Graph neural networks (GNNs) have emerged as a powerful framework for analyzing and learning from structured data represented as graphs. GNNs operate directly on graphs, as opposed to conventional ...

As we increase our understanding of the human connectome, our ability to understand the brain's phenomenal information throughput grows in tandem. We now have a partial network diagram of the human ...

Binary digits and circuit patterns forming a silhouette of a head. Neural networks and deep learning are closely related artificial intelligence technologies. While they are often used in tandem, ...

As the name suggests, neural networks are inspired by the brain. A neural network is designed to mimic how our brains work to ...

Every day, various types of sensory information fromthe external environment are transferred to the brainthrough different modalities and then processed to generate a series of coping behaviors. Among ...

Training AIs remains very processor-intensive, in part because traditional processing architectures are poor matches for the sorts of neural networks that are widely used. This has led to the ...

Like other sectors of society, artificial intelligence is fundamentally changing how investors, traders and companies make ...

We talk a lot about AI, machine learning, and neural nets, but what's a neural net in the first place? Share on Facebook (opens in a new window) Share on X (opens in a new window) Share on Reddit ...