Neuroscientists want to understand how individual neurons encode information that allows us to distinguish objects, like ...

Deep learning models, such as convolutional neural networks (CNNs) and recurrent neural networks (RNNs) are designed to partly emulate the functioning and structure of biological neural networks. As a ...

While humans concentrate on the meaning of objects, artificial intelligence focuses on visual characteristics.

The ability to precisely predict movements is essential not only for humans and animals, but also for many AI applications — from autonomous driving ...

Active vision dynamically refines spatiotemporal neural representations, optimising visual processing through scanning behaviour and non-associative learning, providing insights into efficient sensory ...

Researchers have developed a groundbreaking 3D brain model that closely mirrors the architecture and function of the human brain.

A new discovery of how bees use their flight movements to facilitate remarkably accurate learning and recognition of complex visual patterns could mark a major change in how next-generation AI is ...

We seem to collect information because we have the ability to do so, but we are so busy collecting it that we haven’t devised a means of using it. The true measure of any society is not what it knows ...

Neural Texture Compression (NTC) is a new technique that improves texture quality while reducing VRAM usage. It relies on a specialized neural network trained to compress ...

To transition from LLMs to AGI, we need to overcome several major limitations and introduce fundamentally new capabilities ...

New research reveals that the brain may be learning even during unstructured, aimless exploration. By recording activity in ...