Penn State scientists have devised a new method to predict superconducting materials that could work at higher temperatures.

The proof-of-concept could pave the way for a new class of AI debuggers, making language models more reliable for business-critical applications.

Harvard’s Berkman Klein Center for Internet & Society welcomes applications for its 2026 and 2026-2027 fellowships.

In an ideal world, an AI model looking for new materials to build better batteries would be trained on millions or even ...

As the global focus on artificial intelligence (AI) continues to expand, the demand for high-performance computing resources ...

Chimpanzees may have more in common with human thinkers than previously thought. A new study published in Science by an ...

Explore the NVIDIA DGX Spark, a $4,000 mini supercomputer powerhouse featuring a 20-core Nvidia Grace CPU and 128 GB memory, ...

Scientists have developed a groundbreaking tool called Effort.jl that lets them simulate the structure of the universe using ...

Mathematics is deemed to be beyond figures. It is described as the foundation of resilience in society.

Atrial fibrillation (AFib) is a cardiac disorder in which the chambers of the heart beat rapidly and irregularly. It's the ...

The integration of single-cell RNA sequencing (scRNA-seq) with AI has become a cornerstone for deciphering tumor heterogeneity. For instance, in pancreatic ductal adenocarcinoma (PDAC), spatial ...