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

Neural networks are the opposite. As he put it, they’re extremely lazy, which is a very desirable property for coming up with new algorithms.

Researchers have developed an algorithm to train an analog neural network just as accurately as a digital one, enabling the development of more efficient alternatives to power-hungry deep learning ...

A new technical paper titled “Exploring Neuromorphic Computing Based on Spiking Neural Networks: Algorithms to Hardware” was published by researchers at Purdue University, Pennsylvania State ...

Deep neural networks (DNNs), the machine learning algorithms underpinning the functioning of large language models (LLMs) and other artificial intelligence (AI) models, learn to make accurate ...

Subscribe Now Neural networks are the backbone of algorithms that predict consumer demand, estimate freight arrival time, and more.

Artificial intelligence is reshaping the world, but do we truly understand how it works This video dives into the fascinating ...

The learning algorithm that enables the runaway success of deep neural networks doesn’t work in biological brains, but researchers are finding alternatives that could. Researchers are learning more ...

On a more basic level, [Gigante] did just that, teaching a neural network to play a basic driving game with a genetic algorithm. The game consists of a basic top-down 2D driving game.

Loosely modeled on the human brain, artificial neural networks are finally finding use in industry.