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Chris Olah - Wikidata

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Credibility Rating

3/5
Good(3)

Good quality. Reputable source with community review or editorial standards, but less rigorous than peer-reviewed venues.

Rating inherited from publication venue: Wikidata

Wikidata entry for Chris Olah, a key AI safety researcher known for pioneering mechanistic interpretability work at Google Brain, OpenAI, and Anthropic, where he leads interpretability research.

Metadata

Importance: 30/100wiki pagereference

Summary

This is the Wikidata structured data entry for Christopher Olah (colah), an AI researcher specializing in deep learning, natural language processing, and mechanistic interpretability. He has worked at Google, OpenAI, and currently leads interpretability research at Anthropic. His blog and research have been foundational to the field of neural network interpretability.

Key Points

  • Chris Olah is a leading researcher in mechanistic interpretability, a core AI safety research area focused on understanding neural network internals.
  • He has held positions at Google, OpenAI, and Anthropic, where he currently leads interpretability research.
  • His GitHub handle is 'colah' and his blog at colah.github.io is widely cited in the ML/AI safety community.
  • Fields of work include natural language processing, deep learning, and mechanistic interpretability.
  • His Google Scholar ID is 6dskOSUAAAAJ, enabling access to his academic publications.

2 FactBase facts citing this source

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 From Wikidata 
 
 
 
 
 
 
 
 artificial intelligence researcher Christopher Olah
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