A research paper explores the limitations of current systematic generalization tasks in AI, specifically the ability of models to recombine known elements to solve novel problems. The study introduces a new testbed, TranSGrid, which evaluates deductive, inductive, and abductive reasoning. The results show that existing tasks may not comprehensively measure systematic generalization, and that a more nuanced approach is needed.