Lifeboat.com published an article on the latest findings of Ceres2030, a project designed to solve global hunger over the next decade. Ceres2030 employed machine learning, librarian savvy, and research synthesis methods to quickly scan a trove of thousands of scientific journals for ideas and websites from more than 60 agencies that can help eradicate world hunger. One of the scientists of the most recent report, Ceres2030: ‘Sustainable Solutions to End Hunger, principal investigator, and co-director Jaron Porciello stated, "We're trying something new that hasn't been done before. We know the tools weren't there, the methods weren't there and the teams weren't in place. Now, we've created some staircases to make science and world reality connect a little bit more. This approach could be replicated to build a scientific evidence base for many of the world's most complex policy problems." Republished in Phys.org and Biology News
