Inspired by microscopic worms, Liquid AI’s founders developed a more adaptive, less energy-hungry kind of neural network. Now ...

Older models struggled with depth issues in 2D images, but the novel neural network handles these problems with ease.

A deep neural network was trained using quantum tunneling to mimic the human ability to view optical illusions.

This model uses advanced neural network architectures, including convolutional neural networks (CNN) and long-short-term ...

Relief-type cultural heritage objects are commonly found in many historical sites worldwide, but often suffer from varying levels of damage and deterioration. Traditional methods for image ...

The latest FSR 3.1 release this year brought significantly improved stability over previous versions. However, there's still ...

Accurately modeling particle movement through fluids is crucial in fields ranging from chemical engineering to aerospace. The ...

Imagine being a passenger in a self-driving car as the vehicle starts veering off the road. It's not a faulty sensor causing the dangerous situation—it's a cyberattack. Hackers can access the deep ...

As renewable energy sources such as wind and solar become more widespread, managing the power grid has become increasingly ...

Custom hardware tailored to specific models can unlock performance gains and energy savings that generic hardware cannot ...

Imagine a future where financial transactions are instantaneous, transcending the traditional bottlenecks of speed and ...

Researchers in China have analyzed the effect of phase change material on BIPV, and created an artificial neural network to ...