Researchers are developing a deep learning algorithm that could act as an early warning system against runaway climate change.
Chris Bauch, a professor of applied mathematics at the University of Waterloo, is co-author of research that looks at thresholds beyond which rapid or irreversible change happens in a system. The research is described in "Deep Learning for Early Warning Signals of Tipping Points," published in the journal Proceedings of the National Academy of Sciences.
The researchers say they programmed the AI to learn not just about one type of tipping point but the characteristics of tipping points generally. The approach gains its strength from hybridizing AI and mathematical theories of tipping points. The AI was trained on what is characterized as a "universe of possible tipping points" that included some 500,000 models.
"The new algorithm was able to not only predict the tipping points more accurately than existing approaches but also provide information about what type of state lies beyond the tipping point," Bauch says. "Many of these tipping points are undesirable, and we'd like to prevent them if we can."
From University of Waterloo
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