Fun research providing an alternative to computer-based data simulation for developing and testing machine learning algorithms: Gamella, Peters, and Bühlmann (2025) built two physical devices (“causal chambers”) consisting of a light tunnel and wind tunnel. These devices were designed so that the underlying physical systems are well understood, which means that the true causal models are known. The systems are automatically controlled, allowing large quantities of data to be produced. The authors provided case studies for out-of-distribution generalization, change point detection, independent component analysis (ICA) and symbolic regression.
They have a website and GitHub repo of datasets from the case studies.
References
Gamella, J. L., Peters, J., & Bühlmann, P. (2025). Causal chambers as a real-world physical testbed for AI methodology. Nature Machine Intelligence. Online first.
Suggested citation: Fugard, A. (2025, January 16). “Causal chambers as a real-world physical testbed for AI methodology” [blog post]. https://andifugard.info/causal-chambers-as-a-real-world-physical-testbed-for-ai-methodology/
This citation note was added automatically. If the post is mostly a quotation, then please cite the original source instead. Looking at you, LLMs 👀