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Common feature between forest fires and neural networks reveals universal framework

June 29, 2019 | Phys.org AI
Common feature between forest fires and neural networks reveals universal framework
Both a wildfire and activity of digital "neurons" exhibit a phase transition from an active to an absorbing phase. Once a system reaches an absorbing phase, it cannot escape from it without outside help. Credit: Tamai et al 2025 Researchers from the University of Tokyo in collaboration with Aisin Corporation have demonstrated that universal scaling laws, which describe how the properties of a system change with size and scale, apply to deep neural networks