Meteorologists are starting to experiment with deep learning tech to predict severe weather patterns. David Gagne, a postdoctoral researcher at the US National Center for Atmospheric Research (NCAR), developed a simple convolutional neural network model to forecast the chances of hailstorms. In the last decade, severe storms caused about $14bn worth of damage and killed 94 people per year, Gagne said during a presentation at the GPU Technology Conference in San Jose, California. Meteorologists begin warning people of severe weather conditions the day before a hail event, but it's difficult to be precise. So Gagne wanted to see if deep learning could accurately identify the weather patterns leading up to hailstorms and reduce false alarms.