10 Bits: the Data News Hotlist – Center for Data Innovation

This week’s list of data news highlights covers April 27-May 3, 2019, and includes articles about an AI system that can mimic Van Gogh and an AI system that maps Saturn’s storms.

The U.S. Food and Drug Administration (FDA) is launching a pilot to use AI to decide which food shipments humans should inspect. The system will use a machine-learning model to analyze factors, including the type and supplier of the food, affecting the likelihood a food shipment is hazardous. The United States imported 14 million different food and animal-feed products in 2018, and the FDA will test the AI system against historical results to determine how accurately it flags hazardous shipments.

ClimaCell, a weather technology startup based in Boston, has developed a system to use the signals from wireless devices, such as cellphones and IoT devices, to provide forecasts with as much as 60 percent more accuracy than traditional methods. Climacell’s system analyzes the quality of signals from millions of devices as a proxy for weather conditions, including precipitation and air quality, and uses images from street cameras to increase the accuracy of its system.

Researchers from IBM and New York University have developed an AI system that can help detect and predict the progression of glaucoma. Glaucoma can cause visual defects, which is why physicians use visual field tests to map how well patients see, but these tests can be inaccurate because they rely exclusively on patient feedback. The researcher’s AI system estimates a patient’s visual field index from a single image of the optic nerve, allowing a physician to quickly learn a patient’s visual function without multiple time-consuming tests.

Researchers from the University of Maryland, Adobe, and ByteDance, a Chinese technology company, have developed an AI system called PaintBot that can generate paintings in the style of a particular artist, such as Van Gogh, or in a style itself, such as pointillism. The researchers trained a reinforcement learning algorithm on three to ten paintings per style or artist, and Paintbot can learn to imitate a given painter in roughly six hours. Paintbot learns the color, density, position, size, and order of brushstrokes of a painter or style, allowing it to create new paintings in the desired style based on photos.

Researchers from the University of Arizona and University College London have developed a deep learning algorithm called PlanetNet that identifies and maps Saturn’s storms. The researchers provided PlanetNet a dataset of infrared data from multiple of Saturn’s storms in 2008, and the algorithm analyzed the data for signs of clustering in the atmosphere’s cloud structure and gas composition. PlanetNet then produced a map that illustrated profound differences between the center of storms and surrounding areas, revealing that the clouds were part of a large upwelling of ammonia ice clouds that surrounded a central storm.