Uploaded August 2026 | Updated September 2026, 3 weeks ago
Recorded 31 August 2026. Paul Christiano of the Alignment Research Center presents "Mechanistic Estimation" at IPAM's Foundations of Interpretability Workshop.
Abstract: I will present a formalization of the conjecture that every surprising computational phenomenon has a good explanation. I will then discuss preliminary work aimed at explaining the behavior of simple computational systems and draw on historical experience in mathematics to argue that explanations might not only always exist but also be efficiently discoverable. Finally, I will argue that finding explanations for complex behaviors in neural networks would be a major advance in AI alignment and one of the most important contributions mathematics could make to AI safety.
Learn more online at: https://www.ipam.ucla.edu/programs/workshops/foundations-of-interpretability/?tab=overview
Recorded 31 August 2026. Paul Christiano of the Alignment Research Center presents "Mechanistic Estimation" at IPAM's Foundations of Interpretability Workshop.
Abstract: I will present a formalization of the conjecture that every surprising computational phenomenon has a good explanation. I will then discuss preliminary work aimed at explaining the behavior of simple computational systems and draw on historical experience in mathematics to argue that explanations might not only always exist but also be efficiently discoverable. Finally, I will argue that finding explanations for complex behaviors in neural networks would be a major advance in AI alignment and one of the most important contributions mathematics could make to AI safety.
Learn more online at: https://www.ipam.ucla.edu/programs/workshops/foundations-of-interpretability/?tab=overview
![Takeo Hoshi - General data-analysis framework ODAT-SE and its applications - IPAM at UCLA
Recorded 05 May 2026. Takeo Hoshi of the National Institute for Fusion presents General data-analysis framework ODAT-SE and its applications at IPAMs Fusion Device Design and Engineering Workshop.
Abstract: This talk first provides an overview of our project, “Backcasting Digital Systems by Super-Dimensional State Engineering” [1,2], which is part of the Moonshot R&D Program Goal 10 (MS10): “Realization of a dynamic society in harmony with the global environment and free from resource constraints through diverse applications of fusion energy by 2050” [3]. This program is a Japanese flagship initiative for fusion energy. Our project was launched at the end of 2024 as an interdisciplinary effort bridging the fusion energy field with other domains, including AI and data-driven science, simulation science, applied mathematics, and high-performance computing (HPC). The project aims to develop digital systems for the design of fusion devices, particularly tokamak and helical types, as well as for related materials experiments. This talk then introduces our data analysis framework, ODAT-SE (Open Data-analysis Tool for Science and Engineering, pronounced oh-daht ess-ee)[4]. ODAT-SE enables a variety of analysis methods, including parallelized Monte Carlo methods for Bayesian inference and parallelized Bayesian optimization. These methods are designed to run efficiently on both small-scale PCs and massively parallel supercomputers. This talk gives several preliminary results by ODAT-SE.
[1] https://www.jst.go.jp/moonshot/en/program/goal10/A3_hoshi.html
[2] https://ms10ds.nifs.ac.jp/ (Tentatively, Japanese only)
[3] https://www.jst.go.jp/moonshot/en/program/goal10/index.html
[4] https://www.pasums.issp.u-tokyo.ac.jp/odat-se/en/
Learn more online at: https://www.ipam.ucla.edu/programs/workshops/workshop-iii-fusion-device-design-and-engineering/ Takeo Hoshi - General data-analysis framework ODAT-SE and its applications - IPAM at UCLA](https://i.ytimg.com/vi/_U2XsZ7ddhw/mqdefault.jpg)









