SharpSMT first fuses DPLL(T) polytope enumeration with new factorization, variable-elimination and caching pre-processing, ...

Abstract: Dynamic environments pose great challenges for expensive optimization problems, as the objective functions of these problems change over time and thus require remarkable computational ...

CAMBRIDGE, U.K. – A small Microsoft Research team had lofty goals when it set out four years ago to create an analog optical computer that would use light as a medium for solving complex problems.

We are moving from a world of institutional dependency to one of personal responsibility. The question is no longer, “What can we do for people?” but, “How can we equip people to do more for ...

A line of engineering research seeks to develop computers that can tackle a class of challenges called combinatorial optimization problems. These are common in real-world applications such as ...

What if the toughest problems humanity faces—those that stump our brightest minds and stretch the limits of human ingenuity—could be tackled by a single, purpose-built system? Enter Gemini Deep Think, ...

Solving optimization problems is challenging for existing digital computers and even for future quantum hardware. The practical importance of diverse problems, from healthcare to financial ...

Google’s AI R&D lab DeepMind says it has developed a new AI system to tackle problems with “machine-gradable” solutions. In experiments, the system, called AlphaEvolve, could help optimize some of the ...

Annealing processors (APs) are gaining popularity for solving complex optimization problems. Fully-coupled Ising model APs are especially valued for their flexibility, but balancing capacity (number ...