Arbital was built starting in January 2015 to solve a problem Eliezer Yudkowsky identified: that conventional blog posts, essays, and Wikipedia-style articles were insufficient for conveying complex ideas to readers with varying backgrounds. The platform offered adaptive 'lenses' (the same page rendered at different knowledge levels), a prerequisite network that could generate personalized reading sequences, and support for embedded probabilistic claims. Most of its content covered AI alignment and mathematics, contributed primarily by Yudkowsky, Nate Soares, and Paul Christiano. After failing to achieve the user growth needed to sustain the platform, it was shut down in 2017 and its intellectual property was transferred to MIRI.
Funding Details
- Annual Budget
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- Monthly Burn Rate
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- Current Runway
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- Funding Goal
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- Funding Raised to Date
- $300,000
- Fiscal Sponsor
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Theory of Change
Arbital's implicit theory of change was that progress on AI alignment and related difficult intellectual problems is bottlenecked in part by the difficulty of communicating complex ideas — both to recruit new researchers and to allow existing researchers to build on one another's work efficiently. By creating a platform that could present the same ideas at multiple levels of depth and could sequence explanations based on reader prerequisites, Arbital aimed to lower the barrier to engaging with cutting-edge alignment research. More broadly, the platform hoped to reduce duplication of effort in online intellectual discourse by creating canonical, living explanations that could be updated and shared rather than reinvented in each new conversation.
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Details
- Last Updated
- Apr 2, 2026, 10:10 PM UTC
- Created
- Mar 19, 2026, 10:30 PM UTC