Recent research has employed chemical reaction networks (CRNs), which harness biochemical processes for computations that translate interactions involving biochemical species into graphical form.

Researchers have uncovered how primate brains transform flat, 2D visual inputs into rich, 3D mental representations of ...

By learning the relevant features of clinical images along with the relationships between them, the neural network can outperform more traditional methods.

The starting point of a FlexOlmo project is a so-called anchor AI model. Every organization that participates in the project ...

Discover how Google DeepMind is using video games and generative AI to train advanced artificial intelligence for real-world applications.

When the top spotty fish in a tank disappears, the runner-up turns aggressive within minutes, rushing and nipping rivals ...

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 and ...

AI vision models have improved dramatically over the past decade. Yet these gains have led to neural networks which, though effective, don’t share many characteristics with human vision. For example, ...

To develop their framework, they employed artificial neural networks (ANNs) trained via reinforcement learning ... and human–robot interactions," explained Iannetti. "For example, robots could ...

Thanks to the neural network, the researchers now suspect, for example, that the black hole at the center of the Milky Way is spinning almost at top speed. Its rotation axis points to Earth.

This is because neural networks require extensive training for their inputs (such as pixels in an image) to produce the appropriate output (such as a description of the image).