The framework predicts how proteins will function with several interacting mutations and finds combinations that work well together.

Until now, designing complex metamaterials with specific mechanical properties required large and costly experimental and simulation datasets. The method enables ...

The search space for protein engineering grows exponentially with complexity. A protein of just 100 amino acids has 20100 ...

A new artificial intelligence framework developed at Cornell can accurately predict the performance of battery electrolytes ...

Biologically plausible learning mechanisms have implications for understanding brain functions and engineering intelligent systems. Inspired by the multi-scale recurrent connectivity in the brain, we ...

Accurately tracking atmospheric greenhouse gases requires not only fast predictions but also reliable estimates of ...

Interpretable AI model could offer new insights into why medicines cause certain side effects, helping to improve future drug safety predictions.

Korea University researchers have developed a machine-learning framework that predicts solar cell efficiency from wafer quality, enabling early wafer screening and optimized production paths. Using ...

In an X-note, Awni Hannun, of Apple’s ML team, calls the software: “…an efficient machine learning framework specifically designed for Apple silicon (i.e. your laptop!)” The idea is that it ...