Matthias Georg Mayer
Bio
Matthias Georg Mayer is an independent researcher and mathematician working in AI safety, with a focus on agent foundations and providing formal guarantees for the safety of AI systems. He was a 2025 Alumni Fellow at Principles of Intelligence (PIBBSS), where he worked on theoretical alignment research. His earlier work centered on structural independence, a generalization of d-separation concepts applied to structural causal models (also known as Finite Factored Sets), and he co-authored the paper "Factored space models: Towards causality between levels of abstraction" (arXiv 2412.02579, December 2024) alongside Scott Garrabrant, Magdalena Wache, Leon Lang, Sam Eisenstat, and Holger Dell. More recently his interests have shifted toward the Learning Theoretic Agenda developed by Vanessa Kosoy, with particular focus on Infrabayesian-Physicalism as a means to address embedded agency. He has received funding from the Long-Term Future Fund (LTFF) to research framing computational systems in ways that surface meaningful concepts. He participates in the AI alignment community through the Alignment Forum and LessWrong under the handle matthias-g-mayer.
Links
- Personal Website
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- Twitter / X
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- LessWrong
- matthias-g-mayer
Grants
from Long-Term Future Fund
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Details
- Last Updated
- Mar 22, 2026, 11:27 PM UTC
- Created
- Mar 20, 2026, 2:55 AM UTC