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In mid-May, OpenAI announced that an internal AI model had disproved the Erdős unit distance conjecture, a famous problem in ...

Abstract: Large-scale sparse multiobjective optimization problems (LSMOPs) are of great significance in the context of practical applications, such as critical node detection, feature selection, and ...

A high-performance Rust-based nonlinear least squares optimization library designed for computer vision applications including bundle adjustment, SLAM, and pose graph optimization. Built with focus on ...

Abstract: In planning and scheduling, large-scale optimization problems often have complex limits and a lot of factors, which makes them hard to answer with standard methods. Quantum annealing has ...

Using AI chatbots for even just 10 minutes may have a shockingly negative impact on people’s ability to think and problem-solve, according to a new study from researchers at Carnegie Mellon, MIT, ...