One word: AI – Many of the world's leaders in the field of science and technology, including the late Stephen Hawking, Telsa founder Elon Musk, Apple co-founder Steve Wozniak and Microsoft founder Bill Gates, have all expressed concern in recent years over the risks of artificial intelligence (AI) – most notably its potential use in autonomous weapons. Along with many in academia and human rights groups, the science and tech visionaries have warned that in the wrong hands there is a serious danger posed by AI. One concern is that these weapons could be designed to be extremely difficult to simply "turn off," as the Future of Life Institute noted in its report on the development of autonomous weapon platforms. That could result in a scenario straight out of science fiction where humans lose control of their dangerous creations. While it may not mean a world-ending scenario presented in The Terminator, even losing control of a few AI weapons temporarily could result in unnecessary mass causalities or worse.

"There are a number of seagrass monitoring programs that work on regional and to some degree on global scales, but most of them are really only looking at the cover and the abundance of the seagrass itself," said Emmett Duffy, director of the Marine Global Earth Observatories (MarineGEO) headquartered at the Smithsonian Environmental Research Center. The new grant builds on collaborative work by the Zostera Experimental Network (ZEN), led by Duffy, and will look at how climate, biodiversity and other environmental aspects can change the course of the disease. The team is deploying a wide arsenal of weapons to understand it: In addition to marine biologists, they are bringing on geographers, computer scientists, artificial intelligence and drones. Seagrasses are among the most valuable ecosystems on Earth. They provide habitat for popular fish like salmon and herring, protect shorelines from erosion and filter out nutrient pollution.

Three years ago, Jinghui Zhang, chair of the department of computational biology at St. Jude Children's Research Hospital in Memphis, tried to download a set of 1,547 samples from a government database so she could run an experiment on it. The download took a year and a half. Every time Zhang's team thought they had the complete set of data, they performed a statistical check that was supposed to catch any transmission errors. Seven times, the check failed. Seven times, the team started working only to realize that part of the set was missing, and they'd have to start all over.