# Machine Learning: Physics Simulation, Kolmogorov Complexity, and Squishy Bunnies

*Source* · `src-holden-2020-gdc-squishy-bunnies` · status: **n/a**

| field | value |
|---|---|
| kind | Talk / video |
| authors | Daniel Holden |
| venue | GDC 2020 (GDC Vault) |
| date | 2020 |
| url | https://gdcvault.com/play/1026713/Machine-Learning-Physics-Simulation-Kolmogorov |
| accessed | 2026-10-24 |
| notes | Ubisoft Montreal talk on learned interactive physics and cloth, approximately 300 to 5000 times faster than standard simulation; does not name a shipped title. |

## Backlinks (computed)

**cited by:** [Subspace neural physics and learned deformers](../technique/subspace-neural-physics.md)

## Citation

Daniel Holden (2020). *Machine Learning: Physics Simulation, Kolmogorov Complexity, and Squishy Bunnies*. GDC 2020 (GDC Vault) https://gdcvault.com/play/1026713/Machine-Learning-Physics-Simulation-Kolmogorov

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Provenance: created in run `2026-10-24-techniques-sim-math`.