Artificial intelligence systems may be good at generating text, recognizing images, and even solving basic math problems—but when it comes to advanced mathematical reasoning, they are hitting a wall.

There’s a curious contradiction at the heart of today’s most capable AI models that purport to “reason”: They can solve routine math problems with accuracy, yet when faced with formulating deeper ...

EdSource · Hot classrooms, leaky roofs — one student’s fight for better school facilities (Rebroadcast) While policymakers, researchers and educators decide how our children learn math, parents don’t ...

This study introduces MathEval, a comprehensive benchmarking framework designed to systematically evaluate the mathematical reasoning capabilities of large language models (LLMs). Addressing key ...

A National Academies of Sciences, Engineering, and Medicine-appointed ad hoc committee will plan and organize a workshop that will bring together academic, industry, and government stakeholders to ...

This activity was supported by a contract between the National Academy of Sciences and the National Science Foundation. Any opinions, findings, conclusions, or recommendations expressed in this ...

In the 1970s, the late mathematician Paul Cohen, the only person to ever win a Fields Medal for work in mathematical logic, reportedly made a sweeping prediction that continues to excite and irritate ...

Mathematicians excel at handling complexity and uncertainty. Mathematical reasoning strategies aren't just useful for dilemmas involving numbers. We can apply math mindsets to improve our approach to ...

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Spatial reasoning measured in infancy predicts how children do at math at four years of age, finds a new study. It provides the earliest documented evidence for a relationship between spatial ...