AI thrives on data but feeding it the right data is harder than it seems. As enterprises scale their AI initiatives, they face the challenge of managing diverse data pipelines, ensuring proximity to ...

Researchers have devised a way to make computer vision systems more efficient by building networks out of computer chips’ logic gates. Networks programmed directly into computer chip hardware can ...

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 ...

In a paper published in the journal Nature, researchers developed a recurrent, transformer-based neural network to decode the surface code, a leading quantum error ...

Members can download this article in PDF format. Microcontroller units (MCUs) with neural-network processors (NPUs) bring edge artificial-intelligence (AI) capabilities to advanced applications ...

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 ...

Neural networks have quietly moved from experimental labs into the core of how modern systems think, learn, and act, becoming foundational to digital infrastructure by 2026. Yet as their complexity ...