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 ...

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 ...

Since the very first days of computer science — a field known for its methodical approach to problem-solving — randomness has played an important role. The first program to run on the world’s first ...

In life, we sometimes have to make decisions without all the information we want; that’s true in computer science, too. This is the realm of online algorithms — which, despite their name, don’t ...

AlphaEvolve uses large language models to find new algorithms that outperform the best human-made solutions for data center management, chip design, and more. Google DeepMind has once again used large ...

Can we ever really trust algorithms to make decisions for us? Previous research has proved these programs can reinforce society’s harmful biases, but the problems go beyond that. A new study shows how ...

Estimating the number of triangles in a graph is a fundamental problem and has found applications in many fields. This ...

Artificial intelligence (AI) is the new arms race and the centerpiece of defense modernization efforts across multiple countries, including the United States. Yet, despite the surge in AI investments, ...

The original version of this story appeared in Quanta Magazine. Computer scientists often deal with abstract problems that are hard to comprehend, but an exciting new algorithm matters to anyone who ...