AI is helping farmers automate weed control and create custom tools as they navigate industry challenges and sustainability ...

As June comes to a close, edie and our innovation partner Springwise highlight six of this month’s exciting innovation ...

Have you ever planned a picnic only to have the weather turn against you, leaving you soggy and disappointed? Weather ...

Artificial intelligence is transforming meteorological prediction through innovative approaches to tropical cyclone tracking ...

As a result, energy-intensive infrastructures that try to maximize the use of renewable energy sources (RES), such as ...

Training a deep convolutional neural network (CNN) from scratch is difficult because it requires a large amount of labeled training data and a great deal of expertise to ensure proper convergence. A ...

Thanks to the neural network, the researchers now suspect, for example, that the black hole at the center of the Milky Way is spinning almost at top speed. Its rotation axis points to Earth.

The safety of inorganic nanoparticles (NPs) remains a critical challenge for their clinical translation. To address this, we developed a machine learning (ML) framework that predicts NP toxicity both ...

Data-driven deep learning techniques have made notable advancements in modeling electromagnetic scattering problems. However, its accuracy on the testing dataset can be heavily reduced when data ...

Rose Yu has drawn on the principles of fluid dynamics to improve deep learning systems that predict traffic, model the climate, and stabilize drones during flight.

Subsequently, we constructed a closed-loop approach that integrates machine learning (ML), density functional theory (DFT), high-throughput virtual screening (HTVS), and experiment to accelerate the ...