training tokens under a fixed compute budget. Results are scoped to the studied setups.
Edition and machine-readable evidence
Content version 0.20.0. Evidence cutoff 2026-09-15; this does not mean every source was read on that day.
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