Speech recognition, handwriting recognition, face recognition: just a few of the many tasks that we as humans are able to quickly solve but which present an ever increasing challenge to computer ...

Learn about the most prominent types of modern neural networks such as feedforward, recurrent, convolutional, and transformer networks, and their use cases in modern AI. Neural networks are the ...

MicroCloud Hologram Inc. is advancing the field of quantum computing through its research into Continuous Variable Quantum Neural Networks (CV-QNN), which aim to embed Variational Quantum Circuits in ...

A multivariate analysis of electroencephalography activity reveals super-additive enhancements to the neural encoding of audiovisual stimuli, providing new insights into how the brain integrates ...

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 ...

AI became powerful because of interacting mechanisms: neural networks, backpropagation and reinforcement learning, attention, training on databases, and special computer chips.

Beijing, Feb. 06, 2026 (GLOBE NEWSWIRE) -- WiMi Releases Hybrid Quantum-Classical Neural Network (H-QNN) Technology for Efficient MNIST Binary Image Classification ...