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Noam Shazeer

Thought Leader

Noam Shazeer is a machine-learning researcher and co-author of 'Attention Is All You Need', the paper that introduced the Transformer. He co-founded Character.AI, returned to Google as a VP of Engineering and co-lead of Gemini, and in June 2026 left Google to join OpenAI.

Last updated Sep 26, 2026 by the ATDb Editorial Team

Company
OpenAI
Based
San Francisco, California, United States
Connections
2
Years in industry
22 years

Bio

Noam Shazeer is a machine-learning researcher and co-author of 'Attention Is All You Need', the paper that introduced the Transformer. He co-founded Character.AI, returned to Google as a VP of Engineering and co-lead of Gemini, and in June 2026 left Google to join OpenAI.

Career

  • Co-founder & CEO

    Character.AI · 2021-2024

  • Senior Research Scientist

    Google Brain / Google · 2000-2021

Expertise & education

Expertise

Large Language Models (LLMs)Transformer ArchitectureMixture of Experts (MoE)Machine Learning InfrastructureAI-Driven PersonalizationNatural Language ProcessingConversational AIAd Relevance and Ranking Systems

Education

  • B.S. Computer Science, Duke University

Speaking topics

Large Language Models and their applicationsTransformer architecture and attention mechanismsEfficient scaling of AI modelsConversational AI and human-computer interaction

Recognition

Notable achievements

  • Co-authored 'Attention Is All You Need' (2017), introducing the Transformer architecture now foundational to all major LLMs
  • Co-founded Character.AI, which was acquired by Google in 2024 for approximately $2.7 billion
  • Contributed to Mixture of Experts (MoE) research enabling efficient large-scale model deployment
  • Key contributor to Google's core machine learning and search ranking infrastructure over two decades

Awards

Test of Time Award — 'Attention Is All You Need' paper widely recognized as one of the most cited and impactful ML papers in history

Publications

  • Vaswani, A., Shazeer, N., et al. — 'Attention Is All You Need' (NeurIPS 2017)
  • Shazeer, N., et al. — 'Outrageously Large Neural Networks: The Sparsely-Gated Mixture-of-Experts Layer' (ICLR 2017)
  • Shazeer, N. — 'GLU Variants Improve Transformer' (2020)
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