AI Village

The AI Village runs all frontier agents, persistently, autonomously, on real-world goals, while working together. We aim to generate insights on what agents do when left to their own devices, with most of the affordances and tools a human might have to do those same jobs. 

Stream overview

In this stream people will either analyze our existing data for new insights or run their own experimental version of the Village to test specific hypotheses. The experiments could be around multi-agent dynamics or real-world evaluation.  Specific examples:   

  

  • Come up with and test a better AI monitoring system by using our 1000s of hours of CoTs, messages, and actions of over 20 different agents acting in the real world 

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  • Explore our data for traces of steganography, deception, or misalignment

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  • Design and run a real-world experiment where multiple frontier models are shown to perform better in unison than alone through autonomous self-organization. Possibly compare performance between diverse and uniform teams of models, as on the one hand similar models may collaborate more easily, while on the other hand different models might compensate for each other's blind spots  

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  • Design and run a real-world eval that shows agent-to-agent jailbreaking or misalignment (e.g., where a more capable and aligned agent is "corrupted" by a less capable and less aligned one in a surprising way). Designs will need to be non-adversarial toward the agents. 

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These ideas are illustrative of what's possible, but I'd be excited to hear about new ideas as well

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Note: Mentees can run their experiments using the AI Village compute budget and setup if their project is approved

Mentorship style:

Standard (1-2 hours of weekly 1:1s)

London location preference:

Indifferent

Berkeley location preference:

Indifferent

Mentors

Shoshannah Tekofsky
Sage
,
Member of Technical Staff
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Shoshannah Tekofsky is a member of technical staff at Sage, the nonprofit that runs AI Digest and the AI Village. Tekofsky works on the AI Village, in which several frontier language models pursue their own goals continuously on their own computers.

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Fellows we are looking for

  • Good writing skills: previous scientific publications or well-read blog
  • Good data visualization intuitions: portfolio with infographics would be ideal
  • Experience with analyzing large data sets
  • Strong intuitions about LLM behavior

Project selection