In a study published this week on the preprint server Arxiv.org, Microsoft and Arizona State University researchers propose an AI framework — Multiple sources of Weak Social Supervision (MWSS) — that leverages engagement and social media signals to detect fake news. They say that after training and testing the model on a real-world data set, it outperforms a number of state-of-the-art…

Carnegie Mellon, Google, and Stanford researchers write in a paper that they’ve developed a framework for using weak supervision — a form of AI training where the model learns from large amounts of limited, imprecise, or noisy data — that enables robots to efficiently explore a challenging environment. By learning to reach only areas of its surroundings relevant to tasks as opposed to every…