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How artificial intelligence can deal with climatic change

The substantial challenge facing the planet might be solved by machine learning and Artificial Intelligence for a better future.  

It is good to see an opportunity to help with the causes of changes in our climate. The biggest names in Artificial Intelligence and machine learning released a manuscript by the name ‘Tackling Climate Change with Machine Learning.’  The paper was the main discussion during a workshop on AI, which took place in June. The article was a “call to arms” to bring different researchers together. 

David Rolnick, the seminar organizer, said that it was to his surprise that machine learning could solve many problems, one of them being climate change. 

The paper has thirteen main areas that talk about the application of machine learning setup, for instance, reduction of carbon (IV) oxide, solar geoengineering, production of energy, and finance. In these areas, some of the changes comprise additional energy-yielding utilities, efficient monitoring of deforestation, greener transportation, and making new low-carbon materials. However, Rolnick said that these are early times, and AI won’t be a solution, despite its efforts. 

Artificial Intelligence might not be the perfect solution, but it brings new understandings to the situation. Below are three ways machine learning can help curb climate change. 

1. Excellent climate prediction 

Such push is on the work that is already accomplished by climate informatics, and a discipline that was created back in 2011.  The discipline lies between climate science and data science. Climatic information entails topics that vary from better forecasts of drastic occasions like hurricanes, remaking previous climate situations using information collected from ice cores to forecasting weather on a hyperlocal level as well socio-economic impacts on climate change. 

Artificial Intelligence can also unveil new knowledge from vast proportions of climate simulations produced by an area of climate modeling that has evolved since the debut system, which was created at the Princeton in the 1960s. 

2. Showing the impacts of extreme weather 

The majority of homeowners have started to encounter the impacts caused by extreme weather. Others feel it is not something to get worried about. To make people understand the causes of climate impacts, scientists from Montreal Institute for Learning Algorithms (MILA), ConscientAI Labs, and Microsoft used GANs, a prototype of AI to be able to show what homes would look after the rising sea levels damaged them. 

3. Assessing the origin of carbon

Carbon Tracker is an autonomous financial think tank operating for the UN target of stopping the development of new coal-fired plants by 2020. Carbon Tracker will use the data it gathers to persuade the financial industry that carbon plants aren’t competitive by tracking coal plant emissions with satellite imagery.