4 sources
A useful anchor for understanding the practical scaling-law and GPT-3 era, especially the people who turned broad intuition about scale into concrete training decisions.
Start HereScaling laws for neural language models
Researcher Profile
Editor reviewedTom Brown
Large-scale language modeling
Co-author, Training Data Extraction
One of the clearest researchers to study for the GPT-3 era, especially around few-shot learning, scaling behavior, and what larger language models started making possible in practice.
Organizations
OpenAI
Labs
Topics
About This Page
This profile is meant to help you get oriented quickly: why this researcher matters, what to read first, and where to explore next.
Last reviewed
March 18, 2026
Known For
The ideas, systems, and research directions that make this person worth knowing.
01
GPT-3 era language models
02
Few-shot learning in large models
03
Scaling-law intuition for large language models
04
Large-scale language modeling
05
Language Models are Few-Shot Learners (GPT-3)
06
OpenAI
Start Here
Canonical papers, project pages, or repositories that anchor this profile.
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Co-authored GPT-3: Language Models are Few-Shot Learners.
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Co-authored GPT-3: Language Models are Few-Shot Learners.
1 source
Co-authored GPT-3: Language Models are Few-Shot Learners.
1 source
Co-authored GPT-3: Language Models are Few-Shot Learners.
1 source
Co-authored GPT-3: Language Models are Few-Shot Learners.