Materials testing remains a cornerstone of engineering and manufacturing, ensuring that components and structures—from aircraft fuselages to bridge supports—perform reliably under demanding conditions ...

AI and data science are no longer specialist skills confined to computational biology departments; they are core tools of the modern life science research workflow. From machine learning (ML) models ...

Physics-informed machine learning connects atomic structure with ion transport and electrolyte stability, accelerating better sodium- and lithium-ion batteries.

The future of equitable AI in community health centers will be measured by how effectively we are able to demand partnership ...

Single-cell RNA-seq AI analysis has become the default way to make sense of the millions of expression measurements a single experiment can now generate. Turning raw sequencing counts into ...

OpenAI’s ad revenue forecast is on pace to miss its 2030 target by 90%, according to Emarketer. The post The latest ...

Recent progress in materials, flexible sensors, and embedded intelligence has significantly accelerated the development of ...

For grid-scale energy storage and national energy resilience, the U.S. needs better batteries. Lawrence Livermore National ...

Biologically plausible learning now reaches 96.7% on MNIST and 61.7% on CIFAR-10 without backpropagation, as Sakana AI ...

Roughly one billion people worldwide are estimated to live with obstructive sleep apnea, and a large share of them don't know it. For the ones who do get diagno ...

The line between art and digital tools has become extremely thin. Painters work with neural networks, sculptors prototype in ...

Key market opportunities in AI for omics studies include the demand for precision medicine, adoption of AI in drug discovery, ...