Columbia engineers have developed a machine-learning algorithm that will aid in understanding and mitigating the impact of extreme weather events, which are becoming more frequent in our warming climate.
As director of the Learning the Earth with Artificial Intelligence and Physics (LEAP) Center, Pierre Gentine is aiming to bring greater precision to climate modeling and innovative solutions to the climate crisis.
Have Da Vinci, an artificial intelligence engine created by OpenAI, compose a haiku on the science or nature topic of your choice!
Glacier modeling techniques that involve artificial intelligence can produce high fidelity results to a large number of questions much more quickly than traditional approaches.
A grad student and his colleagues search for innovative new ways to detect and disarm millions of hidden hazards.
A new venture will leverage big data and many disciplines to create better estimates of future climate.
A new artificial neural network named CALFIN catalogues the rates at which glaciers are melting, demonstrating what the future of glaciology could look like.
In the U.S., some 2,000 high hazard dams are in need of repairs. A project from the Columbia Water Center is helping to identify the most hazardous ones.
A new study uses machine learning to better represent clouds in climate models, which helps to predict the climate’s response to rising levels of greenhouse gases.
A new algorithm quickly sifts through hours of field recordings to learn how climate change influences bird migration. The A.I. could help track other wildlife as well.
