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 ...

Modern neural networks, with billions of parameters, are so overparameterized that they can "overfit" even random, ...

Some artificial intelligence models can already resemble the human brain even before having learned anything. This surprising ...

Learn what CNN is in deep learning, how they work, and why they power modern image recognition AI and computer vision ...

Humans and certain animals appear to have an innate capacity to learn relationships between different objects or events in the world. This ability, known as "relational learning," is widely regarded ...

With artificial intelligence and machine learning (AI/ML) processors and coprocessors roaring across the embedded edge product landscape, the quest continues for high-performance technology that can ...

Many "AI experts" have sprung up in the machine learning space since the advent of ChatGPT and other advanced generative AI constructs late last year, but Dr. James McCaffrey of Microsoft Research is ...

A resistor that works in a similar way to nerve cells in the body could be used to build neural networks for machine learning. Many large machine learning models rely on increasing amounts of ...

As artificial intelligence explodes in popularity, two of its pioneers have nabbed the 2024 Nobel Prize in physics. The prize surprised many, as these developments are typically associated with ...