{"id":5441,"date":"2019-11-09T00:40:00","date_gmt":"2019-11-08T23:40:00","guid":{"rendered":"https:\/\/www.sonnenseite.com\/future\/tackling-climate-change-with-artificial-intelligence.html"},"modified":"2019-11-09T00:40:00","modified_gmt":"2019-11-08T23:40:00","slug":"tackling-climate-change-with-artificial-intelligence","status":"publish","type":"post","link":"https:\/\/www.sonnenseite.com\/en\/future\/tackling-climate-change-with-artificial-intelligence\/","title":{"rendered":"Tackling climate change with artificial intelligence"},"content":{"rendered":"

The expert network “Climate Change AI” releases an analysis of potential applications, and prepares for drawing entrepreneurs and investors from across the world.<\/p>\n

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The expert network “Climate Change AI”, a group of 22 scientists from academic institutions and engineers from industry, has released a comprehensive analysis detailing how artificial intelligence (AI) can be used to fight climate change. The network has prominent members like Yoshua Bengio, a Canadian computer specialist and pioneer on artificial neural networks. Also, two scientists of the Berlin climate research institute MCC (Mercator Research Institute on Global Commons and Climate Change) take part: Felix Creutzig<\/a>, head<\/span> of the MCC working group Land Use, Infrastructure and Transport, and researcher Nikola Milojevic-Dupont<\/a><\/span> <\/span>.<\/span> <\/p>\n

Covering various potential applications of AI, <\/span>the 50-page paper <\/span>is freely available from the network’s website (<\/span>www.climatechange.ai<\/span><\/a>, direct download here<\/a>). A preliminary version had already been circulated in June this year at a workshop of the International Conference on Machine Learning in Los Angeles, United States. The now fundamentally revised analysis is accompanied by additional digital resources and by a discussion forum aimed at bringing together experts in AI and areas like energy, agriculture, and disaster response.<\/span> <\/p>\n

The authors focus on machine learning, a powerful branch of artificial intelligence that can learn from data to find patterns and can optimize solutions much more quickly than humans. “Machine learning can be deployed to help reduce greenhouse gas emissions and build a society that is more resilient to climate change,” says David Rolnick, a postdoctoral fellow at the University of Pennsylvania, who led the writing of the paper. “It can help design better batteries, control heating and cooling systems efficiently, track the effects of a changing climate using satellite imagery, and a lot more.”<\/span> <\/p>\n

However, the authors emphasise that machine learning is not a silver bullet, and that all applications require cooperation between many stakeholders. “It is an important step forward that the AI community starts to be interested in climate mitigation”, MCC scientist Creutzig emphasises. “There is a lot of progress in sight, serving public administrations and consumers as well as industry. And AI will have much impact on how we will plan our living spaces and transport facilities in urban areas in the future.”<\/span> <\/p>\n

The network is now preparing an even larger workshop in December at the 2019 Conference on Neural Information Processing Systems in Vancouver, Canada. The aim is to further draw researchers, entrepreneurs, and investors from across the world.<\/span><\/p>\n<\/p><\/div>\n

Source<\/h5>\n

MCC (Mercator Research Institute on Global Commons and Climate Change) 2019<\/a><\/span><\/p>\n

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