The big headlines on this release are efficiency, with OpenAI reporting that GPT-5.4 uses far fewer tokens (47% fewer on some tasks) than its predecessors).

Abstract: Machine Learning (ML)-based optimization frameworks emerge as a promising technique for solving large-scale Mixed Integer Linear Programs (MILPs), as they can capture the mapping between ...

Imagine being able to build a master school schedule in 30 minutes.

Abstract: Many classical and modern machine learning algorithms require solving optimization tasks under orthogonality constraints. Solving these tasks with feasible methods requires a gradient ...

Moving heavy materials through cutting, polishing and coating stages requires precise balancing of load capacity and motion speed. Here’s how the right linear guidance selection and configuration can ...

Excel has outlasted many tech trends, and in the age of AI, it remains very much in the mix. While new platforms promise automation and out-of-the-box intelligence, many teams continue to rely on ...

Amateur mathematicians are using artificial intelligence chatbots to solve long-standing problems, in a move that has taken professionals by surprise. While the problems in question aren’t the most ...

Enterprises across industries, from energy to finance, use optimization models to plan complex operations like supply chains and logistics. These models work by defining three elements: the choices ...

AI-powered search isn’t coming. It’s already here: As rankings and clicks matter less, citations matter more. Businesses now need content that AI engines trust and reference when answering questions.

NVIDIA's GPU-accelerated cuOpt engine discovers new solutions for four MIPLIB benchmark problems, outperforming CPU solvers with 22% lower objective gaps. NVIDIA's cuOpt optimization engine has found ...

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