Rolnick, David, Donti, Priya L., Kaack, Lynn H., Kochanski, Kelly, Lacoste, Alexandre, Sankaran, Kris, Ross, Andrew Slavin, Milojevic-Dupont, Nikola, Jaques, Natasha, Waldman-Brown, Anna, Luccioni, Alexandra, Maharaj, Tegan, Sherwin, Evan D., Mukkavilli, S. Karthik, Kording, Konrad P., Gomes, Carla, Ng, Andrew Y., Hassabis, Demis, Platt, John C., Creutzig, Felix, Chayes, Jennifer, Bengio, Yoshua
Climate change is one of the greatest challenges facing humanity, and we, as machine learning experts, may wonder how we can help. Here we describe how machine learning can be a powerful tool in reducing greenhouse gas emissions and helping society adapt to a changing climate. From smart grids to disaster management, we identify high impact problems where existing gaps can be filled by machine learning, in collaboration with other fields. Our recommendations encompass exciting research questions as well as promising business opportunities. We call on the machine learning community to join the global effort against climate change.
Technology is powering the rise of smart cities, transforming everything from traffic management to waste collection. We dig into the digital revolution giving rise to cities that are more connected, sustainable, and efficient -- and what the future of urbanization might look like. Cities are evolving at a rapid pace. Over half the world's population currently lives in urban areas. By 2050, that number is expected to jump to 70%. Along with a growing population, new challenges are emerging as cities look to improve everything from infrastructure to connectivity. Many see this as a viable business opportunity, developing technology to help cities efficiently provide proper foundation, energy, transportation, resources, jobs, and services to their residents. As a result, cities are undergoing a digital transformation -- that is, they are turning into "smart" cities. Get a data-driven look at the startups and industry players developing smart city technologies.