"Estimating No-CoT Task-Completion Time Horizons of Frontier AI Models" by Anders Cairns Woodruff, Francis Rhys Ward, Dewi Gould, Rauno Arike, Jason R Brown, Jo Jiao, wlanderson, ariana_azarbal, harrymayne, Patrick Leask

About this episode

The episode discusses the implications of frontier AI models completing tasks without chain of thought and its relevance to safety.

(see full author list at the end) PAPER LINK About a year ago, METR showed that the length of tasks frontier models can reliably complete doubles every few months. A related safety-relevant question is this: what length of tasks can models complete without any chain of thought (CoT)? If models can do extensive reasoning without outputting any CoT, it would have implications for safety. Developers and deployment-time monitors couldn’t easily understand models’ motivations and catch dang...

People in this episode

Guests: Anders Cairns Woodruff, Francis Rhys Ward, Dewi Gould, Rauno Arike, Jason R Brown, Jo Jiao, wlanderson, ariana_azarbal, harrymayne, Patrick Leask

Topics covered

• AI safety
• task completion
• frontier models
• chain of thought
• reasoning
• deployment monitoring

Keywords

• AI models
• task length
• safety implications
• reasoning without CoT
• deployment-time monitoring

Mentioned in this episode

Organizations: METR

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