Therefore, parallel computing and acceleration techniques have become crucial in the research and application of neural networks, as they can significantly enhance the performance and efficiency of ...

At a time when conflict and division dominate the headlines, a new study from UCLA finds remarkable similarities in how mice ...

Overview PyTorch and JAX dominate research while TensorFlow and OneFlow excel in large-scale AI trainingHugging Face ...

John Hopfield and Geoffrey Hinton won the Nobel Prize in Physics for their work on artificial neural networks and machine learning. Jonathan Nackstrand / AFP via Getty Images A pair of scientists—John ...

The idea of simplifying model weights isn't a completely new one in AI research. For years, researchers have been experimenting with quantization techniques that squeeze their neural network weights ...

A research team has studied the development of the Shanghai Typhoon Model from a traditional physics-based regional model toward a data-driven, machine-learning typhoon forecasting system. They ...

Recurrent Neural Networks (RNNs) are AI models designed to process sequential data, capable of sequentially handling words and temporarily storing previously processed information in short-term memory ...