“Recent advances in deep learning have been driven by ever-increasing model sizes, with networks growing to millions or even billions of parameters. Such enormous models call for fast and ...

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 ...

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 ...

The machine-learning programs that underpin their ability to “see” still have blind spots—but not for much longer ...

This article is part of our coverage of the latest in AI research. A new machine learning technique developed by researchers at Edge Impulse, a platform for creating ML models for the edge, makes it ...

The initial research papers date back to 2018, but for most, the notion of liquid networks (or liquid neural networks) is a new one. It was “Liquid Time-constant Networks,” published at the tail end ...