The rise of AI, graphic processing, combinatorial optimization and other data-intensive applications has resulted in data-processing bottlenecks, as ever greater amounts of data must be shuttled back ...

For about a decade, computer engineer Kerem Çamsari employed a novel approach known as probabilistic computing. Based on probabilistic bits (p-bits), it’s used to solve an array of complex ...

Right now, quantum computers are small and error-prone compared to where they’ll likely be in a few years. Even within those limitations, however, there have been regular claims that the hardware can ...

Shenzhen, May 14, 2025 (GLOBE NEWSWIRE) -- MicroAlgo Inc. (MLGO) Announces Research on Quantum Information Recursive Optimization (QIRO) Algorithm, for Combinatorial Optimization Problems to Expand ...

A framework based on advanced AI techniques can solve complex, computationally intensive problems faster and in a more more scalable way than state-of-the-art methods, according to a new study. A ...

Conventional quantum algorithms are not feasible for solving combinatorial optimization problems (COPs) with constraints in the operation time of quantum computers. To address this issue, researchers ...

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 ...

A quantum computer can solve optimization problems faster than classical supercomputers, a process known as “quantum advantage” and demonstrated by a USC researcher in a paper recently published in ...

For decades, the solution to harder problems has been ‘build a bigger computer’— but what if this is the wrong strategy altogether? This is because some problems defeat computers, not because they are ...