Neural networks first treat sentences like puzzles solved by word order, but once they read enough, a tipping point sends ...

The language capabilities of today's artificial intelligence systems are astonishing. We can now engage in natural ...

A Comparative Study of AI-Powered Chatbot for Health Care. Journal of Computer and Communications, 13, 48-66. doi: 10.4236/jcc.2025.137003 . The need for this research arises from the increasing ...

Nvidia's Transformer model for DLSS has exited the beta stage and will replace the CNN-based approach very soon with DLSS 4.

More information: Yi Teng et al, Solving the fractional quantum Hall problem with self-attention neural network, Physical Review B (2025). DOI: 10.1103/PhysRevB.111.205117.

Training Transformers Large language models are built around mathematical structures called artificial neural networks. The many “neurons” inside these networks perform simple mathematical operations ...

Recurrent neural networks struggled to parse longer chunks of text. Take a passage like Joe is a baseball player, and after a good breakfast he went to the park and got two hits.

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.

Secondly, the Double Hidden Layer Recurrent Neural Network (DHLRNN) is proposed to model the mapping relationships between variables in the power flow constraints, aiming to calculate the virtual ...

Then, three different neural networks—1D-CNN, Muti-Transformer, and Wav2Vec2.0—are used to locate the defects in the collected ultrasonic testing data. The performance of the network is verified with ...

As an important secondary power supply of aircraft power supply system, the normal operation of aviation twelve-pulse transformer rectifier unit is of great significance to the safe operation of ...