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, ...

Liquid Neural Networks could help us to achieve the next level of efficiency with AI/ML Many of us can agree that over the past few years AI/ML progress has been, well, rapid. Now, we’re given yet ...

Peter van der Made is the founder and CTO of BrainChip Ltd. BrainChip produces advanced AI processors in digital neuromorphic technologies. The artificial intelligence (AI) revolution is upon us, and ...

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 ...

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 ...

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 ...