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A number of experts believe the Earth is rapidly approaching its 'tipping point' for reversing climate change, but researchers at Canada's University of Waterloo are creating artificial intelligence that could act as an 'early warning system' against a runway threat to the planet.
The deep learning algorithm was created to better predict the tipping points, while also understanding what happens after they have been reached, the study's co-author, Chris Bauch, a professor of applied mathematics at the University of Waterloo, said.
'Many of these tipping points are undesirable, and we'd like to prevent them if we can,' Bauch said in a statement.
Canadian researchers are creating AI that could act as an 'early warning system' against runway climate change. The deep learning algorithm can predict the tipping points and understand what happens after they have been reached
In May, scientists said there was a 40 percent chance that annual temperature rises would go beyond the the 1.5C (2.7F) set by the 2015 Paris Agreement.
Some of these tipping points include the melting of the Arctic permafrost, extreme heat, the disintegration of ice sheets, ocean acidification and ruminant livestock.
For the first time, the researchers were able to teach the deep learning to detect the tipping points and convert that into a pattern-recognition problem in order to help them learn the patterns before the tipping point occurs.
The deep learning algorithm was created to better predict the tipping points, while also understanding what happens after they have been reached,
'People are familiar with tipping points in climate systems, but there are tipping points in ecology and epidemiology and even in the stock markets,' said study co-author and researcher at McGill University Thomas Bury.
'What we've learned is that AI is very good at detecting
