The neural network market is poised for rapid growth, driven by rising data volumes, advanced computing, and integration with ...

Learn about the most prominent types of modern neural networks such as feedforward, recurrent, convolutional, and transformer networks, and their use cases in modern AI. Neural networks are the ...

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 ...

What are convolutional neural networks in deep learning? Convolutional neural networks are used in computer vision tasks, which employ convolutional layers to extract features from input data.

Deep neural networks (DNNs), which power modern artificial intelligence (AI) models, are machine learning systems that learn ...

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Spiking Neural Networks (SNNs) are a cutting-edge approach to artificial intelligence, designed to emulate the brain's architecture and functionality. Their ...

Learn more about the new biological computer that fuses brain cells and computer chips — and uses far less energy.

An MIT spinoff co-founded by robotics luminary Daniela Rus aims to build general-purpose AI systems powered by a relatively new type of AI model called a liquid neural network. The spinoff, aptly ...