Reducing the precision of model weights can make deep neural networks run faster in less GPU memory, while preserving model accuracy. If ever there were a salient example of a counter-intuitive ...

An innovative planar spoof plasmonic neural network (SPNN) platform capable of directly detecting and processing terahertz (THz) electromagnetic signals has been unveiled by researchers at City ...

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 ...

The era of AI evangelism is giving way to an era of rigorous evaluation, as 2026 sees a pivotal shift in how we measure neural network capabilities. Recent breakthroughs in stress testing, including ...