Rewon Child
Also known as 石井興元
Rewon Child is a researcher whose work spans sparse transformers, generative pretraining, and few-shot language models. At Yale he applied computational methods and natural language processing to politics and government. He then applied deep learning to medical imaging at Enlitic and worked on speech recognition at Baidu Research. At OpenAI he helped develop the Sparse Transformer, and he coauthored Language Models are Few-Shot Learners, which NeurIPS named an Outstanding Paper in 2020. He was on Inflection AI's founding team from 2022 to 2024, and he now works at Microsoft AI.
Timeline
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2013
Computational politics at Yale
He is in Yale's class of 2013, where he focuses on computational methods and natural language processing for politics and government.
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2015–2017
Deep learning at Enlitic and Baidu
From 2015 to 2016 he applies deep learning to medical imaging at Enlitic. From 2016 to 2017 he works as a researcher on speech recognition at Baidu Research.
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2019
The Sparse Transformer at OpenAI
At OpenAI he develops the Sparse Transformer with collaborators, and the paper is submitted to arXiv in April 2019.
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2020
A NeurIPS Outstanding Paper
Language Models are Few-Shot Learners, which he coauthors, wins an Outstanding Paper award at NeurIPS in 2020.
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2020
An ICML honorable mention
Generative Pretraining From Pixels, with his coauthors, receives an Outstanding Paper Honorable Mention at ICML 2020.
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2021–2022
Large-model research at Google
From 2021 to 2022 he does research on large models at Google Brain and Search. He is one of the authors of PaLM: Scaling Language Modeling with Pathways.
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2022–2024
Inflection AI's founding team
He works on the founding team at Inflection AI from 2022 to 2024.
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Since 2024
Working at Microsoft AI
He works at Microsoft AI, the division that Microsoft forms when it hires the Inflection founding team.
Sources and credits
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- Speaker Lunch: A conversation on artificial intelligence (AI), machine learning, and building start-ups | Yale School of Management
- Rewon Child
- [1904.10509] Generating Long Sequences with Sparse Transformers
- [2005.14165] Language Models are Few-Shot Learners
- NeurIPS 2020 Awards
- ICML 2020 Awards
- [2204.02311] PaLM: Scaling Language Modeling with Pathways