Researchers develop AI that solves a matrix-based visual cognitive test

Multiple choice tests provide test-takers the ability to compare answers to eliminate choices (or guess the correct one). Each choice can be compared with the question to infer patterns that might have been missed; it's arguably the ability to narrow down the right answer from sets of answers that's the test of true comprehension. Inspired by this, researchers at Tel Aviv University and Facebook developed a machine learning model that generates answers to the Raven Progressive Matrix (RPM), a type of intelligence test where the goal is to complete the location in a grid of abstract images. The coauthors claim that their algorithm is not only able to generate a plausible set of answers competitive with state-of-the-art methods, but that it could be used to build an automatic tutoring system that adjusts to the proficiencies of individual students. RPM is a nonverbal test typically used in educational settings like schools.