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.
The AI car computer called Drive PX will be combined with German automotive supplier ZF's self-driving platform in a fleet test planned by package delivery and logistics vendor Deutsche Post DHL Group (DPDHL). The goal is solving one of the biggest challenges for automating package delivery: getting deliveries the "last mile" between a central location to their final destination. The 2018 demonstration will use the package delivery company's (ETR: DPW) fleet of 3,400 electric delivery vehicles outfitted with cameras, radar and lidar (light detection and ranging). Sensor data is fed into an AI platform based on Drive PX. The partners claimed the combination can leverage AI and deep learning to allow autonomous vehicles to understand its surroundings, plot and drive along a safe route, and then park itself at the delivery point.