Neural networks are a key technology in artificial intelligence (AI) that are inspired by the human brain’s structure and ...

A new study proposes NdLinear, a multi-dimensional linear layer that preserves data structure and slashes parameter counts across neural networks — from CNNs to Transformers. It outperforms standard ...

Often, each node in a layer is connected to every node in the subsequent layer to send information forward in the network. “When you write code to build an artificial neural network, you're basically ...

CytoTronics, Inc., a pioneer of semiconductor-based platforms for discovery in cell biology, launched its Neural application for Pixel systems today. A pioneering innovation for neurodegenerative ...

Systolic arrays never took off when they first emerged, but they are shaping up as the dominant ways to structure an AI ... can keep the entirety of the neural network on die," he said.

The study provides compelling evidence that local dopamine release serves as a crucial signal for neural plasticity in the motor cortex, enabling the necessary adaptations for producing precise and ...

A new editorial was published in Oncotarget, Volume 16, on April 4, 2025, titled “Deep learning-based uncertainty ...

Within this network, the premotor region HVC is essential ... Their findings suggest HVC is organised into highly structured neural modules that contain both projection neurons and inhibitory ...

One notable missing feature in most ANN models is top-down feedback, i.e. projections from higher-order layers to lower-order layers in the network. Top-down feedback is ubiquitous in the brain, and ...

Artificial neural networks have been applied to problems ranging from speech recognition to prediction of protein secondary structure ... An artificial neural network can be created by simulating ...