This is the era of big-data: high-volume, high-velocity and high-variety information assets are being collected, demanding cost-effective information processing. Analytic techniques primarily based on statistical methods are showing astonishing results, but exhibit also limited reasoning capabilities. On the other end of the spectrum the era of bigreasoning is emerging with next-generation cognitive and autonomous end-to-end solvers. A problem description in terms of text and diagrams is given: problem solvers should automatically understand the problem, identify its components, devise a model, identify a solving technique and find a solution with no human intervention. We propose a challenge: to design and implement an end-to-end solver for mathematical puzzles able to compete with primary school students. Mathematical puzzles require mathematics to solve them, but also logic, intuition and imagination are essential ingredients, thus calling for an unprecedented integration of many different AI techniques.
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