New analysis provides mathematical and behavioral economics evidence supporting the accelerated payoff debt elimination ...

AI could soon spew out hundreds of mathematical proofs that look "right" but contain hidden flaws, or proofs so complex we ...

Deep learning is increasingly used in financial modeling, but its lack of transparency raises risks. Using the well-known ...

A team of researchers has found a way to steer the output of large language models by manipulating specific concepts inside ...

A new proposal calls on social media and AI companies to adopt strict verification, but the company hasn’t committed to ...

Extracting and analyzing relevant medical information from large-scale databases such as biobanks poses considerable challenges. To exploit such "big data," attempts have focused on large sampling ...

Historian Philip Decker, mathematician Victor Geadah, computer scientist Sayash Kapoor, and literary scholar Eliana Rozinov are this year’s Porter Ogden Jacobus Fellows.

Traditional computational electromagnetics (CEM) methods—such as MoM, FEM, or FDTD—offer high fidelity, but struggle to scale ...

A marriage of formal methods and LLMs seeks to harness the strengths of both.

Large language models struggle to solve research-level math questions. It takes a human to assess just how poorly they ...

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The GSMM Camp is a weeklong workshop directed towards interdisciplinary problem solving whose aim is graduate student education and career development. The GSMM Camp is designed to promote a broad ...