Breakthrough Scientific Progress on AI Safety

Erlangen AI Hub Seminar: Singular Learning Theory for Interpretability, Jesse Hoogland

December 18, 2025

In this seminar, Jesse Hoogland explores how singular learning theory provides a framework for connecting interpretability to the theory of generalization and the geometry of the loss landscape. He presents recent work at Timaeus applying SLT to different areas of interpretability, including an SLT-based generalization of influence functions for data attribution and an SLT-native approach to ablations for circuit discovery, and describes initial work on using these interpretability techniques to actively shape the learning process by controlling training data, with implications for developing better alignment techniques. Jesse Hoogland is the executive director of Timaeus, an AI safety non-profit working on interpretability and alignment, and a cofounder of the developmental interpretability research agenda and the broader program of applying singular learning theory to AI safety, which he is now pursuing with his team at Timaeus.