Real physical systems as a testbed for AI methodology
If you do basic research in AI & ML, it can be a struggle to find real-world datasets to validate your work. Often, the best we can do is test new methods on synthetic data, making it difficult to asses core assumptions and predict how well an algorithm would work in practice.
The Causal Chambers are here to help. As computer-controlled laboratories built around well-understood physical systems, they provide real-world datasets with a ground truth for fields where such datasets are otherwise scarce or non-existent.
Access the Chambers
The chambers are a tool for educators and scientists who do basic research in AI & ML. Depending on your needs, there are several ways you can access the chambers and their data.
Dataset repository
Fully documented, open-source datasets collected from the chambers. Updated regularly with new experiments & benchmarks.
Please reach out if you need help navigating the repository.
Custom Datasets
Do you have a use case in mind but the appropriate dataset is not yet on the repository?
We can collect custom datasets on request. We are also happy to help you design new benchmarks and collaborate on scientific research.
Own a Chamber
Collect your own datasets with full, uninterrupted access to the chambers. For applications in active learning, RL & control, etc. For conference competitions, teaching and demonstrations.
Manufactured in Switzerland
1-year warranty
Full documentation
Set-up support
Research
Research papers that use chamber data
Context is Key: A Benchmark for Forecasting with Essential Textual Information
Andrew Robert Williams, Arjun Ashok, Étienne Marcotte, Valentina Zantedeschi, Jithendaraa Subramanian, Roland Riachi, James Requeima, Alexandre Lacoste, Irina Rish, Nicolas Chapados, Alexandre Drouin
Contact
Do you need help navigating the dataset repository? Do you have an application or case study in mind? Would you or your research group like to own a chamber?
Please reach out via email! We’re happy to help.