Can a neural network be constructed entirely from DNA and yet learn in the same way as its silicon-based brethren? Recent ...

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.

This study presents valuable computational findings on the neural basis of learning new motor memories without interfering with previously learned behaviours using recurrent neural networks. The ...

Researchers have developed a new tool, bimodularity, that adds directionality to community detection in networks.

AI models like artificial neural networks and language models help scientists solve a variety of problems, from predicting the 3D structure of proteins to designing novel antibiotics from scratch.

Neural networks, from GPT-4 to Stable Diffusion, are built by wiring together perceptrons, which are highly simplified simulations of the neurons in our brains.

Although not the first video game ever produced, Pong was the first to achieve commercial success and has had a tremendous influence on our culture as a whole. In Pong’s time, its popularity ...

This year, Shiyuan Co., Ltd. has newly obtained 290 patent authorizations, a decrease of 40.57% compared to the same period last year. According to the company's mid-2025 financial data, in the first ...

For decades, scientists have looked to light as a way to speed up computing. Photonic neural networks—systems that use light instead of electricity to process information—promise faster speeds ...