Choosing the right method for multimodal AI—systems that combine text, images, and more—has long been trial and error. Emory ...

"We believe that our framework combines best practices in the field and provides a conceptual blueprint on how to work with and analyze experimental catalyst data, which should prove useful to future ...

Neuroblastoma is the most common solid tumor in infants and accounts for nearly 15% of all pediatric cancer-related deaths. Despite decades of progress in surgery, chemotherapy, and stem cell ...

Underpinnings and advantages of the scDiffEq model The new machine learning-based framework developed by the researchers models how cells change over time using neural stochastic differential ...

Below is a curated list of machine learning development providers that stand out in 2026 for their ability to build enterprise-grade ML solutions tailored to complex business environments.

Researchers employ machine learning to more accurately model the boundary layer wind field of tropical cyclones. Conventional approaches to storm forecasting involve large numerical simulations run on ...

Linux has long been the backbone of modern computing, serving as the foundation for servers, cloud infrastructures, embedded systems, and supercomputers. As artificial intelligence (AI) and machine ...

The PyTorch team at Meta, stewards of the PyTorch open source machine learning framework, has unveiled Monarch, a distributed programming framework intended to bring the simplicity of PyTorch to ...

The search space for protein engineering grows exponentially with complexity. A protein of just 100 amino acids has 20100 possible variants—more combinations than atoms in the observable universe.