Researchers paired graphene and cellulose nanoparticles with a genetic-algorithm-optimized neural network to predict hybrid ...

While neural networks can help to improve the accuracy of fluid flow simulations, new research shows how their accuracy is limited unless the right approach is taken. By embedding fluid properties ...

The study was conducted by a team led by Xiaofan Li from the University of Hong Kong, China. The researchers designed the framework to address a persistent challenge in fluid-structure interaction: ...

An MIT spinoff co-founded by robotics luminary Daniela Rus aims to build general-purpose AI systems powered by a relatively new type of AI model called a liquid neural network. The spinoff, aptly ...

The simplified approach makes it easier to see how neural networks produce the outputs they do. A tweak to the way artificial neurons work in neural networks could make AIs easier to decipher.