In the ever-evolving world of artificial intelligence, deep neural networks (DNNs) have revolutionized data processing, offering unparalleled accuracy across various ...

Neural architecture search promises to speed up the process of finding neural network architectures that will yield good models for a given dataset. Neural architecture search is the task of ...

The researchers discovered that this separation proves remarkably clean. In a preprint paper released in late October, they ...

Deep neural networks have gained fame for their capability to process visual information. And in the past few years, they have become a key component of many computer vision applications. Among the ...

"The papers and data we've presented at the November IEEE conference show how Verseon's advances in AI produce superior results in life-science applications," said Verseon's Head of AI Ed Ratner. "Our ...

A new technical paper titled “Optimizing event-based neural networks on digital neuromorphic architecture: a comprehensive design space exploration” was published by imec, TU Delft and University of ...

Deep neural networks have a huge advantage: They replace “feature engineering”—a difficult and arduous part of the classic machine learning cycle—with an end-to-end process that automatically learns ...

This blog post is the second in our Neural Super Sampling (NSS) series. The post explores why we introduced NSS and explains its architecture, training, and inference components. In August 2025, we ...

Near-infrared (NIR) photon detection and object recognition are crucial technologies for all-weather target identification.

After 150 years of mystery, neuroscience has finally cracked the code on how language works in the brain—and the answer is surprisingly elegant.