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Causal AI

Physical benchmarks for testing algorithms

Nature Machine Intelligence volume 7, pages 166–167 (2025)Cite this article

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The development of comprehensive benchmarks to assess the performance of algorithms on causal tasks is an important, emerging area. The introduction of two physical ‘causal chamber’ systems serves as a firm step towards future, more reliable benchmarks in the field.

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Fig. 1: Ice-cream, sunshine and causal modelling.

Artur Debat / Moment / Getty images

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Authors and Affiliations

  1. Department of Statistics, University of Oxford, Oxford, UK

    Jakob Zeitler

  2. SMARTbiomed, Big Data Institute, University of Oxford, Oxford, UK

    Jakob Zeitler

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  1. Jakob Zeitler
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Correspondence to Jakob Zeitler.

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The author declares no competing interests.

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Zeitler, J. Physical benchmarks for testing algorithms. Nat Mach Intell 7, 166–167 (2025). https://doi.org/10.1038/s42256-025-00999-8

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